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The growing interest in the directed energy deposition process to fabricate and repair thin wall structures has warranted a deeper understanding in the properties of the method’s basic building block: clad formation. In this study, clads obtained by depositing stainless steel 316L (SS316L) powder with three different process parameters, namely laser power, laser traverse speed, and powder mass flow rate, were investigated. Repeatability was ensured through a wide sample range per parameter. From the data measurement, the clads have an average hardness close to the typical 200 Hv of SS316L materials, indicating that Hall-Petch effect is dominant. The study also shows that: (i) Laser power is the most significant factor to clad depth, but has little influence on clad thickness. (ii) Laser traverse speed is the dominant parameter to clad height. (iii) Powder mass flow rate tends to compensate depth reduction with thickness gain, resulting in no noticeable effect on clad height. Increasing laser power was observed to be the most effective way to prevent clads from forming with zero dilution, an indicator to how well the printed clad is bonded to the substrate. A dimensionless analysis was derived from the set of SS316L clads. Through validation with different stainless steel datasets and extrapolation to a larger parametric range, the analysis was demonstrated to be able to facilitate the selection of process parameters to meet given requirements on the clad dimensions. As its application is intuitive, the analysis has the potential to be adopted as a standard preprinting tool that will increase success rate, thus improving the manufacturing turnaround time. National Research Foundation (NRF) Submitted/Accepted version This research is supported by the National Research Foundation, Prime Minister’s Office, Singapore, under its Medium Sized Centre funding scheme.

This study provides a quantitative way to tailor the grain structure in laser powder bed fusion (LPBF). Square-bottomed columnar grains (SCGs) were developed with a certain width roughly equal to the hatch spacing. The development of SCGs relied on different distinguishable regions, which were identified based on the differences in microstructural features between the melt-pool side and centreline. High lattice rotation accumulated at the melt-pool centreline, leading to grain boundaries forming at the centreline regions. The ultrasonic attenuation measurements and microhardness tests further validated the controllable properties. The findings indicated a novel approach to customise the material property. Agency for Science, Technology and Research (A*STAR) Published version This work was supported by A∗STAR Science and Engineering Research Council [Grant Number A20F9a0045]; Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong [Grant Number RNE-p2-21].

Fabric-based materials have demonstrated promise for high-performance wearable applications but are currently restricted by their deficient mechanical properties. Here, this work leverages the design freedom offered by additive manufacturing and a novel interlocking pattern to for the first time fabricate a dual-faced chain mail structure consisting of 3D re-entrant unit cells. The flexible structured fabric demonstrates high specific energy absorption and specific strength of up to 1530 J kg-1 and 5900 Nm kg-1 , respectively, together with an excellent recovery ratio of ≈80%, thereby overcoming the strength-recoverability trade-off. The designed dual-faced structured fabric compares favorably against a wide range of materials proposed for wearable applications, attributed to the synergetic strengthening of the energy-absorbing re-entrant unit cells and their unique topological interlocking. This work advocates the combined design of energy-absorbing unit cells and their interlocking to extend the application prospects of fabric-based materials to shape-adaptive protection. Published version This study was supported by the RIE2020 Industry Alignment Fund – Industry Collaboration Projects (IAF-ICP) Funding Initiative, Singapore and cash and in-kind contribution from the industry partner, HP Inc.

In additive manufacturing (AM), due to large number of process parameters and multiple responses of interest, it is hard for AM designers to attain optimal part performance without a systematic approach. In this research, a data-driven framework is proposed to achieve the desired AM part performance and quality by predicting part properties and optimising AM process parameters effectively and efficiently. The proposed framework encompasses efficient sampling of design space and establishing the initial experiment points. Based on established empirical data, surrogate models are used to characterise the influence of critical process parameters on responses on interest. Furthermore, process maps can be generated for enhancing understanding on the influence of process parameters on responses of interests and AM process characteristics. Subsequently, multi-objective optimisation coupled with a multi criteria decision-making technique is applied to determine an optimal design point, which maximises the identified responses of interest to meet the part functional requirements. A case study is used to validate the proposed framework for optimising an ULTEM™ 9085-fused filament fabrication part to meet its functional requirements of surface roughness and mechanical strength. From the case study, results indicate that the proposed approach is able to achieve good predictive results for responses of interest with a relatively small dataset. Furthermore, process maps generated from the surrogate model provide a visual representation of the influence between responses of interest and critical process parameters for FFF process, which traditionally requires multiple investigations to arrive at similar conclusions. Economic Development Board (EDB) Nanyang Technological University National Research Foundation (NRF) This research is supported by a grant from ST Engineering Aerospace, EDB-IPP, the National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme, and Singapore Centre for 3D Printing.

Melting and solidification in metal-based additive manufacturing (AM) ultimately determine the crystallographic texture, cellular/columnar dendritic growth, solute segregation, and resultant materials properties. The microstructure of AM-built alloys is closely related to various physics during the printing process. In the present study, a multi-physics model was developed to simulate the evolution of grain and dendritic-scale microstructure during laser AM of a Ni-based alloy. Computational fluid dynamics was used to simulate the melt pool dynamics and temperature distribution for the laser powder bed fusion process. Using Ni-Nb as an analogue to Inconel 625, a phase field model was applied to predict the microstructural features within a two-dimensional solidified melt pool. The predicted results exhibit fair agreement with experimental characteristics in the literature, including melt pool profile, dendrite size, dendrite morphology, and crystallographic texture. The multi-physics model paves the way for computationally predicting the chemistry-process-structure relationship in AM-built alloys, which helps to understand the fundamental physics of AM solidification. National Research Foundation (NRF) The authors acknowledge the support by the National Research Foundation, Prime Minister’s Office, Singapore, under its Medium Sized centre funding scheme.

Mechanical anisotropy greatly influences the applications of materials printed by additive manufacturing techniques such as Multi Jet Fusion (MJF) and selective laser sintering. However, the mechanical anisotropy of MJF-printed fibre–reinforced polymer composites has not been well understood. In this work, the effect of the fibre length on the mechanical performance of MJF-printed glass fibre–reinforced polyamide 12 (GF/PA12) composites is systematically investigated. Both experimental and simulation results confirm that longer fibres are in favour of fibre alignment in the powder spreading direction. The composite parts with longer fibres exhibit higher porosity. When GFs with an average length of 226 μm are added, the ultimate tensile strength and tensile modulus of the composites measured in the powder bed spreading direction are remarkably improved by 51% and 326%, respectively, as compared with those of neat PA12 specimens. This work provides guidance for the printing of other high-strength fibre–reinforced polymer composites. Published version This work was supported by Industry Alignment Fund-Industry Collaboration Projects Grant [Grant number I1801E0028].

Additive manufacturing of electronic devices using inkjet printing provides a potential alternative approach in substitution for conventional electronic fabrication processes. However, the complex nature of inkjet printing involves the liquid deposition and film formation from the vaporization of solvent, which makes it different from film created by conventional deposition methods. Inkjet printing of zinc oxide (ZnO), which is a widely utilized semiconductor, produces polycrystalline film composed of nano-size grains, which could significantly influence the properties of printed film. In this study, low-temperature annealing was employed to treat inkjet-printed ZnO for UV photodetection application, and its influence on electrical properties was studied. Band bending was characterized using the Mott-Schottky plot which examines the charge distribution of the films. It is found that the annealing of inkjet-printed polycrystalline ZnO film has improved its electrical properties, which could be attributed to the reduction of band bending due to the merging of grains. The treatment also helps to reduce impurities of the film, such as zinc hydroxide complexes, which is common for solution-derived films. Hence, the study could pay the way for the improvement of electrical properties of inkjet-printed functional materials. Ministry of Education (MOE) Nanyang Technological University Published version This work was supported by Nanyang Technological University and the Ministry of Education of Singapore through a Ph.D. Scholarship and AcRF Tier 1 research grant (RG 96/18).

Multi Jet Fusion (MJF) has gradually been utilised for the commercial fabrication of final products. In particular, the mechanical properties of MJF-printed polyamide 12 (MJF PA12) parts have been widely investigated by manipulating the process parameters such as the printing orientation and the cooling rate. In this work, the effects of build positions on the thermal history, crystallization, and mechanical properties of MJF PA12 parts were investigated. The thermal history of printed parts was obtained using the MJF Thermal Prediction Engine software developed by Hewlett-Packard HP Labs (HP Inc.). As compared to the parts printed at the boundaries, those in the centre region experienced a slower cooling rate, which was favourable for crystal growth. Both the crystallite size and crystallinity of the parts in the centre region were larger than those of the parts at the boundaries. The parts printed in the centre region had slightly higher tensile modulus and significantly smaller elongation at break and strain energy density than those printed at the boundaries. The tensile strength of the parts at different locations was comparable. This work serves as a guide to selecting the build position of MJF-printed parts to achieve desirable mechanical properties. Published version This work was supported by Industry Alignment Fund-Industry Collaboration Projects Grant: [Grant Number I1801E0028].

The 4th Industrial Revolution integrates the digital revolution into the physical world, opens up new directions for research in several fields, including artificial intelligence and 3D printing. Data-driven models have been developed thanks to the advancement in computational power and machine learning algorithms, which enables machines to learn and execute a certain task through data without the need to formulate them explicitly. Machine learning have been used in 3D printing to enhance the product quality and productivity through in-situ monitoring, to optimize design and process parameters, and to speed up the prediction microstructure evolution through the development of physic-based data driven surrogate model. This article summarizes the work done by our group on the use of machine learning in 3D printing and provides an outlook on the 3D printing industry. National Research Foundation (NRF) This research is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme.

Soft robotics is gaining more interest because of the increasing demands in the manufacturing line to handle various types of delicate parts. The progress in the development of soft robotics does not only rely on the technology in the fabrication of the soft gripper structures, it also depends significantly on the integration of electronics such as the soft sensors and circuits. 3D printing technology is an important manufacturing tool for soft robotics due to its ability to fabricate designs with complex geometry and multi-material printing capability. Herein, the recently developed soft electronics such as sensors and circuits that involved the use of 3D printing technology are focused upon. In this article, the various designs of soft sensors, their fabrication techniques, and the materials used will be introduced. Besides, the design considerations and requirements for soft electronics will be presented. Lastly, the potential applications and the future outlook of soft electronics for soft grippers will be discussed. Agency for Science, Technology and Research (A*STAR) Submitted/Accepted version This research is supported by the Agency for Science, Technology and Research (A*STAR) under its IAF-ICP Programme ICP1900093 and the Schaeffler Hub for Advanced Research at NTU.

The 3D cementitious material printing method is an extrusion-based additive manufacturing strategy in which cementitious materials are extruded through a dynamic nozzle system to form filaments. Despite its ability to fabricate structures with high complexity and efficiency, the uneven material distribution during the extrusion and deposition process is often encountered when a radial toolpath is introduced. This limits the design freedom and printing parameters that can be utilized during radial toolpath printing. Here, we report a facile strategy to overcome the existing challenges of cementitious material non-homogeneity by rationally developing new nozzle geometries that passively compensate the differential deposition rate encountered in conventional rectangular nozzles. Using two-phase numerical study, we showed that our strategy has the potential of achieving a homogeneous mass distribution even when the nozzle travel speed is unfavorably high, while filament from a rectangular nozzle remains highly non-homogenous. The material distribution unevenness can be reduced from 1.35 to 1.23 and to 0.98 after adopting trapezoid and gaussian nozzles, indicating improvements of 34.3% and 94.2%, respectively. This work not only outlines the methodology for improving the quality of corner/curved features in 3DCMP, but also introduces a new strategy which can be adopted for other extrusion-based fabrication techniques with high material inertia. National Research Foundation (NRF) Published version This research is supported by the National Research Foundation, Singapore, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme, Singapore Centre for 3D Printing, Chip Eng Seng Corporation Ltd., CES_SDC Pte. Ltd., and CES_INNOVFAB Pte. Ltd.

Critical bone defects are the most difficult challenges in the area of tissue repair. Polycaprolactone (PCL) scaffolds, associated with hydroxyapatite (HA) and tricalcium phosphate (TCP), are reported to have an enhanced bioactivity. Moreover, the use of electrical stimulation (ES) has overcome the lack of bioelectricity at the bone defect site and compensated the endogenous electrical signals. Such treatments could modulate cells and tissue signaling pathways. However, there is no study investigating the effects of ES and bioceramic composite scaffolds on bone tissue formation, particularly in the view of cell signaling pathway. This study aims to investigate the application of HA/TCP composite scaffolds and ES and their effects on the Wingless-related integration site (Wnt) pathway in critical bone repair. Critical bone defects (25 mm2) were performed in rats, which were divided into four groups: PCL, PCL + ES, HA/TCP and HA/TCP + ES. The scaffolds were grafted at the defect site and applied with the ES application twice a week using 10 µA of current for 5 min. Bone samples were collected for histomorphometry, immunohistochemistry and molecular analysis. At the Wnt canonical pathway, HA/TCP and HA/TCP + ES groups showed higher Wnt1 and β-catenin gene expression levels, especially HA/TCP. Moreover, HA/TCP + ES presented higher Runx2, Osterix and Bmp-2 levels. At the Wnt non-canonical pathway, HA/TCP group showed higher voltage-gated calcium channel (Vgcc), calmodulin-dependent protein kinase II, and Wnt5a genes expression, while HA/TCP + ES presented higher protein expression of VGCC and calmodulin (CaM) at the same period. The decrease in sclerostin and osteopontin genes expressions and the lower bone sialoprotein II in the HA/TCP + ES group may be related to the early bone remodeling. This study shows that the use of ES modulated the Wnt pathways and accelerated the osteogenesis with improved tissue maturation. Published version This project was partially supported by the São Paulo Research Foundation (FAPESP), grants numbers 2018/21167-4 and 2016/23237-4, CNPq (“Conselho Nacional do desenvolvimento Científico e Tecnológico”) grant number 423710/2018-4.

Peer reviewed: True, Funder: Wellcome Leap 1kD Program, The first years of an infant's life represent a sensitive period for neurodevelopment where one can see the emergence of nascent forms of executive function (EF), which are required to support complex cognition. Few tests exist for measuring EF during infancy, and the available tests require painstaking manual coding of infant behaviour. In modern clinical and research practice, human coders collect data on EF performance by manually labelling video recordings of infant behaviour during toy or social interaction. Besides being extremely time-consuming, video annotation is known to be rater-dependent and subjective. To address these issues, starting from existing cognitive flexibility research protocols, we developed a set of instrumented toys to serve as a new type of task instrumentation and data collection tool suitable for infant use. A commercially available device comprising a barometer and an inertial measurement unit (IMU) embedded in a 3D-printed lattice structure was used to detect when and how the infant interacts with the toy. The data collected using the instrumented toys provided a rich dataset that described the sequence of toy interaction and individual toy interaction patterns, from which EF-relevant aspects of infant cognition can be inferred. Such a tool could provide an objective, reliable, and scalable method of collecting early developmental data in socially interactive contexts.

Crystallization of polyamide 12 (PA12) is an essential process requiring thorough investigation for evaluating the mechanical properties after the polymer parts are manufactured. The change in crystallization temperature results in different crystallization behaviors for PA12. Hence, the crystal morphology of PA12 achieved provides important information about crystallization behavior, especially for those produced through additive manufacturing due to its heterogenous cooling rate in a single print bed. Considering the need of investigating PA12 crystallization using phase-field modeling, this paper aims to simulate the spherulite morphology of PA12 undergoing isothermal crystallization. This model is compared with the spherulite morphologies obtained from the optical microscopy test. The model shows that PA12 spherulites have thicker dendrites when the isothermal temperature is higher. The present phase-field model can determine the spherulite morphologies of bulk printed PA12 based on the crystallization condition and be used to evaluate the properties of the printed part. Nanyang Technological University This research work is conducted in collaboration with HP Inc. and supported by Nanyang Technological University and the Singapore Government through the Industry Alignment Fund–Industry Collaboration Projects Grant (I1801E0028).

Additive manufacturing (AM) of 410L ferritic/martensitic stainless steel via laser metal deposition (LMD) process is investigated. The carbon content of 410L powder used is low at 0.004 wt%. Heat treatment is utilized to study the microstructure and mechanical properties evolution of the deposited material. The microstructure of as-built low carbon 410L includes equiaxed ferrite phase, widmanstatten ferrite, martensite, and (Fe,Cr)23C6 nanoprecipitates. After heat treatment at 1000 °C for 10 min, refined equiaxed grains and high fraction of martensitic phase are formed. The yield strength is 601.9 MPa for as-built condition and 930.6 MPa for heat-treated condition (1000 °C/10 min); the ultimate tensile strength (UTS) is 923.0 MPa for as-built condition and 1101.5 MPa for the heat-treated condition (1000 °C/10 min); the elongation is 17.7% for as-built condition and 15.1% for the heat-treated condition (1000 °C/10 min). The low carbon 410L fabricated using LMD shows a better combination of high strength and good ductility compared with 12Cr stainless steels with higher carbon contents fabricated using conventional processes. This study provides a benchmark of 410L stainless steel fabricated using fusion-based metal AM process. Submitted/Accepted version This research was funded by LUX Photonics Consortium and Precision Laser Solutions Pte. Ltd. through grants #020408-00002 and #020408-00003.

The expanding capabilities and decreasing costs of additive manufacturing have resulted in the increased adoption of micro-unmanned aerial vehicles (micro-UAVs) among professionals and hobbyists. Due to safety regulatory requirements of UAV operations, weight is generally the overriding design features of interest for micro-drones, but it often comes as a trade-off against the durability, loading constraints, and other subsystem equipment. Nevertheless, ultra-lightweight structures can be realized through the adoption of both 3D-printing and topology optimization without compromising the structural integrity and overall strength and this article explores the use of these two technologies for designing and manufacturing optimized ultralight micro-UAVs. First, material properties of Nylon 12 (PA12) manufactured using selective laser sintering (SLS) were accurately characterized via mechanical testing and ultrasonic means. These properties were verified by comparing the mechanical response of 3-point and 4-point bending tests with corresponding finite element (FE) simulation. Next, topology optimization was performed to produce an optimized structure of a Z-split configured lightweight micro-quadcopter. The optimized design is then 3D-printed and subsequently validated through a load test for verification against the optimized FE simulation-based design. A close correlation was obtained between the numerical and experimental data, suggesting that topology optimization with 3D printing can be safely and reliably adopted for the design and rapid prototyping of micro-UAVs, whilst catering to different specifications and requirements. National Research Foundation (NRF) Submitted/Accepted version This research is jointly supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme, and ST Engineering Aerospace Ltd., under project titled ‘3D Printing of micro UAV’.

We propose and employ a novel X-shaped geometry to strengthen the 〈001〉 || z crystallographic texture – distinctive of the electron beam powder-bed fusion technique, for a 3D-printed austenitic stainless steel of type 316 L. The prism angles of the X-shaped parts are varied among 60, 90, and 120 degrees (X-60, X-90, and X-120) to investigate the effect it has on the parts’ properties. Strikingly, the strength of the 〈001〉 || z crystallographic texture and columnar grain width with increasing prism angle is seen to follow a ‘bell-curve’ profile which peaks with the X-90 shape. A distinct mechanical response of X-shaped samples is obtained with X-60 samples showing significantly stronger strain-hardening behavior along with cracking concentrated along the grain boundaries between 〈110〉 || z and 〈001〉 || z grains. Molecular dynamics simulations are utilized to rationalize this phenomenon. Agency for Science, Technology and Research (A*STAR) Ministry of Education (MOE) National Research Foundation (NRF) This work was partially supported by the Medium-Sized centre funding scheme awarded by the National Research Foundation, Prime Minister’s Office, Singapore. We also acknowledge support by the Structural Metal Alloys Program of the Agency for Science, Technology and Research of Singapore (grant number A18B1b0061). Xipeng Tan acknowledges the funding supoort by the Singapore Ministry of Education Academic Research Fund Tier 1 (22-4902-A0001).

In this work, our proof-of-concept study can be used to predict the number of cells within printed droplets based on droplet velocity at two different points along the nozzle-substrate distance using machine learning approaches. A novel high-throughput contactless method that combines the use of an optical system and machine learning algorithms was utilized for various applications such as cell detection within single droplets (presence/absence of cells) and prediction of the total number of printed cells within multiple droplets by measuring the droplet deceleration between two positions along the nozzle-substrate distance. The proposed method in this work has demonstrated good accuracy in cell prediction within single droplet (presence/absence of cells) and low prediction error in determining number of cells within multiple droplets by reducing the error by a factor of (Fomrula Presented.). for N droplets measured in a batch. The performance of five different machine learning algorithms such as linear regression, support vector regression, decision tree regressor, random forest regression, and extra tree regression were compared to determine the best algorithm for each type of application. The random forest regressor algorithm demonstrated the highest accuracy at 80% in cell prediction (presence/absence of cells) within single droplets, while the extra tree regressor demonstrated the lowest mean error of 12% in predicting the number of printed cells within multiple droplets (e.g., 20 droplets on same spot). By incorporating these models in a droplet monitoring system, live assessment of the number of printed cells during an inkjet-based bioprinting process can be achieved. Submitted/Accepted version This study is supported under the RIE2020 Industry Alignment Fund – Industry Collaboration Projects (IAF-ICP) Funding Initiative, as well as cash and in-kind contribution from the industry partner, HP Inc., through the HP-NTU Digital Manufacturing Corporate Lab.

AlSi10Mg is often used to fabricate functional parts by Laser Beam Powder Bed (LBPB) fusion but is limited by the residual stresses formed during the process. Conventional methods of stress relief of AlSi10Mg often compromise the mechanical properties due to the high-temperature used. This paper solves the dilemma by using a novel method of residual stress relief without compromising its mechanical properties. This process uses a lower temperature for treatment followed by uneven cooling, inducing thermal stress during the cooling process such that it cancels out the existing residual stress that remains. The compressive strength of the part was not compromised after this treatment, verified by microstructure images. From electron backscatter diffraction (EBSD) analysis, the change in density of low angle grain boundaries (LAGB) and magnitude of residual stress relieved via this method followed the same trend, indicating the induction of dislocations from the stress-induced during uneven cooling. Agency for Science, Technology and Research (A*STAR) Economic Development Board (EDB) National Research Foundation (NRF) Published version This research was supported by Makino Asia Pte Ltd [account no. 04IDS000476N035] through the Economic Development Board Industrial Postgraduate Programme and the National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme. This work was also supported by the Singapore Centre for 3D Printing (SC3DP), School of Mechanical and Aerospace Engineering (MAE), Nanyang Technological University (NTU), and Advanced Remanufacturing and Technological Center (ARTC) [account no. 04SBS000515C160], Agency for Science, Technology and Research (A*STAR), Singapore, through the use of its additive manufacturing facilities.

Laser powder bed fusion (L-PBF) is one of the most widely used metal additive manufacturing technology for fabrication of functional and structural components. However, inconsistency in quality and reliability of L-PBF products is still a significant barrier preventing it from wider adoption. Machine learning (ML) of monitoring data offers a unique solution to effectively identify possible defects and predict the quality of L-PBF products. In this work, we introduce a semi-supervised ML approach to detect anomalies that occurred in L-PBF products. We train the ML model to classify surface appearances in the reference monitoring data. We then correlate the classified appearances to post-process characteristics, e.g. surface roughness, morphology, or tensile strength. We demonstrate that the established correlation enables the determination of key appearances indicative of the quality of the printed samples including anomaly-free, lack-of-fusion and overheated. We further validate our ML approach by performing prediction on test samples having various geometries. National Research Foundation (NRF) Published version This research is supported by Republic of Singapore’s National Research Foundation Singapore under its Innovation Cluster Programme (NAMIC), and VinUniversity, Vietnam.

Skin is a hierarchical and multi-cellular organ exposed to the external environment with a key protective and regulatory role. Wounds caused by disease and trauma can lead to a loss of function, which can be debilitating and even cause death. Accelerating the natural skin healing process and minimizing the risk of infection is a clinical challenge. Electrospinning is a key technology in the development of wound dressings and skin substitutes as it enables extracellular matrix-mimicking fibrous structures and delivery of bioactive materials. Honey is a promising biomaterial for use in skin tissue engineering applications and has antimicrobial properties and potential tissue regenerative properties. This preliminary study investigates a solution electrospun composite nanofibrous mesh based on polycaprolactone and a medical grade honey, SurgihoneyRO. The processing conditions were optimized and assessed by scanning electron microscopy to fabricate meshes with uniform fiber diameters and minimal presence of beads. The chemistry of the composite meshes was examined using Fourier transform infrared spectroscopy and X-ray photon spectroscopy showing incorporation of honey into the polymer matrix. Meshes incorporating honey had lower mechanical properties due to lower polymer content but were more hydrophilic, resulting in an increase in swelling and an accelerated degradation profile. The biocompatibility of the meshes was assessed using human dermal fibroblasts and adipose-derived stem cells, which showed comparable or higher cell metabolic activity and viability for SurgihoneyRO-containing meshes compared to polycaprolactone only meshes. The meshes showed no antibacterial properties in a disk diffusion test due to a lack of hydrogen peroxide production and release. The developed polycaprolactone-honey nanofibrous meshes have potential for use in skin applications. Published version The authors wish to acknowledge the funding provided by the Republic of Turkey’s Ministry of National Education, the United Kingdom’s Engineering and Physical Sciences Research Council (EPSRC) Doctoral Prize Fellowship (EP/R513131/1), and the EPSRC and Medical Research Council (MRC) Centre for Doctoral Training in Regenerative Medicine (EP/L014904/1).

Purpose This study aims to examine on-site particle concentration levels due to emissions from a wide spectrum of additive manufacturing techniques, including polymer-based material extrusion, metal and polymer-based powder bed fusion, directed energy deposition and ink-based material jetting. Design/methodology/approach Particle concentrations in the operating environments of users were measured using a combination of particle sizers including the TSI 3910 Nano SMPS (10–420 nm) and the TSI 3330 optical particle sizer (0.3–10 µm). Also, fumes from a MEX printer during printing were directly captured using laser imaging method. Findings The number and mass concentration of submicron particles emitted from a desktop open-type MEX printer for acrylonitrile-butadiene-styrene and polyvinyl alcohol approached and significantly exceeded the nanoparticle reference limits, respectively. Through laser imaging, fumes were observed to originate from the printer nozzle and from newly deposited layers of the desktop MEX printer. On the other hand, caution should be taken in the pre-processing of metal and polymer powder. Specifically, one to ten micrometers of particles were observed during the sieving, loading and cleaning of powder, with transient mass concentrations ranging between 150 and 9,000 µg/m3 that significantly exceeded the threshold level suggested for indoor air quality. Originality/value Preliminary investigation into possible exposures to particle emissions from different 3D printing processes was done, which is useful for the sustainable development of the 3D printing industry. In addition, automatic processes that enable “closed powder cycle” or “powder free handling” should be adopted to prevent users from unnecessary particle exposure.

Carbapenemase-producing Enterobacteriaceae (CPE) are a group of drug-resistant Gram-negative pathogens that are classified as a critical threat by the World Health Organization (WHO). Conventional methods of detecting antibiotic-resistant pathogens do not assess the resistance mechanism and are often time-consuming and laborious. We have developed a magnetic digital microfluidic (MDM) platform, known as MDM Carba, for the identification of CPE by measuring their ability to hydrolyze carbapenem antibiotics. MDM Carba offers the ability to rapidly test CPE and reduce the amount of reagents used compared with conventional phenotypic testing. On the MDM Carba platform, tests are performed in droplets that function as reaction chambers, and fluidic operations are accomplished by manipulating these droplets with magnetic force. The simple droplet-based magnetic fluidic operation allows easy system automation and simplified hands-on operation. Because of the unique “power-free” operation of MDM technology, the MDM Carba platform can also be operated manually, showing great potential for point-of-care testing in resource-limited settings. We tested 27 bacterial isolates on the MDM Carba platform, and the results showed sensitivity and specificity that were comparable to those of the widely used Carba NP test. MDM Carba may shorten the overall turnaround time for CPE identification, thereby enabling more timely clinical decisions for better clinical outcomes. MDM Carba is a technological platform that can be further developed to improve diagnostics for other types of antibiotic resistance with minor modifications. Ministry of Education (MOE) Nanyang Technological University Published version The authors would like to thank Scott Cunningham and Robin Patel from the Mayo Clinic, Rochester, MN, for sharing the reference isolates used in this study and Lew Wen Siang and Gerard Joseph Lim at Nanyang Technological University, Singapore, for helping with vibrating-sample magnetometer measurements. Yi Zhang and Shawn Vasoo are grateful for the funding support from NTUitive Gap Fund NGF-2020-08-002. Yi Zhang is thankful for funding support from the Singapore Ministry of Education Grant Tier 1 RG39/19 and the Nanyang Technological University Startup Grant.

Many studies have shown that the mechanical properties and geometric accuracy of additive manufacturing parts are dependent of many factors such as laser energy density, build orientation, and heat transfer histories. Amongst the factors, heat transfer histories are highly dependent on the geometry of a part, resulting in influencing the mechanical properties and microstructure evolution due to the repeated heating and cooling process. Heat transfer histories are associated with material thermal properties which include thermal conductivity, thermal diffusivity, specific heat capacity, and temperature gradient. The objective of this paper is to understand and observe the microstructure evolution process and microhardness based on variation in geometrical characteristic of the laser-based powder bed fusion (L-PBF). This paper presents the effect of the geometric factors on the mechanical properties and geometric accuracy during the L-PBF process, which benefit future process optimisation and modelling. In this study, samples with varying wall thickness are fabricated in TI6AL4Vand AlSi10Mg alloys by L-PBF. The samples are systematically evaluated by the optical microscope and the Vickers hardness tester. Microstructural characterisation of these samples is further evaluated via scanning electron microscopy. The results show that there is a signification relationship between material thermal properties, microstructure evolution, and mechanical properties with respect to the variation in wall thickness. These results can be used to understand the material thermal behaviour in lattice structures with a thin or small-sized feature and serve as a design guideline to indirectly control the microstructure of a L-PBF part. National Research Foundation (NRF) Accepted version This research was supported by the Singapore Centre for 3D Printing (SC3DP), the National Research Foundation, Prime Minister’s Office, Singapore, under its Medium-Sized Centre funding scheme, Natural Science Foundation of Hebei Province (Project No. F2020208018), and Funding for Introduction of Overseas Researcher of Hebei Province (Project No. C20190331).

The advent of additive manufacturing (AM) has brought about radically new ways of designing and manufacturing of end-use parts and components, by exploiting freedom of design. Due to the unique manufacturing process of AM, both design and process parameters can strongly influence the part properties, thereby enlarging the possible design space. Thus, finding the optimal combination of embodiment design and process parameters can be challenging. A structured and systematic approach is required to effectively search the enlarged design space, to truly exploit the advantages of AM. Due to lowered costs in computing and data collection in the recent years, data-driven strategies have become a viable tool in characterization of process, and researches have starting to exploit data-driven strategies in the design domain. In this paper, a state-of-the-art data-driven design strategy for fused filament fabrication (FFF) is presented. The need for data-driven strategies is explored and discussed from design and process domain, demonstrating the value of such a strategy in designing an FFF part. A comprehensive review of the literature is performed and the research gaps and opportunities are analysed and discussed. The paper concludes with a proposed data-driven framework that addresses the identified research gaps. The proposed framework encompasses knowledge management and concurrent optimization of embodiment design and process parameters to derive optimal FFF part design. Contribution of this paper is twofold: A review of the state-of-the-art is presented, and a framework to achieve optimal FFF part design is proposed. Economic Development Board (EDB) National Research Foundation (NRF) Published version This research was supported by a grant from ST Engineering Aerospace, EDB-IPP, Singapore Centre for 3D Printing (SC3DP), the National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme.

Metal additive manufacturing (AM) enables unparalleled design freedom for the development of optimized devices in a plethora of applications. The requirement for the use of nonconventional aluminum alloys such as AlSi10Mg has made the rational micro/nanostructuring of metal AM challenging. Here, the techniques are developed and the fundamental mechanisms governing the micro/nanostructuring of AlSi10Mg, the most common metal AM material, are investigated. A surface structuring technique is rationally devised to form previously unexplored two-tier nanoscale architectures that enable remarkably low adhesion, excellent resilience to condensation flooding, and enhanced liquid-vapor phase transition. Using condensation as a demonstration framework, it is shown that the two-tier nanostructures achieve 6× higher heat transfer coefficient when compared to the best filmwise condensation. The study demonstrates that AM-enabled nanostructuring is optimal for confining droplets while reducing adhesion to facilitate droplet detachment. Extensive benchmarking with past reported data shows that the demonstrated heat transfer enhancement has not been achieved previously under high supersaturation conditions using conventional aluminum, further motivating the need for AM nanostructures. Finally, it has been demonstrated that the synergistic combination of wide AM design freedom and optimal AM nanostructuring method can provide an ultracompact condenser having excellent thermal performance and power density. Ministry of Education (MOE) Nanyang Technological University Published version J.Y.H. would like to acknowledge the financial support for his research ap-pointment at the University of Illinois at Urbana-Champaign, USA under the College of Engineering (CoE) International Postdoctoral FellowshipScholarship (IPS) provided jointly by the Ministry of Education, Singa-pore and Nanyang Technological University, Singapore. K.F.R., S.S., andN.M. gratefully acknowledge funding support from the Office of Naval Re-search under Grant Nos. N00014-16-1-2625 and N00014-21-1-2089, theNational Science Foundation under Award No. 1554249, and the Air Con-ditioning and Refrigeration Center. N.M. gratefully acknowledges fundingsupport from the International Institute for Carbon Neutral Energy Re-search (WPI-I2CNER), sponsored by the Japanese Ministry of Education,Culture, Sports, Science and Technology. Scanning electron microscopywas carried out in part in the Materials Research Laboratory Central Facil-ities, University of Illinois at Urbana-Champaign.

The process-structure-property (PSP) relationship of continuous carbon fiber reinforced thermoplastics manufactured through fused filament fabrication was investigated for the first time, specifically on mode I Interlaminar Fracture toughness (ILFT). A standard double cantilever beam test is used to evaluate the mode I ILFT. The PSP relationship is established using micro-computed tomography scan and laser optical microscope. This study demonstrates that higher nozzle, bed temperatures, and lower print speed enhances the mode I ILFT. The mode I ILFT is found to be greatly affected by porosity and bond formation between the layers, which are dependent on the process parameters. National Research Foundation (NRF) This research is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme.

Magnetic digital microfluidics (MDM) manipulates fluids in the form of droplets on an open substrate, and incorporates surface energy traps (SETs) to facilitate the droplet manipulation. Conventional MDM devices are fabricated monolithically, which makes it difficult to modify the device configuration without completely overhauling the original design. In this paper, we present a modular MDM architecture that enables rapid on-demand configuration and re-configuration of MDM platforms for customized bioanalyses. Each modular component contains a SET and a Lego-like antistud that fits onto a base board with Lego-like studs. We illustrate the versatility of the modular MDM architecture in biomarker sensing, pathogen identification, antibiotic resistance determination, and biochemical quantification by demonstrating immunoassays, phenotypical assays and enzymatic assays on various modular MDM platforms configured on demand to accomplish the fluidic operations required by assorted bioanalytical assays. The modular MDM architecture promises great potential for point-of-care diagnostics by offering on-demand customization of testing platforms for various categories of diagnostic assays. It also provides a new avenue for microfluidic assay development with its high configurability which would significantly reduce the time and cost of the development cycle. A Lego-inspired, modular magnetic digital microfluidic architecture enables customizable bioanalysis. Magnetic digital microfluidics controls droplets on a surface via magnetic particles, with the liquid droplets themselves acting as mini bioreactors for analysis. Such devices often include surface energy traps to aide droplet manipulation. However, because they are fabricated as monolithic systems, they cannot be altered for different bioanalysis post-fabrication. Here, a team led by Yi Zhang from Nanyang Technological University, Singapore, reports a modular design for magnetic digital microfluidic devices, in which functional modules are configured and reconfigured via Lego-like studs. This modular design allows users to build testing platform on demand for a wide range of bioanalyses.

3D Concrete Printing (3DCP) has been gaining popularity in the past few years. Due to the nature of line-by-line printing and the slump of the material deposition in each extruded line, 3D printed structures exhibit obvious lines or marks at the layer interface, which affects surface finish quality and potentially affect bonding strength between layers. This makes it necessary to control the extrudate formation in 3DCP. However, it is difficult to directly analyse the extrudate formation process because the extrudate shape depends on many parameters. In this paper, a machine learning technique is applied to correlate the formation of the extrudate to the printing parameters using an Artificial Neural Network model. The training data for the model development was obtained from extrudates printed in 3DCP experiments. The performance of the trained model was experimentally validated and the predicted extrudate geometry resulting from the developed model showed good agreement to the actual extrudate geometry. Subsequently, the developed model was used to find proper nozzle shapes to produce designated extrudate geometries. Significant improvement on the printing quality was demonstrated using nozzle shapes generated from the model on 3D printed objects consisting a vertical wall, an inclined wall and a curved part. National Research Foundation (NRF) Accepted version

Fe-Based bulk metallic glasses (BMGs) with a composition of Fe48Cr15Mo14C15B6Y2 have recently been reported with good application performance due to their excellent mechanical and chemical properties, showing excellent corrosion resistance, remarkable forming and processing ability, ultrahigh yield strength and large elasticity. Here, we report on a new functional application for such Fe-based BMGs, which can exhibit better catalytic performance than the pristine Fe surface. The hydrogen evolution and dissociation processes of one and two H2O molecules on both BMG and pristine Fe surfaces are investigated using first-principles calculations. The energy barriers of the dissociation processes on the BMG surface are lower than those on the pristine Fe surface. Moreover, the structural configurations along the dissociation path during hydrogen evolution show that it is easier for H2O molecules to dissociate into H2 on the surface of the BMG, rendering it a more active catalyst than the pristine Fe surface. Analyses on the electronic structures show further evidence that the BMG surface has a stronger ability to facilitate charge transfer at the interface and is more inclined to accept transferred charges, thereby promoting its catalytic activity. These findings shed light on understanding the functional applications of BMGs and are anticipated to be highly meaningful for further experimental investigations. Nanyang Technological University National Research Foundation (NRF) The authors gratefully acknowledge financial support from the National Research Foundation Medium-Sized Centre, Singapore through the Marine and Offshore Programme and the Nanyang Environment and Water Research Institute (Core Fund), Nanyang Technological University, Singapore.

Polycaprolactone (PCL) is one of the most recognized polymeric materials used for bone tissue engineering scaffold fabrication. This study aims to evaluate the effects of the molecular weight (Mn) of PCL on the degradation kinematics, surface, microstructural, thermal, mechanical, and biological properties of 3D printed bone scaffolds. Surface properties were investigated considering water-in-air contact angle and nanoindentation tests, while morphological characteristics and degradation kinematics (accelerated degradation tests) were examined using scanning electron microscopy (SEM), pairing with thermal and mechanical properties monitored at each considered time point. A set of mathematical equations describing the variation of fiber diameter, porosity, mechanical properties, and weight, as a function of molecular weight and degradation time, were obtained based on the experimental results. Human adipose-derived stem cells (hADSCs) proliferation and differentiation tests were also conducted using in vitro colorimetric assay. All results indicated that molecular weight had impacts on the surface, mechanical and biological properties of PCL scaffolds, while no significant effects were observed on the degradation rate. Scaffolds with lower molecular weight presented better bio-mechanical properties. These findings provide useful information for the design of polymeric bone tissue engineering scaffolds. Published version This research was partially supported by Rosetrees & Stoneygate Trust Enterprise Fellowship (Ref: M874) from Rosetrees Trust UK and Stoneygate Trust UK, and the Engineering and Physical Sciences Research Council (EPSRC) UK through the Global Challenges Research Fund (grant number EP/R015139/1).

"Stress shielding" caused by the mismatch of modulus between the implant and natural bones, is one of the major problems faced by current commercially used biomedical materials. Beta-titanium (β-Ti) alloys are a class of materials that have received increased interest in the biomedical field due to their relatively low elastic modulus and excellent biocompatibility. Due to their lower modulus, β-Ti alloys have the potential to reduce "stress shielding." Powder bed fusion (PBF), a category of additive manufacturing, or more commonly known as 3D printing techniques, has been used to process β-Ti alloys. In this perspective article, the emerging research of PBF of β-Ti alloys is covered. The potential and limitations of using PBF for these materials in biomedical applications are also elucidated with focus on the perspectives from processes, materials, and designs. Finally, future trends and potential research topics are highlighted. Nanyang Technological University Published version The author acknowledges the support from NTU Presidential Postdoctoral Fellowship from Nanyang Technological University, Singapore.

The helical spring is one of the most used components in mechanisms but there is little research on the application of 3D printing, also called Additive Manufacturing, to springs. Therefore, the objective of this paper is to derive a model for the stiffness of 3D printed springs. The equation assumes that springs are made of orthotropic material and with a rectangular wire cross-section, that is, die springs. A second version of the equation has also been postulated that accounts for the misalignment of the deposited tracks with respect to the direction of the coils due to the coil pitch. The two models are compared to various springs printed with PLA and ULTEM 9085 and are found to accurately predict the stiffness of real, 3D printed springs. These equations allow the design and manufacturing of helical die springs for applications with few load cycles and that require chemical and radiation resistance, such as in space. The equations are also the first step in the development of models for new kinds of springs, such as linear conical springs or hollow wire die springs. National Research Foundation (NRF) This research was supported by the Singapore Centre for 3D printing (SC3DP), the National Research Foundation, Prime Minister's Office, Singapore under its Medium-Sized Centre funding scheme, and National Additive Manufacturing Innovation Cluster.

Large bone loss injuries require high-performance scaffolds with an architecture and material composition resembling native bone. However, most bone scaffold studies focus on three-dimensional (3D) structures with simple rectangular or circular geometries and uniform pores, not able to recapitulate the geometric characteristics of the native tissue. This paper addresses this limitation by proposing novel anatomically designed scaffolds (bone bricks) with nonuniform pore dimensions (pore size gradients) designed based on new lay-dawn pattern strategies. The gradient design allows one to tailor the properties of the bricks and together with the incorporation of ceramic materials allows one to obtain structures with high mechanical properties (higher than reported in the literature for the same material composition) and improved biological characteristics. Published version This project has been supported by the University of Manchester and the Engineering and Physical Sciences Research Council (EPSRC) of the United Kingdom and the Global Challenges Research Fund (GCRF), grant no, EP/R01513/1 and EPSRC Doctoral Prize Fellowship grant no. EP/R513131/1.

Grippers with shape conformance and tunable rigidity are often achieved using a combination of soft and rigid structures made of different materials. These grippers are often known as soft grippers. In this review article, various gripper designs with shape conforming ability and stiffness tunability are discussed. In particular, the discussion mainly focuses on the advantages and limitations of each gripper design in terms of the shape conformance and the ease of manufacturability. Then, various 3D printing technologies that are capable of doing multimaterial printing have been introduced. The potential of multimaterial 3D printing of soft and smart grippers has been discussed. Agency for Science, Technology and Research (A*STAR) National Research Foundation (NRF) Submitted/Accepted version This work is partly supported by the Schaeffler Hub for Advanced Research at NTU, under the ASTAR IAF-ICP Programme ICP1900093.

Microcellular injection moulding is an important injection moulding technique to create foaming plastic parts. However, there are no consistent conclusions on the impact of processing parameters on the cell morphology of microcellular injection moulded parts. This paper investigates the influence of the main processing parameters, such as melt temperature, mould temperature, injection pressure, flow rate, shot volume and gas dosage amount, on the average cell size and weight reduction of a talc-reinforced polypropylene square part (165 mm × 165 mm × 3.2 mm), using the commercial software Moldex 3D. The effect of each parameter is investigated considering a range of values and the simulation results were compared with published experimental results. The differences between numerical and experimental trends are discussed. Published version This research was partially funded by the Engineering and Physical Sciences Research Council (UK) Doctoral Prize Fellowship (EP/R513131/1).

The ability to design and fabricate lightweight structure is one of the most important aspects for building a drone system. Often, connecting wires are used on the drone system for powering and signal transmission at the expense of the drone’s weight. In this paper, we explore the design and fabrication of a safety cage for drone using design optimization and 3D printing. A comparison between fused deposition modelling (FDM) and selective laser sintering (SLS) 3D printing techniques for the fabrication of thin structures was made, and it was found that SLS is more superior in this aspect. A hybrid 3D printing process combining SLS and aerosol jet printing is proposed for the fabrication of lightweight multifunctional structure with printed circuit for a drone safety cage. The safety cage is designed in such a way that maximizes the production efficiency of SLS printing process. In addition, aerosol jet printing is used to fabricate conformal circuit onto the 3D-printed safety cage structure to replace the conventional connecting wires for weight saving purpose. Lastly, an electrical characterization is conducted to investigate the functionality of the printed conductive traces on the safety cage. Nevertheless, this work demonstrates the streamlining of various 3D printing approaches for the fabrication of multifunctional structures with conformal circuits. National Research Foundation (NRF) Submitted/Accepted version This research is supported by NAMIC Singapore and funded by the National Research Foundation Singapore under its Innovation Cluster Programme.

Duplex stainless steels come under the difficult-to-machine category, considering the loss of the sensitive balance between the constituent phases due to thermal and mechanical working effects. Selective laser melting is emerging as an additive process for achieving near-net shape manufacturing solutions with these steels. Nevertheless, post-printing machining is essential to varying degrees and the machinability responses of the laser melted duplex stainless steels need sufficient attention. This paper addresses this gap, considering the experimental evaluation of the mechanics of machining with laser melted duplex stainless steels. Specimens printed with the most promising laser melting process conditions are evaluated for machinability, comparing with the wrought counterparts and also ascertaining the differential responses between the as-built and solution annealed states. Cutting forces and thermal measurements confirm better machinability with the laser melted samples which is an interesting finding considering the possibility of laser melting, machining, and post-process heat treatment as the best possible sequence of processing duplex stainless steels to circumvent the difficulties in machining. Published version The authors wish to acknowledge the support received through the MBIE funding subcontract from the New Zealand Product Accelerator of the University of Auckland.

Owing to the rapid cooling rates and directional thermal gradients involved, fusion-based additive manufacturing (AM) processes yield complex, fine solidification structures that impart anisotropic mechanical properties in materials, such as stainless steel 316L (SS316L). In this work, we present a comprehensive study of the mechanical anisotropy of SS316L produced by laser powder bed fusion using instrumented nanoindentation. We produce and test near-single crystal samples oriented along the three principal crystallographic axes—namely ⟨100⟩, ⟨110⟩, and ⟨111⟩—using a Berkovich indenter. We find that the ⟨111⟩ and ⟨100⟩ orientations exhibit the highest and the lowest hardness, respectively. To decouple the contributions of grain orientation and solidification structure to the alloy's mechanical anisotropy, we compare our experimental results against crystal plasticity finite element (CPFE) simulations. We ascribe the hardness anisotropy in SS316L to the cell spacing along the slip direction (CSSD), which is a novel metric that we introduce to account for the role of the solidification structure on plasticity. Our work provides a universal pathway to understanding the microstructure-property relationships in cubic metallic materials that exhibit solidification structures,such as those commonly imparted by fusion-based AM. Agency for Science, Technology and Research (A*STAR) Nanyang Technological University National Research Foundation (NRF) Published version This work was supported by the NTU Presidential Postdoctoral Fellowship (Grant number: 04INS000761C160), National Research Foundation (NRF) Singapore, under the NRF Fellowship program (NRF-NRFF2018-05), and A*STAR, Singapore under the Structural Metals and Alloys Program (Grant number: A18B1b0061).

Hybrid optical elements, which combine refractive and diffractive optical components to enhance optical performance by taking advantage of the optical characteristics of the individual components, have enormous potential for next-generation optical devices. However, there have not been many reports on the simulation methodology to characterize such hybrid optical systems. Here, we present a method for simulating a hybrid optical element realized by attaching an ultra-thin, flexible diffractive optics array onto a refractive optical element. The ultra-thin diffractive optical element is fabricated by direct-laser-writing using a femtosecond pulsed laser as the light source. A systematic investigation of the proposed simulation method, which does not require extensive hardware resources or computational time, but retains resolution and accuracy, is presented. The proposed scheme is validated by comparing simulation and experimental results. The simulation and experimental results on the spot size and focal length for the diffractive Fresnel zone plate (FZP) match well, with typical errors of less than 6%. The aspect ratio of the focal spot sizes at the compound and FZP focal planes of the hybrid optical system from the simulation and experiment also match quite well, with typical errors below 7%. This simulation scheme will expedite the designs for novel hybrid optical systems with optimal optical performances for specific applications, such as microfluidics and aberration-controlled optics. Nanyang Technological University This work was financially supported by a research collaboration agreement by Panasonic Factory Solutions Asia Pacific (PFSAP) and Singapore Centre for 3D Printing (RCA15/027); National Research Foundation of the Republic of Korea (NRF-2012R1A3A1050386, 2020R1A2C2102338, 2021R1A4A1031660); Korea Forest Service (Korea Forestry Promotion Institute) through the R & D Program for Forest Science Technology (2020229C10-2022-AC01); and Basic Research Program funded by the Korea Institute of Machinery and Materials (NK224C).

The use of 3D printing to produce acoustic panels with good mechanical and acoustic properties was investigated in this paper. Various fiber layups of the fiberglass face sheet and core designs were fabricated and tested for their indentation resistance and acoustic absorption performance. It was found that the bidirectional face sheet layup exhibited the best indentation energy absorption recording 4.2 J, which is 37% more than the 45-degree layout and 66% more than the quasi-isotropic layup. The specific energy absorption of the hybrid honeycomb core is the best among the three core designs recording 404 J/kg, which is 56% higher than the corrugated triangle with horizontal beam core (359 J/kg) and 20% higher than double ellipse core (335 J/kg). Computed-Tomography (CT) scan was used to study the fracture behavior of the sandwich structures. It was found that the bidirectional layup exhibited a different failure mode as compared to the 45-degree and quasi-isotropic layup. In terms of the acoustic properties, the face sheets with various layup patterns have a low acoustic absorption coefficient with minimal differences from each other at low frequencies (500 Hz–3000 Hz) and have higher absorption coefficients with greater differences from each other at frequencies between 3000 Hz–6500 Hz. The absorption curve was significantly affected by the design of the core. The orientation of the core also comes into play if the core is asymmetrical. The hybrid honeycomb sandwich structure was the optimal structure among the three designs for balanced indentation resistance and acoustic insulation. National Research Foundation (NRF) This research is supported by the National Research Foundation, Prime Minister's Office, Singapore under its Medium-Sized Centre funding scheme.

The varying physical property in a functionally graded material can be tailored to its specific requirements while using material resources effectively. 3D concrete printing can produce robust and lightweight functionally graded material for the construction industry. In this study, an approach was developed to create an objective tailored functionally graded concrete material by examining the filament material property correlations with the printing parameters. It was found that the physical property of the printed material is closely correlated to the flow rate and travel speed of the printer. Results obtained from the experiment show that the optimised structure achieved an approximately 50% improvement in the strength-to-weight ratio. This preliminary examination of the 2D optimised concrete structure opens the realm of possibility for future work in 3D optimised functionally graded concrete. National Research Foundation (NRF) Published version This research is supported by the National Research Foundation, Prime Minister’s Office, Singapore, under its Medium-Sized Centre funding scheme, Singapore Centre for 3D Printing, Berkeley Education Alliance for Research in Singapore (BEARS) for the Singapore-Berkeley Building Efficiency and Sustainability in the Tropics (SinBerBEST) Programme.

Energy consumed in building and construction accounts for 40% of the total end-use energy. To achieve the energy reduction in this area, conventional construction approaches need to be reshaped. To overcome existing challenges, this study explores the use of 3D cementitious material printing (3DCMP) and investigates the printability of these cementitious materials incorporated with the phase change material (PCM). To realize the newly developed composite cementitious materials for real-world applications, we examinate the benefits of utilizing them for building's energy consumption reduction. From our study, we demonstrate, for the first time, the successful fabrication of the PCM composite wall by 3DCMP method. The enthalpy porosity method is then proposed to study the time-dependent thermal performance of the composite wall by modelling the encapsulated PCM and cementitious material as porous and medium, respectively. Our results show the proposed model is reliable in predicting the PCM composite wall thermal performance and demonstrate the composite wall has the potential of smoothing and reducing energy consumption by the building. From our investigation, it is determined that the PCM melting temperature should be chosen based on heating time and heat power density. Additionally, the total cost of precasting a wall by conventional methods with a dimension of 4 m × 0.12 m × 2.8 m (L × W × H) is 28.4% higher than the printing counterpart. Furthermore, the performance enhancements resulted in approximately 30% savings in building energy consumption during the day using plain walls infused with 3% PCM. This study not only demonstrates the potential of fabricating enhanced building materials through the utilization of additive manufacturing technique, but it also provides the guidelines to design PCM composite walls under various operating conditions. National Research Foundation (NRF) This research is supported by the National Research Foundation, Singapore, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme, Doctoral Research Startup Project of Suzhou University (No. 2021BSK023), Key Natural Science Project of Anhui Provincial Education Department (No. KJ2021A1111). Chip Eng Seng-Sembcorp Design & Construction Pte Ltd, Sembcorp Architects & Engineers Pte Ltd.

Purpose Springs are an integral part of mechanisms and can benefit from additive manufacturing’s (AM) increased design freedom. Given the limited literature on the subject, the purpose of this paper is to develop guidelines for fabricating helical springs using three-dimensional (3D) printing. Design/methodology/approach Polylactic acid (PLA) is the main material investigated, with ULTEM™ 9085 used as a comparison. The experimental procedure is to vary the spring parameters, print the springs and test them in tension or compression using constant velocity. Plots of the force and displacement are used to measure the linear and post-deformation spring constants. Loading of the springs is done both to breakage and cyclically. Cyclic loading is also used to observe the plastic behaviour of the springs. Parameters that are varied include wire and coil diameters, pitch, wire cross-section, in-fill and layer height. Findings A square wire cross-section is used, instead of a circle because it produces more consistent coils. In-fills make no significant difference in the elastic stiffness of the springs but the mono in-fill breaks at a greater extension, so it is recommended. Tension and compression springs are confirmed to behave the same when in the elastic regime. ULTEM™ 9085 produces consistently weaker springs compared to PLA. Variation of layer height shows that thinner layers increase the stiffness of the springs. Originality/value This study investigates the behaviour of 3D printed helical springs in tension and compression. Three guidelines are created: square wire cross-section, mono-directional in-fill and thin layers are recommended.

Rapid development of additive manufacturing (AM) technologies leads to an increasing demand for quality control of printed parts. While in-process monitoring systems and post-testing technologies have been developed to inspect the part quality, there is not yet a well-established method that specifies the procedures and requirements to convert the extracted in-process layer-wise information into a single 3D file for quality evaluation and control. In this study, an off-axial imaging system utilizing optical and thermal cameras is deployed to acquire in-process optical and thermal images of the Powder Bed Fusion (PBF) process. Image registration and analyses are then performed on the acquired images to extract the in-process layer-wise data (e.g., coordinates, gray value, and temperature) associated with the printing process. Based on a comparison of file formats commonly used in industrial software, we select the Extensible Markup Language (XML) file format, which is specified by post-processing software, and further propose procedures for constructing a single 3D file from the in-process data to represent the printing process and evaluate the printing quality. This work provides guidelines for conversion of in-process data into 3D files and contributes to in-process monitoring and quality control of AM manufactured parts. Submitted/Accepted version

With the capability to build components with freeform geometries, laser powder bed fusion (L-PBF) is considered as one of the most promising techniques for industrial applications. Compared to conventional manufacturing technologies, an additional advantage of L-PBF process is the capability to fabricate parts with multiple materials, such as in-situ alloying and functionally graded alloys. In this regard, here we present a computational model to simulate the L-PBF of multiple materials. Based on volume of fluid (VOF) methods and computational fluid dynamics (CFD), the multi-physics multi-material model was successfully implemented with various physics of L-PBF process, including surface tension, Marangoni shear force, recoil pressure, compositional diffusion, etc. In addition, we demonstrated the numerical algorithm of ray tracing heat source for multiple materials. With reasonable assumptions, conduction mode or keyhole mode laser melting of miscible materials can be simulated via the proposed computational framework. Furthermore, such multi-physics model is capable of simulating L-PBF of an arbitrary number of materials. The computational model can help achieve insightful understanding of the L-PBF of multiple materials. National Research Foundation (NRF) The authors acknowledge the support by the National Research Foundation, Prime Minister’s Office, Singapore under its Medium Sized center funding scheme.

Additive manufacturing (AM), or commonly known as 3D printing, gained prominence as part of a suite of technologies that is expected to bring about the Fourth Industrial Revolution, or Industry 4.0. This technology primer aims to showcase the capabilities across the Schools and Research Centres under CoE. While introducing AM, the primer also elucidates the market growth of AM, the exciting new directions undertaken in research development for AM and the current challenges that AM is facing. Applications of AM can be multidisciplinary and span across many fields of study. The research projects featured in this primer are categorised into seven research areas: (1) Aerospace & Defence (2) Biomedical & Food Printing (3) Building & Construction (4) Marine & Offshore (5) AI in Part Design & Manufacturing (6) Novel Materials & 3D Microstructure Engineering (7) Beyond 3D Printing. It is certain that AM will have an important part to play in our journey towards Industry 4.0. There is more to explore with this emerging technology as new players enter the field, bringing new AM methods, materials, and challenges for vastly different applications. Through this primer, we hope to provide a deeper understanding of AM and encourage partnerships between academia and industry to fully unleash the exciting potential of AM and transform the industry through digitalisation of manufacturing.

In order to address the high throughput data generation challenges in the directed energy deposition (DED) process development, a design of experiments (DOE) informed deep learning (DL) model is developed for modeling of laser powder-based DED process. A small-size experimental dataset is obtained according to DOE, by which a large-size dataset is augmented via the DOE regression model and then used to pre-train the DL model. A subset of experimental data is employed to fine-tune the DL model. The presently developed DOE-informed DL model is validated via single-track deposition of stainless steel 316L, in which the cross-section dilution shape (including depth) and the geometrical characteristics of beads, including the width, height, area, and wetting angle are predicted accurately. The prediction of the porosity and hardness are acceptable for single-track deposition, since variations of both the experimental porosity (from 0.04 % to 0.30 %) and hardness (from 168 HV to 182 HV) are quite small for the single-track deposition, especially predicted ranges for the porosity (from 0.05 % to 0.25 %) and hardness (from 170 HV to 180 HV) are the subset of the experimental results. The DOE-informed DL model developed in this study is based on a single-track deposition dataset; in future work, the DOE-informed DL model will be extended to multi-layer deposition. Economic Development Board (EDB) National Research Foundation (NRF) Published version This research is supported by Makino Asia Pte Ltd through the Economic Development Board Industrial Postgraduate Programme and the National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme.

Ankle braces typically restrict the functional range of motion. Braces should preferably allow a free functional range of motion during sport while protecting the foot at high-risk positions beyond that range. This could be achieved with 3D printed metamaterial structures that could have varying properties throughout an individual’s ankle range of motion. This paper aims to illustrate an exploratory methodology of using an affordable Fused Deposition Modelling 3D printing technology to develop an ankle brace using metamaterial structures. It also showcases the design, manufacturing processes and testing of 3D printed customised ankle brace prototype designs that incorporated metamaterial structures. Initial tests showed that as designed, the prototype braces maintained the full range of motion for plantar flexion angles. Results also showed that the prototypes required one of the lowest moments during functional range of motion while achieving almost twice to thrice the moment required beyond the functional range of motion. This work was supported by Institute for Sports Research, Innovation Development Grant [grant number S11-1191-IDS].

Metal additive manufacturing (MAM) is an effective way to fabricate conformal cooling channels (CCCs), which follow the curves of the plastic product in the mold body of the plastic injection. CCCs have free-curved pathways thanks to the design & manufacturing flexibilities of the MAM process so that they can achieve better cooling performance with shorter cooling time and smaller temperature non-uniformity. On the other hand, the flexibilities of the MAM process bring multiple options for design variables and the high number of design variables make the final design of CCCs complex, high-cost, and time-consuming. Considering this challenge, this study presents the entire process of MAM of CCCs for a target product with eight different design variables, which makes it a product with a high number of design variables, from the initial design to the on-site manufacturing including the steps of computer-aided design & simulations, metamodel, multiobjective optimization, and the printing quality monitoring. The target product has three main objectives that are i) the temperature difference between the maximum and minimum values at the internal wall of the mold, ii) maximum temperature in the mold body, and iii) pressure drop. The optimized product is then printed via direct metal laser sintering (DMLS) machine and the quality check is done via X-ray computed tomography. Ministry of Education (MOE) This study is funded by the Ministry of Education Tier 1 RG154/19.