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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].

Hydrogels have a wide range of applications in tissue engineering, drug delivery, device fabrication for biological studies and stretchable electronics. For biomedical applications, natural polymeric hydrogels have general advantages such as biodegradability and non-toxic by products as well as biocompatibility. However, applications of nature derived hydrogels have been severely limited by their poor mechanical properties. For example, most of the protein derived hydrogels do not exhibit high stretchability like methacrylated gelatin hydrogel has ∼11% failure strain when stretched. Moreover, protein derived elastomeric hydrogels that are fabricated from low molecular weight synthetic peptides require a laborious process of synthesis and purification. Biopolymers like gelatin, produced in bulk for pharma and the food industry can provide an alternative for the development of elastomeric hydrogels. Here, we report the synthesis of ureidopyrimidinone (Upy) functionalized gelatin and its fabrication into soft elastomeric hydrogels through supramolecular interactions that could exhibit high failure strain (318.73 ± 44.35%). The hydrogels were fabricated through a novel method involving co-solvent optimization and structural transformation with 70% water content. It is anticipated that the hydrogel fabrication method involves the formation of hydrophobic cores of ureidopyrimidinone groups inside the hydrogel which introduced elastomeric properties to the resulting hydrogel. Agency for Science, Technology and Research (A*STAR) Ministry of Education (MOE) Nanyang Technological University Published version The authors acknowledge the financial support provided by Ministry of Education, Singapore, Singapore Centre for 3D Printing (SC3DP), A*STAR (Singapore Food Story R&D Programme), and School of Material Sciences and Engineering, Nanyang Technological University, Singapore.

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.

Hierarchically porous-structured materials show tremendous potential for catalytic applications. In this work, a facile method through the combination of three-dimensional (3D) printing and chemical dealloying was employed to synthesize a nanoporous-copper-encapsulating microporous-diamond-cellular-structure (NPC@DCS) catalyst. The developed NPC@DCS catalyst was utilized as a heterogeneous photo-Fenton-like catalyst where its catalytic applications in the remediation of organic wastewater were exemplified. The experimental results demonstrated that the NPC@DCS catalyst possessed a remarkable degradation efficiency in the removal of rhodamine B with a reaction rate of 8.24 × 10-2 min-1 and displayed attractive stability, durability, mineralization capability, and versatility. This work not only manifests the applicability of the proposed NPC@DCS catalyst for wastewater purification in practical applications but also is anticipated to inspire the incorporation of the 3D printing technology and chemical synthesis to design high-performance metal catalysts with tunable hierarchical micro- and nanopores for functional applications. National Research Foundation (NRF) The authors acknowledge the financial support from the National Natural Science Foundation of China (nos. 51775207 and 51905192), Fundamental Research Funds for the Central Universities (no. 2020kfyXJJS088), and National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme through the Marine and Offshore Program.

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.

Natural materials such as bone and enamel have intricate microstructures with inorganic minerals oriented to perform multiple mechanical and biological functions. Current additive manufacturing methods for biominerals from the calcium phosphate (CaP) family enable fabrication of custom-shaped bioactive scaffolds with controlled pore structures for patient-specific bone repair. Yet, these scaffolds do not feature intricate microstructures similar to those found in natural materials. In this work, we used direct material extrusion to 3D print water-based inks containing CaP microplatelets, and obtained microstructured scaffolds with various designs. To be shear-thinning and printable, the ink incorporated a concentration of 21 – 24 vol% CaP microplatelets of high aspect ratio. Good shape retention, print fidelity and overhanging layers were achieved by simultaneous printing and drying. Combined with the 3D design, versatile CaP microstructured objects can be built, from porous scaffolds to bulk parts. Extruded filaments featured a core-shell microstructure with graded microplatelet orientations, which was not affected by the printing parameters and the print design. A simple model is proposed to predict the core-shell microstructure according to the ink rheology. Given the remaining open porosity after calcination, microstructured scaffolds could be infiltrated with an organic phase in future to yield CaP biocomposites for hard tissue engineering. National Research Foundation (NRF) Published version This work was supported by the National Research Foundation, Singapore, with the Fellowship NRFF12- 2020-0006.

Conformal cooling is an additive manufacturing-based solution and it is a rapidly developing method for reducing the cooling time of the plastic injection process. The present study investigates the thermal and mechanical performances of the 3D-printed conformal cooling channels using computational analyses and multi-objective optimization. For a real injection mold product, two different conformal cooling channel profiles, which are circular and elongated, are analyzed individually. Their cooling time, temperature non-uniformity, and pressure drop are assessed. Compared to the traditional channels, the cooling time of designed CCCs is reduced in the range of 30-60%. The cooling and fatigue life performances of the elongated channel are analyzed for different channel pathways and cross section areas. As for the circular channel, the coolant temperature, volume flow rate, and channel diameter are selected as the parameters within the ranges of 288.0-298.0 K, 1.0-10.0 L/min, and 2.1-2.5 mm, respectively. According to these parameters, the multi-objective optimization study is performed and the best trade-off point is found at the channel diameter of 2.5 mm, coolant temperature of 297 K, and the flow rate of 1 L/min when all the objectives have equal weights in the optimization problem. Accepted version

Precise control of light is indispensable to modern optical communication devices especially as the size of such devices approaches the subwavelength scale. Plasmonic devices are suitable for the development of these optical devices due to the extreme field confinement and its ability to be controlled by tuning the carrier density at the metal/dielectric interface. Here, an electro-ionic controlled plasmonic device consisting of Au/graphene/ion-gel is demonstrated as an optical switch, where an external electric field modulates the real part of the electrical conductivity. The graphene layer enhances charge penetration and charge separation at the Au/graphene interface resulting in an increased photoinduced voltage. The ion-gel immobilized on the Au/graphene further enables the electrical tunability of plasmons which modulates the intensity of the reflected laser light. This work paves the way for developing novel plasmonic electro-optic switches for potential applications such as integrated optical devices. Ministry of Education (MOE) National Research Foundation (NRF) J.Y.P. acknowledges NTU for the Research Student Scholarship and SC3DP which is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme. This work was supported in part by the Ministry of Education (MOE), Singapore - Academic Research Funding (AcRF) Tier 1 Grant RG192/17. R.M. and R.S.R. acknowledge Grants MOE2017- T2-2-129 and MOE2019-T2-1-058. M.B. acknowledges NTU for the NAP-SUG grant.

4D printing provides a means to create dynamic structures for self-actuating devices fabricated by additive manufacturing techniques. Most existing 4D printing processes are only capable of one-way shape morphing using a single mechanism for stimulation. In the limited successful reversible 4D-printing studies, most only demonstrate 2D-to-3D shape morphing. This study introduces a contactless shape setting mechanism to empower reversible 4D printing using a combination of stimuli. The forward shape programming is realised by asymmetric swelling with heated ethanol, and the shape recovery is accomplished by dry heating. The shape morphing can be predicted using a simulation model. Several designs are 4D-printed to achieve different forms of morphing to obtain 3D-to-3D shape morphing. The entire shape morphing cycle could be completed within as short as 3 min. The capability of 3D-to-3D shape morphing and reversibility of our 4D-printing process promise great potential for different applications such as biomimetics and soft robotics. National Research Foundation (NRF) Accepted version This research is supported by the Singapore Centre for 3D Printing, which is funded by the Singapore National Research Foundation.

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.

Additive manufacturing (AM) or 3D printing is growing rapidly in the manufacturing industry and has gained a lot of attention from various fields owing to its ability to fabricate parts with complex features. The reliability of the 3D printed parts has been the focus of the researchers to realize AM as an end-part production tool. Machine learning (ML) has been applied in various aspects of AM to improve the whole design and manufacturing workflow especially in the era of industry 4.0. In this review article, various types of ML techniques are first introduced. It is then followed by the discussion on their use in various aspects of AM such as design for 3D printing, material tuning, process optimization, in situ monitoring, cloud service, and cybersecurity. Potential applications in the biomedical, tissue engineering and building and construction will be highlighted. The challenges faced by ML in AM such as computational cost, standards for qualification and data acquisition techniques will also be discussed. In the authors’ perspective, in situ monitoring of AM processes will significantly benefit from the object detection ability of ML. As a large data set is crucial for ML, data sharing of AM would enable faster adoption of ML in AM. Standards for the shared data are needed to facilitate easy sharing of data. The use of ML in AM will become more mature and widely adopted as better data acquisition techniques and more powerful computer chips for ML are developed. National Research Foundation (NRF) Accepted version This research is supported by the National Research Foundation, Prime Minister’s Ofce, Singapore under its Medium-Sized Centre funding scheme.

While significant progress has been made in laser powder bed fusion (L-PBF) for metal additive manufacturing (AM), there is still limited large scale adoption of this advanced manufacturing technique by the industry. This paper covers the recent developments in L-PBF with discussions from the materials and process perspectives. High entropy alloys and high strength aluminium alloys have been identified as key materials development for L-PBF. Then, scanning strategies and multi-lasers applications for the process are also discussed. Other research trends and topics such as powder recycling, shape memory alloys and magnetic alloys are illustrated. The final part of this paper provides an outlook on the recent advancements while suggesting potential research topics for L-PBF. National Research Foundation (NRF) Accepted version The authors acknowledge the support from the National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme.

PurposeSoft robotics is currently a rapidly growing new field of robotics whereby the robots are fundamentally soft and elastically deformable. Fabrication of soft robots is currently challenging and highly time- and labor-intensive. Recent advancements in three-dimensional (3D) printing of soft materials and multi-materials have become the key to enable direct manufacturing of soft robots with sophisticated designs and functions. Hence, this paper aims to review the current 3D printing processes and materials for soft robotics applications, as well as the potentials of 3D printing technologies on 3D printed soft robotics.Design/methodology/approachThe paper reviews the polymer 3D printing techniques and materials that have been used for the development of soft robotics. Current challenges to adopting 3D printing for soft robotics are also discussed. Next, the potentials of 3D printing technologies and the future outlooks of 3D printed soft robotics are presented.FindingsThis paper reviews five different 3D printing techniques and commonly used materials. The advantages and disadvantages of each technique for the soft robotic application are evaluated. The typical designs and geometries used by each technique are also summarized. There is an increasing trend of printing shape memory polymers, as well as multiple materials simultaneously using direct ink writing and material jetting techniques to produce robotics with varying stiffness values that range from intrinsically soft and highly compliant to rigid polymers. Although the recent work is done is still limited to experimentation and prototyping of 3D printed soft robotics, additive manufacturing could ultimately be used for the end-use and production of soft robotics.Originality/valueThe paper provides the current trend of how 3D printing techniques and materials are used particularly in the soft robotics application. The potentials of 3D printing technology on the soft robotic applications and the future outlooks of 3D printed soft robotics are also presented.

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.

Organically modified montmorillonite/polypropylene (OMMT/PP) composite powders for selective laser sintering (SLS) were developed using four powder preparation methods including melt extrusion combined with cryogenic grinding, thermally induced phase separation (TIPS), surface coating, and mechanical mixing. Evaluations were conducted on the shape and size, powder-bed surface roughness, and thermal behavior of the developed composite powders as well as the mechanical properties of their injection-moulded tensile specimens. Melt extrusion proved to be the most favorable as the powders exhibited the highest thermo-oxidative stability (Td,max = 378 °C) and enhanced mechanical strength and ductility. TIPS could produce powders with reduced crystallization temperatures and increased melt enthalpies that were beneficial for SLS, and with powder morphology ideal for SLS without post-processing. It was found that at low loadings, nanofillers with sheet-like structures such as OMMT could limit the increase in crystallization temperatures of the composite powder, thus ensuring their wide sintering windows for SLS. Economic Development Board (EDB) Accepted version The work was supported by the Economic Development Board (EDB), Singapore and Robert Bosch (SEA) Pte Ltd. through the Industrial Postgraduate Program with School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore.

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 critical challenges of using electromembrane processes [e.g., electrodialysis and flow-electrode capacitive deionization (FCDI)] to recycle resources (e.g., water, salts, and organic compounds) from wastewater are the fractionation of dissolved ionic matter, the removal/recovery of organic components during desalination, and membrane antifouling. This study realized the simultaneous fractionation, desalination, and dye removal/recovery (FDR) treatment of dye/salt mixtures through a simple but effective approach, that is, using a carbon cloth-modified FCDI (CC-FCDI) unit, in which the carbon cloth layer was attached to the surface of each ion-exchange membrane (IEM). The IEMs and carbon-based flow-electrodes were responsible for the fractionation and desalination of dye and salt ions, while the carbon cloth layers contributed to the active membrane antifouling and dye removal/recovery by the electrosorption mechanism. Attributed to such features, the CC-FCDI unit accomplished the effective FDR treatment of dye/salt mixtures with wide ranges of salt and dye concentrations (5-20 g L-1 NaCl and 200-800 ppm methylene blue) and different dye components (cationic and anionic dyes) under various applied voltages (1.2-3.2 V). Moreover, the active membrane antifouling by virtue of the carbon cloth facilitated the excellent and sustainable FDR performance of CC-FCDI. The removal/recovery of dyes from the carbon cloth strongly depends on the characteristics of dye molecules, the surface properties of the carbon cloth, and the local pH at the IEM/CC interfaces. This study sheds light on the strategies of using multifunctional layer-modified FCDI units to reclaim resources from various high-salinity organic wastewater. Nanyang Technological University The authors would like to thank the financial support from the Nanyang Environment and Water Research Institute (Core Funding), Nanyang Technological University, Singapore.

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).