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The report details the results of a unique experimental demonstration of applying university resources to local government problems. Faculty-student teams worked with city and county personnel on projects chosen by mutual agreement, including work in areas of traffic management, law enforcement, waste heat utilization, solid waste conversion, and rural planning and zoning. (Author)

The nanometer-scale (nano-scale) microstructural evolution in an additively manufactured Re-free Ni-based superalloy, with single crystal compositions, is investigated through field emission scanning electron microscopy, transmission electron microscopy, and atom probe tomography. We find that nano-scale primary γ′ precipitation occurs in the fine as-built microstructure, leading to an exceptional microhardness of 480.0 ± 6.7 HV at room temperature. Presence of ultra-fine γ′ precipitates, ~ 20 nm in size, is observed in the bottom few layers of the as-built samples, which is hitherto undocumented and contrary to the widespread consensus regarding hierarchical γ′ phase evolution in additively manufactured Ni-based superalloys. Moreover, considerable precipitation of tantalum-rich C14 Laves phase at the grain boundaries and interdendritic regions in the as-built samples emphasizes the need for additive manufacturing specific alloy design. National Research Foundation (NRF) Accepted version

International audience; Interstitial flow in tumors is a key mechanism leading to cancer metastasis. Tumor growth is accompanied by the development of a leaky vasculature, which increases intratumoral pressure and generates an outward interstitial flow. This flow promotes tumor cell migration away from the tumor. The nature of such interstitial flow depends on the coupling between hydrodynamic conditions and material properties of the tumor, such as porosity and deformability. Here we investigate this coupling by means of a microfluidic model of interstitial flow through a tumor, which is represented by a tumor cell aggregate. For a weak intratumoral pressure, the model tumor behaves as a viscoelastic material of low permeability, which we estimate by means of a newly developed microfluidic device. As intratumoral pressure is raised, the model tumor deforms and its permeability increases. For a high enough pressure, localized intratumoral fracture occurs, which creates preferential flow paths and causes tumor cell detachment. The energy required to fracture depends on the rate of variation of intratumoral pressure, as explained here by a theoretical model originally derived to describe polymer adhesion. Besides the well-established picture of individual tumor cells migrating away under interstitial flow, our findings suggest that intratumoral pressures observed in tumors can suffice to detach tumor fragments, which may thus be an important mechanism to release cancer cells and initiate metastasis.

Purpose This study aims to investigate the effect of mechanical peening on the cooling rate of a subsequently deposited layer in a hybrid additive manufacturing (AM) process. Design/methodology/approach In this experimental study, 20 layers of 316 L stainless steel are built via directed energy deposition, with the tenth layer being subject to various peening processes (shot peening, hammer peening and laser shock peening). The microstructure of the eleventh layer of all the samples is then characterized to estimate the cooling rate. Findings The measurements indicate that the application of interlayer peening causes a reduction in primary cellular arm spacing and an increase in micro segregation as compared to a sample prepared without interlayer peening. Both factors indicate an increase in the cooling rate brought about by the interlayer peening. Practical implications This work provides insight into process design for hybrid AM processes as cooling rates are known to influence mechanical properties in laser-based AM. Originality/value To the best of the authors’ knowledge, this work is the first of its kind to evaluate the effects of interlayer peening on a subsequently deposited layer in a hybrid AM process.

Due to its limited intelligence and abilities, machine learning is currently unable to handle various situations thus cannot completely replace humans in real-world applications. Because humans exhibit robustness and adaptability in complex scenarios, it is crucial to introduce humans into the training loop of artificial intelligence (AI), leveraging human intelligence to further advance machine learning algorithms. In this study, a real-time human-guidance-based (Hug)-deep reinforcement learning (DRL) method is developed for policy training in an end-to-end autonomous driving case. With our newly designed mechanism for control transfer between humans and automation, humans are able to intervene and correct the agent's unreasonable actions in real time when necessary during the model training process. Based on this human-in-the-loop guidance mechanism, an improved actor-critic architecture with modified policy and value networks is developed. The fast convergence of the proposed Hug-DRL allows real-time human guidance actions to be fused into the agent's training loop, further improving the efficiency and performance of DRL. The developed method is validated by human-in-the-loop experiments with 40 subjects and compared with other state-of-the-art learning approaches. The results suggest that the proposed method can effectively enhance the training efficiency and performance of the DRL algorithm under human guidance without imposing specific requirements on participants’ expertise or experience. Agency for Science, Technology and Research (A*STAR) Nanyang Technological University Published version This work was supported in part by the SUG-NAP Grant of Nanyang Technological University and the A*STAR Grant (W1925d0046), Singapore.

Membrane technology is a key enabler for a circular pharmaceutical industry, but chemically resistant polymeric membranes for organic solvent nanofiltration (OSN) often suffer from lower-than-required performances. Recently, graphene-based laminated membranes using small-flake graphene oxide (SFGO) nanosheets open up new avenues for high-performance OSN, but their permeance toward high viscosity solvents is below expectation. To address this issue, we design hyperlooping channels using multiwalled carbon nanotubes (MWCNTs) intercalated within lanthanum(III) (La3+)-cross-linked SFGO nanochannels to form a ternary nanoarchitecture for low-resistant transport toward high viscosity solvents. At optimized MWCNT loading, the defect-free membrane exhibits 138 L m-2 h-1 bar-1 ethanol permeance at >99% rejections toward organic dyes, outperforming state-of-the-art graphene oxide (GO)-based membranes to date. Even butanol─with twice the viscosity of ethanol─exhibits a permeance no less than 60 L m-2 h-1 bar-1 at comparable rejection rates. Theoretical simulation suggests that La3+ cross-linking is critical and can create an intact architecture that brings size exclusion into play as the dominant separation mechanism. Also, MWCNT nanochannel offers at least 1.5-fold lower ethanol transport resistance than that of the GO nanochannel, owing to greater bulk freedom in orientating ethanol molecules. Overall, the hyperlooping architecture demonstrates ∼3-fold higher permeance than neat SFGO membrane for elevating OSN performances. Economic Development Board (EDB) Nanyang Technological University This work was supported by GSK-EDB Trust Fund (T.-H.B. and J.-M.L.) and the National Research Foundation of Korea (NRF) grant funded by the Korea government MSIT (T.-H.B.; Reference number: NRF-2021R1A2C3008570). K.Z. and Y.W. would like to acknowledge financial support from the Nanyang Environment and Water Research Institute (Core Fund), Nanyang Technological University, Singapore. K.G. would also like to acknowledge funding support from the Economic Development Board (EDB) of Singapore to the Singapore Membrane Technology Centre.

Blood tests are considered as standard clinical procedures to screen for markers of diseases and health conditions. However, the complex cellular background (>99.9% RBCs) and biomolecular composition often pose significant technical challenges for accurate blood analysis. An emerging approach for point-of-care blood diagnostics is utilizing "label-free" microfluidic technologies that rely on intrinsic cell properties for blood fractionation and disease detection without any antibody binding. A growing body of clinical evidence has also reported that cellular dysfunction and their biophysical phenotypes are complementary to standard hematoanalyzer analysis (complete blood count) and can provide a more comprehensive health profiling. In this review, we will summarize recent advances in microfluidic label-free separation of different blood cell components including circulating tumor cells, leukocytes, platelets and nanoscale extracellular vesicles. Label-free single cell analysis of intrinsic cell morphology, spectrochemical properties, dielectric parameters and biophysical characteristics as novel blood-based biomarkers will also be presented. Next, we will highlight research efforts that combine label-free microfluidics with machine learning approaches to enhance detection sensitivity and specificity in clinical studies, as well as innovative microfluidic solutions which are capable of fully integrated and label-free blood cell sorting and analysis. Lastly, we will envisage the current challenges and future outlook of label-free microfluidics platforms for high throughput multi-dimensional blood cell analysis to identify non-traditional circulating biomarkers for clinical diagnostics. Ministry of Education (MOE) Published version The authors would like to acknowledge support from Singapore Ministry of Education Academic Research Fund (MOE AcRF) Tier 2 (MOE-T2EP30120-0004) and under the RIE2020 Industry Alignment Fund – Industry Collaboration Projects (IAF-ICP) Funding Initiative, as well as cash and in kind contributions from the industry partner, HP Inc., through the HP-NTU Digital Manufacturing Corporate Lab.

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.

Prevention of mechanical and thermal damage to the composite parts is crucial during the debonding process of adhesive joints. This work highlights the impact of thermally expanded particles (TEPs) on bulk adhesive properties and the lap shear strength of adhesively bonded GFRP joints. FTIR studies revealed insignificant chemical changes occurring among the epoxy and its blend with TEPs. The addition of TEPs has slightly influenced the glass transition temperature (Tg) of adhesive. TMA showed that TEPs lose permanent expansion above maximum expansion temperature due to burst and/or diffuse of gas through the thin shell. DIC analysis of materials revealed that CTE mismatch grows with the addition of TEPs in x and y directions. Increases in TEP content up to 15 wt.% also raised the maximum dimension change in the epoxy adhesive. DMA and TGA studies indicated no major change in storage modulus and weight loss when GFRP was heated up to 170°C. The contact angle of GFRP decreased substantially after plasma surface treatment. Plasma surface treatment provided higher bond strength at room temperature than sandblasting surface treatment and prevented fiber-tearing. Despite the incorporation of TEPs, the enhanced debonding effectiveness at 145°C was marginal (less than 5%) for the epoxy adhesive used in the study. The incorporation of TEPs generated the residual stresses inside the adhesive as confirmed by measuring the residual strength of SLJ samples, especially 10 wt.% TEPs-epoxy joints exhibited more than 20% strength drop. Submitted/Accepted version

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].

Drone has become more and more popular in various civil applications due to the open of the low-altitude airspace and its easy operation. Unlike the common search and track task for the target, the new search and lock (SAL) task is focused on in this paper. In the SAL task, multiple drones first try to detect the moving ground target cooperatively. Then they must lock the target by covering all the surrounding area of it at a low flight altitude, which indicates that the target can be watched clearly in all directions from then on. The SAL task can be applied in the panorama shot for the moving ground target. First, the low-altitude urban airspace is discretized into cubes, based on which the flight rules of drone are defined. The field of view (FOV) of drone is modeled considering the flight altitude and the block of buildings. For the cooperation among multiple drones, the constraints on the type of waypoint, the communication distance and the collision avoidance are all included. The goal in the search phase is to cover more area which have not been visited recently to increase the probability of detecting the target, and it is expected to lock the target as soon as possible in the lock phase. A new swarm-based imitative learning optimization (SBILO) algorithm is proposed to determine the waypoint of drone in the search phase considering the characteristic of the established SAL model. To have a quick response to the escape behavior of the target in the lock phase, the waypoint of drone is generated in a distributed way to cover more surrounding area of the target and lock it gradually. The case of losing the target in the FOV of all drones is also addressed by covering more possible places where the target may appear. Simulation results demonstrate that the SAL task can be performed efficiently by the drones with the flight routes obtained by the proposed SBILO algorithm and the distributed asynchronous decision-make (DADM) approach. Ministry of Education (MOE) Submitted/Accepted version This research work is supported by the Chongqing Research Program of Basic Research and Frontier Technology with the grant numbers of cstc2020jcyjmsxmX0602, Fundamental Research Funds for the Central Universities with the project reference number of 2020CDJ-LHZZ-066, China Scholarship Council with the project reference number of 201906055030. This collaborative research is also supported by the Ministry of Education (MOE, Singapore) Tier-1 project research grant (Project ID: 2018-T1-002-124) and the UAS Program on “Urban Aerial Transport Traffic Management and Systems” in the ATMRI, NTU, Singapore.

Damage induced by a low-velocity impact can reduce the stability and reliability of structures. In this study, a novel low-velocity impact region identification method based on the spectral peak frequency (SPF) and support vector machine (SVM) is proposed to identify the low-velocity impact regions on a steel cantilever beam. A low-velocity impact region identification system of the cantilever beam is established by applying fiber Bragg grating (FBG) sensors, and only 2 sensors are used in this system. The power spectral density functions of the impact response signal are smoothed using the linear weighting method to remove pseudospectral peak frequencies, and then, SPFs are extracted as the features. For 25 low-velocity impact regions with dimensions of 30 mm × 10 mm, the results show that the recognition rate obtained by the proposed method is 100% and the feature vector consisting of the first two SPFs with the largest amplitude has the highest recognition rate. Through the comparative study, it is found that the recognition rate of SVM is higher than that of the probabilistic neural network (PNN) and extreme learning machine (ELM) for low-velocity impact area recognition of cantilever beams. As a result, the low-velocity impact region identification method of this paper can be applied to the real-time health monitoring of cantilever beam structures. Published version This work was supported in part by the project from the Ministry of Industry and Information Technology of China under Grant CJ09N20, 2019GXB01-01-001.

The stiffnesses and microstructures of interfaces may have significant influence on the propagation of elastic waves. In this paper, we investigate the reflection and refraction of SH waves at a non-ideal interface between two elastic half-spaces. First, we use the surface elasticity theory (Gurtin and Murdoch in Arch. Ration. Mech. Anal. 57: 291–323, 1975) to describe the mechanical behaviour of the interface. We derive the reflection and transmission coefficients, as well as the phase angles of the reflected and transmitted waves. Then we treat the non-ideal interface between two elastic bodies as a thin membrane with microstructures. By employing the second-order strain-gradient model (Aifantis in Int. J. Eng. Sci. 30: 1279–1299, 1992) to describe the mechanical behaviour of the thin membrane, we establish the strain-gradient thin membrane model for the present problem. Finally, by selecting combinations of non-dimensional parameters, we demonstrate the effects of interfacial material constants on the reflection and refraction of SH waves. Jianmin Long would like to thank the support from the National Natural Science Foundation of China (11702081), the Natural Science Foundation of Jiangsu Province (BK20191295) and the Fundamental Research Funds for the Central Universities (2019B08714).

Due to the uncertainty of vehicle model parameters, modeling errors and external disturbances, the performance of path tracking control system is poor, especially under high velocity and large curvature extreme conditions. To address this issue, this paper presents a novel gain-scheduled robust control strategy based on linear parameter varying system with model predictive control (MPC) and H∞. Firstly, fully considering the influence of the time-varying characteristics of vehicle velocity and tire cornering stiffness on the path tracking system model, a novel linear parameter varying system model is built for path tracking control of autonomous vehicle. Then, a path tracking robust controller is designed based on gain-scheduled approach, and the linear matrix inequality (LMI) is applied to solve optimization problem, in which MPC and H∞ robust control theory are applied to the controller design process. Finally, the simulation experiments have verified that the proposed novel robust control strategy can improve the path tracking accuracy and ensure the vehicle lateral and roll stability, especially under high velocity and large curvature extreme conditions. Meanwhile, the proposed robust controller shows superiority to suppress the parameters uncertainty, modeling error and external disturbance. This work was supported in part by the Foundation of Key Laboratory of Vehicle Advanced Manufacturing, Measuring and Control Technology (Beijing Jiaotong University), Ministry of Education, China under Grant 014062522006 and in part by the National Key Research Development Program of China under Grant 2017YFB0103701.

The use of intelligent decision aids in Air Traffic Management is recommended to manage the exponential rise in global air traffic. Consequently, trust, which is one of the main drivers of how Air Traffic Controllers use such decision aids, has become an important area of research. It has been suggested that there is a strong emotional influence in the formation of Human-Human Trust, and it is unclear if this paradigm is valid for Human-Autonomy Trust. The extent of the cognitive and emotional components in the initial trust relationship between Air Traffic Controllers and a simulated conflict detection autonomous decision aid was examined with the use of functional Magnetic Resonance Imaging. The results confirmed that the emotional component showed higher activation than the cognitive component for the initial formation of trust between Air Traffic Controllers and autonomous decision aids. Civil Aviation Authority of Singapore (CAAS) Nanyang Technological University National Research Foundation (NRF) Submitted/Accepted version This research is supported by the National Research Foundation, Singapore, and the Civil Aviation Authority of Singapore, under the Aviation Transformation Programme, with Research Grant 04SBS000704C160. IRB approval for this study was granted by the Nanyang Technological University Institutional Review Board (IRB) (NTU IRBIRB-2018-12-002).

This communication presents an enhancement of heat transportation of tangent hyperbolic nanofluid comprised of silver / Gasoline oil and silver (Formula presented.) /Gasoline oil. The flow of fluid is caused by the stretching Riga wedge. The leading nonlinear coupled differential formulation is transmuted into ordinary differential form with the utilization of similarity transform. Numerical findings are yielded by hiring the Runge–Kutta method and shooting procedure coded in a MATLAB script. The computational run is carried out to explore the influence of notable parameters on skin friction, velocity, local heat transfer rate, and temperature of the fluid. The range of the parameters are taken arbitrarily as (Formula presented.), (Formula presented.), (Formula presented.), (Formula presented.) and (Formula presented.), etc. It is noticed that flow accelerates with modified Hartman number and Weissenberg number. The temperature is incremented directly with heat source strength and Biot number. The velocity of mono nanofluid (Ag/Gasoline) is slow as than that of hybrid nanofluid but the temperature behaves reciprocally.

Meshes obtained by 3D scanning or photogrammetry are usually very dense and multi-chart textured. Effectively reducing the amount of data while preserving both geometry and appearance is an important and also challenging problem. This paper presents a new method for seamless simplification of dense triangular meshes with multi-chart textures. The method is composed of three components: geometry simplification, correspondence map construction and texture image generation. The core of the method lies in the ideas of decoupling geometry, UV-parameterization and texture processes to make the simplification process less constrained by the underlying attribute encoding, a reliable updating procedure for constructing the correspondence map between the simplified and original meshes, and a least squares model for filling texture elements, which are the key to producing artifact-free visual appearance. Compared to the state-of-the-art, the proposed method has several advantages: (1) it enables aggressive simplification with well preserved geometry and appearance; (2) it automatically achieves seamless simplification without special treatment on the seams between multi-charts of the texture; and (3) it is reliable. Experimental results have demonstrated these features. Nanyang Technological University National Research Foundation (NRF) This work was supported by a joint WASP/NTU project (04INS000440C130), Ynnerman Scholar (KAW 2019.0024) and National Research Foundation (NRF) Singapore, under its Virtual Singapore (VSG) Programme (Award No. NRF2015VSG-AA3DCM001-018).

Common vulnerabilities in typical intelligent cyber-physical systems such as unmanned aerial vehicles (UAVs) can be easily exploited by cyber attackers to cause serious accidents and harm. For successful UAV operations, security against cyber attacks is imperative. In this paper, we propose a modified sliding innovation sequences (MSIS) detector, based on the extended Kalman filter optimal state estimation, for a dynamic quadrotor system to detect cyber attacks inflicted on both its actuators and sensors in real time. These cyber attacks include random attacks, false data injection (FDI) attacks and denial-of-service (DoS) attacks. The MSIS detector computes the operator norm of the normalized innovation (residual) sequence within a sliding time window and triggers the alarm if the value is above the preset threshold. For a quadrotor undergoing rapid turns in a complex trajectory, the detector observes a reduced false alarm rate as compared to other state estimation-based detectors. To address the initial estimation error problem, we implement an iteration procedure to initiate and calibrate the detector. By evaluating the sample covariance of the normalized innovation sequence, the MSIS detector has the capability to isolate cyber attacks. Finally, simulation results of a quadrotor in a periodic, complex trajectory flight are provided to verify the effectiveness of the MSIS detection and isolation method. Ministry of Education (MOE) This work was supported by the Ministry of Education - Singapore, under its Academic Research Fund Tier 1 under Grant RG69/20.

Simultaneous trajectory prediction for multiple heterogeneous traffic participants is essential for safe and efficient operation of connected automated vehicles under complex driving situations. Two main challenges for this task are to handle the varying number of heterogeneous target agents and jointly consider multiple factors that would affect their future motions. This is because different kinds of agents have different motion patterns, and their behaviors are jointly affected by their individual dynamics, their interactions with surrounding agents, as well as the traffic infrastructures. A trajectory prediction method handling these challenges will benefit the downstream decision-making and planning modules of autonomous vehicles. To meet these challenges, we propose a three-channel framework together with a novel Heterogeneous Edge-enhanced graph ATtention network (HEAT). Our framework is able to deal with the heterogeneity of the target agents and traffic participants involved. Specifically, agents' dynamics are extracted from their historical states using type-specific encoders. The inter-agent interactions are represented with a directed edge-featured heterogeneous graph and processed by the designed HEAT network to extract interaction features. Besides, the map features are shared across all agents by introducing a selective gate-mechanism. And finally, the trajectories of multiple agents are predicted simultaneously. Validations using both urban and highway driving datasets show that the proposed model can realize simultaneous trajectory predictions for multiple agents under complex traffic situations, and achieve state-of-the-art performance with respect to prediction accuracy. The achieved final displacement error (FDE@3sec) is 0.66 meter under urban driving, demonstrating the feasibility and effectiveness of the proposed approach. Agency for Science, Technology and Research (A*STAR) Nanyang Technological University This work was supported in part by A*STAR Singapore under Grant W1925d0046 and in part by Start-Up Grant, Nanyang Technological University, Singapore.

International audience; Numerical simulation for resin transfer moulding manufacturing process is attempted using the extended finite element method combined with the level set method. The level set method is used to transport the resin flow front at each time step during the mould filling. Extended finite element method allows to obtaining a good numerical precision of the resin pressure near the resin flow front, where the gradient of the pressure could be discontinuous. The enriched shape functions of extended finite element method are derived using the level set values so as to correctly describe these shape functions with the resin flow front. In addition, the position of the resin flow front at each time step is calculated by an implicit characteristic Galerkin finite element method. Some examples are presented to validate our study in comparison with analytical or experimental results and to illustrate its industrial applications.

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.

This experimental study investigates the effect of scarf geometry in restoring the impact response of scarf-patched 3 mm thick glass-fiber reinforced polymer (GFRP) matrix composite laminates. Traditional circular along with rounded rectangular scarf patch configurations are considered repair patches. Experimental measurements revealed that the temporal variations of force and energy response of the pristine specimen are close to that of circular repaired specimens. The predominant failure modes were witnessed only in the repair patch which includes matrix cracking, fiber fracture, and delamination, and no discontinuity in the adhesive interface was witnessed. When compared with the pristine samples, the top ply damage size of the circular repaired specimens are larger by 9.91%, while that of the rounded rectangular repaired specimens is larger by 434.23%. The results show that circular scarf repair is a more suitable choice of repair approach under the condition of a 37 J low-velocity impact event even though the global force-time response is similar. National Research Foundation (NRF) Published version This work was financially supported by the National Research Foundation (NRF) of Singapore under the Corporate Laboratories @ Universities Scheme (ARMS 1.3 project).

In a flexible job shop problem with transportation (FJSPT), a typical flexible manufacturing system comprises transporters that pick up and deliver jobs for processing at flexible job shops. This problem has grown in importance through the wide use of automated transporters in Industry 4.0. In this article, a two-phase iterative mathematical programming-based heuristic is proposed to minimize makespan using a machine-operation assignment centric decomposition scheme. The first phase approximates the FJSPT through an augmented flexible job shop scheduling problem (FJSP + T) that reduces the solution space while serving as a heuristic in locating good machine-operation assignments. In the second phase, a job shop scheduling problem with transportation (JSPT) network is constructed from these assignments and solved for the makespan. Compared to prior JSPT implementations, the proposed JSPT model considers job pre-emption, which is instrumental in enabling this FJSPT implementation to outperform certain established benchmarks, confirming the importance of considering job pre-emption. Results indicate that the proposed approach is effective, robust, and competitive. Ministry of Education (MOE) Published version This work was funded by an AcRF Tier 1 grant (RG186/18) from the Ministry of Education, Singapore.

Detection of air traffic conflicts in a weather constrained airspace is challenging given the inherent uncertainties and aircraft maneuvers which give rise to new conflict birth-points. Traditional conflict detection tools are untenable in such situations as they primarily rely on flight-plan, aircraft performance characteristics and trajectories projection in short-term (2-4 minutes). This work adopts a convolutional neural network (CNN) model, on radar-like images, for conflict detection task in a constrained airspace. The CNN models are well-known for their learning capabilities when dealing with unstructured data like pixelated images. In this study, historical ADS-B data with weather constrained airspace is input as pixelated images to the CNN model. The learned model was compared with two well-known models for conflict detection (CD). The results demonstrated that the CNN based model was able to predict off-nominal conflict with high accuracy. The CNN model also demonstrated its ability to predict off-nominal conflict early for a given ten-minute look-ahead window. The CNN based model also showed low levels of false alarm signals as compared to other models. Generally speaking, all models showed low probabilities of miss-detection, mostly in the early phase of the 10-minute look-ahead window. This novel approach may serve to develop effective CD algorithms with longer look-ahead time and may aid in early detection of air traffic conflicts in non-nominal scenarios. Civil Aviation Authority of Singapore (CAAS) National Research Foundation (NRF) Submitted/Accepted version This research was supported by the National Research Foundation, Singapore, and the Civil Aviation Authority of Singapore, under the Aviation Transformation Programme.

International audience; The formation of Cube oriented elements in plane strain compressed aluminium has been studied by EBSD for both hot and cold deformations. By following the orientation changes of the same set of 176 grains deformed at 400 degrees C up to a strain of 1.2 using a split sample, it is shown that about 15% of the grains can break up into several regions of very different orientations, characterized by very large orientation gradients. In particular those grains oriented within about 30 degrees of Cube develop Cube oriented zones in contact with other rolling texture components. Finite element crystal plasticity simulations confirm this mechanism of creation of Cube by plastic deformation. The same type of microstructure can also be observed after heavy cold rolling (strain of 2.3), but at a scale that is much finer by at least an order of magnitude. In this case the micron-sized Cube fragments are located along many grain boundaries or in some particular grains. When the cold deformed sample is annealed, EBSD observations of the same areas reveal that the intergranular Cube fragments are very efficient recrystallization nucleation sites, apparently since they possess mobile high angle boundaries with the local environment.

Directed energy deposition (DED) is capable in producing complex or high-value components with good mechanical properties. Despite these potential advantages, the quality and integrity of multi-material DED parts, remains a challenging issue that limits its wide applications. Material porosity in multi-material components is detrimental since it may lead to premature structural failure. This paper proposes a two-stage ultrasonic method to characterise the internal structure to enhance the understanding of the process parameters on material porosity. In this method, the low-frequency model building aims at reconstructing background structure and the high-frequency imaging targets at small defects. The first stage is based on the gradient sampling full-waveform inversion for the estimation of the velocity model, which is then used as the initial model for the reverse time migration for reflectivity. The experimental results show that accurate reconstructions of the interface between two materials and defects in multi-material DED components can be achieved. Jing Rao was supported by the start-up grant from UNSW Canberra [grant number PS63396]. Jizhong Yang was supported by the National Natural Science Foundation of China [grant number 42004096] and the Fundamental Research Funds for the Central Universities.

In this paper, we perform molecular dynamics simulations to investigate the performance of multilayer graphene slit membranes. Graphene slit membranes at a critical slit size have been found to be promising desalination membranes. In this contribution, it is shown that multilayer slit membranes have the potential to provide significantly better permeability while retaining outstanding salt rejection. Improved permeability of the membrane is achieved by using slits of widths larger than the critical slit size required to reject salt through size exclusion, and desalination of sea water is performed by increased resistance to salt passage through the multilayering. To facilitate the design process of future multilayer membranes, we analyze the flow resistance of the membrane as a combination of electrical resistors in series and show that this analogy works for membranes where the layers possess the same slit size, as well as membranes with layers of different slit sizes. Comparing with single layer graphene membranes, it was shown that it is possible to obtain 55% improvement in permeability without loss in salt rejection capabilities through multilayering. This opens up possibilities for membrane designers to be free from the restrictions of using a single layer graphene slit membrane with a fixed slit width.

3D printing is a disruptive technology that is a key driver of the new industrial revolution. Among the various 3D printing methods, direct-ink-writing (DIW) takes a viscous ink material, extrudes it through a nozzle, and deposits it layer-by-layer to create 3D objects. DIW is a versatile method that can print ceramics, polymers, metals, living cells, etc. Yet, the ink formulation is critical for the success of printing. One major challenge to operate the transition to Industry 4.0 is to educate laypersons on 3D printing, without the need to master physics and chemistry. In this paper, we propose a protocol to familiarize laypersons with ink formulation for DIW. Using this protocol, a clay-based ink was optimized and the best ink composition containing 48 wt% clay and 2.4 wt% bamboo fibers was used for printing. The experimental set-ups and details used in the work are easily available, cheap, sustainable, and safe, enabling its implementation in various settings from classrooms to workshops, without the need for specialized equipment. Nanyang Technological University Published version The authors acknowledge financial support from Nanyang Technological University, Start-up grant, and the URECA undergraduate program. The authors thank Alireza Javadian from Singapore ETH Centre for providing bamboo microfibers.

Multilayer capsules not only provide better protection for the core, but also enable multifunctionalities. However, their fabrication is challenging. Rapid encapsulation by the impact of the droplet is a simplified approach to form the compound droplet with a single shell layer. Therefore, it is worth exploring the potential for multilayer capsule formation with the approach.We investigate the impact of an aqueous core droplet through a layered liquid pool to form compound droplet and use ultraviolet polymerization to solidify its outer layer. The critical conditions to form the compound droplet are studied. We then explore the protection features of the capsule.We succeed in fabricating defect-free capsules that featuring a triple-layered structure with a solid outer shell. The corresponding formation dynamics is revealed. We illustrate that the capsule provides reliable protection to the core through fluorescent intensity monitoring, pH level indication and bacteria revival test. Our method can also be adapted to tailor the functionality of the capsule, which is demonstrated by fabricating the magnetically steerable capsule. Our proposed approach offers great potentials for protecting sensitive ingredients and allows great flexibility in customizing capsule functionalities.

The maneuverability of standard quadrotors with coplanar propellers is limited by their inherent underactuation. To overcome this challenge, in-flight, active propeller tilting has been widely investigated in the literature. However, biaxial propeller tilting that renders extensive thrust vectoring has not been explored much owing to the ensuing mechanical complexities. Therefore, this paper presents an innovative design capable of achieving independent bi-axial tilting of 100° and 180° about two perpendicular axes while keeping the mechanical complexity relatively low. The developed quadrotor, aptly named QuadPlus, efficiently combines actuator redundancy and propeller rotation in a compact package, compared to its stateof-the-art counterparts. The hyperdynamic QuadPlus with a total of 12-DoFs can control its attitude independent of the position, thus enabling effective maneuvering through narrow spaces. Moreover, a novel cascade approach comprising of a high-level nonlinear model predictive control (NMPC) algorithm is adopted to obtain the optimal actuator configuration for an underdetermined system while dealing with the physical constraints. Also, proportional-integral-derivative controllers are employed at low-level to track attitude references generated by the navigation algorithm. Finally, with the help of realistic Gazebo simulations, the efficacy of the system is demonstrated by tracking complex 3-D trajectories which replicate the motion in a constrained environment. Overall, the obtained results manifest QuadPlus’s capability of achieving independent position and attitude control even with multiple actuator saturation. The Authors envision that the proposed simplistic design would stimulate interest in the community for exploring the benefits offered by bi-axial propeller tilting platforms. Ministry of Education (MOE) Accepted version This research is supported by the Ministry of Education, Singapore, under its Academic Research Fund Tier 1 (RG69/20)

The current problem is attributed to various features of Sisko nanofluids flow over-stretching cylinder along bioconvection of motile microorganisms in the presence of activation energy and non-Fourier thermal diffusion. The appropriate methodology is adopted to transform the governing boundary layer equations of fluid flow into the dimensionless nonlinear ODEs. The transformed coupled nonlinear differential equations are resolved numerically with MATLAB software with Bvp4c (Lobatto-IIIa) solver. The effect of dissimilar parameters viz., the Sisko material parameter, porosity parameter, bioconvection Lewis number, thermophoresis parameter, and bioconvection parameter on the velocity, temperature, concentration, and micro-organisms distribution are presented in numeric and graphics modes. The porous drag force of the Darcian linear system is used to evaluate the porosity parameter. It is also noticed that the numerical values of the porosity parameter reduced the velocity while it is enhancing the temperature. This research of wall cooling and heating bears is indispensable applications in solar porous water absorber systems, chemical engineering, space technology, metallurgy, substantial processing, and so forth. This Research was supported by Taif University Researchers Supporting Project Number (TURSP-2020/217), Taif University, Taif, Saudi Arabia.

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.

This paper proposes a novel method to impart intelligence to metal parts using additive manufacturing. A sensor-embedded metal bracket is prototyped via a metal powder bed fusion process to recognise partial screw loosening or total screw missing or identify the source of vibration with the assistance of artificial intelligence (AI). The digital metal bracket can recognise subtle changes in the screw fixation state with 90% accuracy and identify unknown sources of vibration with 84% accuracy. The von Mises stress distribution in the prototyped metal bracket is evaluated using a finite element analysis, which is learned by AI to match the real-time deformation analysis of the metal bracket in augmented reality. The proposed prototype can contribute to hyper-connectivity for developing next-generation metal-based mechanical components. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) [grant Nos. 2021M2D2A1A01050059 and 2021R1F1A1046079].

In this paper, a constrained image-based visual servoing control method for the shipboard landing problem of unmanned helicopters is proposed. First, the pitch and roll motion of ship are predicted by an auto-regressive (AR) model to determine an appropriate period for landing. Subsequently, a novel robust sliding mode controller without linear velocity measurements is developed on the basis of the perspective image feature in a virtual image plane. Meanwhile, a modified Chebyshev Neural Network (CNN) is proposed to estimate the uncertainties including the linear acceleration of ship and translational perturbation, while an adaptive law is employed to compensate the influence of rotational disturbances. The whole controller only requires the measurements feedback of a vision sensor and an inertial measurement unit (IMU). Ulteriorly, to prevent the visual target on the ship from going beyond the field of view of camera, the constrained controller is developed by a control barrier function and a quadratic programming, where the unknown relative velocity is estimated by a velocity observer. Finally, simulations are implemented to substantiate the capability of the presented shipboard landing control method. Accepted version This work was supported by the Beijing Natural Science Foundation (no. 4202038), China Postdoctoral Science Foundation (no. 2020TQ0028), the National Natural Science Foundation of China (no. 61827901), the National Key R&D Program of China (no. 2018YFC1506401), China Scholarship Council, and NTU ATMRI Project Agreement Research Grant (no. 2016-01).

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.

The current work investigates the successful preparation of Ni-TiN coatings via the jet electrodeposition method. The x-ray diffraction, high-resolution transmission electron microscopy, electrochemical workstation, and triboindenter were used to analyze the structure, mechanical deformation response, and corrosion properties of the coatings. The results reveal that the Ni-TiN coating produced by the deposition method had a fine and uniform microstructure at a 5 g/L concentration of TiN. The mean sizes of TiN nanoparticles and Ni grains were found to be 23.3 and 43.9 nm, respectively. The corrosion potential of the Ni-based TiN coating obtained at 5 g/L by electrodeposition was as minimum as − 0.396 V with a corrosion current density of 1.06 × 10−3 mA/cm2. The Ni-TiN coatings prepared, respectively, at three different concentrations (3, 5, and 8 g/L) under the applied load of 1500 µN were about 34.9, 28.2, and 30.3 µm in vertical depth, respectively. The coatings obtained at 5 g/L had the maximum nanohardness of 34.5 GPa when compared to the other coatings. In addition, the coatings were then subjected to three sliding scans, and the Ni-TiN coating prepared at 5 g/L showed the least magnitude of wear damage and plastic deformation when compared to the other coatings. This work has been supported by the Natural Science Foundation of China (Grant No. 51974089).

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).

Introduction: As highly sophisticated intercellular communication vehicles in biological systems, extracellular vesicles (EVs) have been investigated as both promising liquid biopsy-based disease biomarkers and drug delivery carriers. Despite tremendous progress in understanding their biological and physiological functions, mechanical characterization of these nanoscale entities remains challenging due to the limited availability of proper techniques. Especially, whether damage to parental cells can be reflected by the mechanical properties of their EVs remains unknown. Methods: In this study, we characterized membrane viscosities of different types of EVs collected from primary human trophoblasts (PHTs), including apoptotic bodies, microvesicles and small extracellular vesicles, using fluorescence lifetime imaging microscopy (FLIM). The biochemical origin of EV membrane viscosity was examined by analyzing their phospholipid composition, using mass spectrometry. Results: We found that different EV types derived from the same cell type exhibit different membrane viscosities. The measured membrane viscosity values are well supported by the lipidomic analysis of the phospholipid compositions. We further demonstrate that the membrane viscosity of microvesicles can faithfully reveal hypoxic injury of the human trophoblasts. More specifically, the membrane of PHT microvesicles released under hypoxic condition is less viscous than its counterpart under standard culture condition, which is supported by the reduction in the phosphatidylethanolamine-to-phosphatidylcholine ratio in PHT microvesicles. Discussion: Our study suggests that biophysical properties of released trophoblastic microvesicles can reflect cell health. Characterizing EV’s membrane viscosity may pave the way for the development of new EV-based clinical applications. Ministry of Education (MOE) Nanyang Technological University Submitted/Accepted version This work was supported by Eunice Kennedy Shriver National Institute of Child Health and Human Development [R01HD086325, R37HD086916]; Nanyang Technological University [M4082352, M4082428]; the Ministry of Education, Singapore, under its Academic Research Fund Tier 1 [RG92/19]; National Institute of Health [S10OD023402].

The propensity of cells to align in particular directions is relevant to a number of areas, including tissue engineering and biohybrid robotics. Cell alignment is modulated through various extracellular conditions including surface topographies, mechanical cues from cell-matrix interactions, and cell-cell interactions. Understanding of these conditions provides guidance for desirable cellular structure constructions. In this study, we examine the roles of surface topographies and cell-cell interactions in inducing cell alignment. We employed wavy surface topographies at the nanometer scale as a model extracellular environment for cell culture. The results show that, within a certain range of wavelengths and amplitudes of the surface topographies, cell alignment is dependent on cell confluency. This dependence on both topology and confluency suggests interplay between cell-cell and cell-matrix interactions in inducing cell alignment. Images of sparsely distributed and confluent cells also demonstrated clear differences in the structures of their focal adhesion complexes. To understand this effect, we introduced anti-N-cadherin to cell culture to inhibit cell-cell interactions. The results show that, when anti-N-cadherin was applied, cells on wavy surfaces required greater confluency to achieve the same alignment compared to that in the absence of anti-N-cadherin. The understanding of the cell alignment mechanisms will be important in numerous potential applications such as scaffold design, tissue repair, and development of biohybrid robotic systems. STATEMENT OF SIGNIFICANCE: Cell alignment plays a critical role in numerous biological functions. Advances in tissue engineering utilizes cell alignment to restore, maintain, or even replace different types of biological tissues. The clinical impact that tissue engineering has made is facilitated by advancements in the understanding of interactions between scaffolds, biological factors, and cells. This work further elucidates the role of cell-cell interactions in promoting the organization of biological tissues. Nanyang Technological University Published version This work was supported in part by the National Institute of Health (R01AG06100501A1), Air Force Office of Scientific Research (FA9550–18–1-0262), National Science Foundation (CMMI-1946456), Office of Naval Research (N00014-17–1–2566), and the Pennsylvania Department of Health (SAP4100077084). BD and KJH acknowledge partial financial support by the NIH Eunice Kennedy Shriver National Institute of Child Health and Human Development (grant R01HD086325). KJH, YH and HRS would like to acknowledge the financial support from Nanyang Technological University (grant M4082428.050).

A molecular dynamics (MD) simulation method is used to investigate the effect of grain boundary (GB) segregation on the deformation behavior of bicrystals of equiatomic nanoscale CoCrCuFeNi high-entropy alloy (HEA). The deformation mechanisms during shear and tensile deformation at 300 K and 100 K are analyzed. It is revealed that upon tensile deformation, the stacking fault formation, and twinning are the main deformation mechanisms, while for the shear deformation, the main contribution to the plastic flow is realized through the GB migration. The presence of the segregation at GBs leads to the stabilization of GBs, while during the shear deformation of the nanoscale CoCrCuFeNi HEA without the segregation at GBs, GBs are subject to migration. It is found that the GB segregation can differently influence the plasticity of the nanoscale CoCrCuFeNi HEA, depending on the elemental composition of the segregation layer. In the case of copper and nickel segregations, an increase in the segregation layer size enhances the plasticity of the nanoscale CoCrCuFeNi HEA. However, an increase in the thickness of chromium segregations deteriorates the plasticity while enhancing maximum shear stress. The results obtained in this study shed light on the development of HEAs with enhanced mechanical properties via GB engineering. Published version The research was carried out with financial support from the Ministry of Science and Higher Education of the Russian Federation within the framework of the state assignment of the Ufa University of Science and Technology (Agreement No. 075-03-2023-119) for the Youth Research Laboratory of the Center for Metals and Alloys under Extreme Conditions for K.A.M., grant NSH4320.2022.1.2 for K.A.A., and grant RSF 21-12-00275 for K.E.A.

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.