Publications
J Park, J Noh, J Shin, GX Gu, and J Rho. Investigating static and dynamic behaviors in 3D chiral mechanical metamaterials by disentangled generative models. Advanced Functional Materials, 2024
A Chen, U Ezimora, S Lee, JH Lee, and GX Gu. Sea sponge-inspired designs enhance mechanical properties of tubular lattices. International Journal of Mechanical Sciences, 2024
KA Brown and GX Gu. Computational challenges in additive manufacturing for metamaterials design. Nature Computational Science, 2024 [PDF]
J Jung and GX Gu. Data-driven airfoil shape optimization framework for enhanced flutter performance. Physics of Fluids, 2024 [PDF]
D Lim, S Lee, JH Lee, W Choi, GX Gu. Mechanical metamaterials as broadband electromagnetic wave absorbers: Investigating relationships between geometrical parameters and electromagnetic response. Materials Horizons, 2024 [PDF]
S Lee, J Kwon, H Kim, RO Ritchie, and GX Gu. Advancing programmable metamaterials through machine learning-driven buckling strength optimization. Current Opinion in Solid State and Materials Science, 2024 [PDF]
Z Wei, S Wang, S Farris, N Chennuri, N Wang, S Shinsato, K Demir, M Horii, and GX Gu. Towards silent and efficient flight by combining bioinspired owl feather serrations with cicada wing geometry. Nature Communications, 2024 [PDF]
Z Zhang, JH Lee, L Sun, and GX Gu. Weak-formulated physics-informed modeling and optimization for heterogeneous digital materials. PNAS Nexus, 2024
J Lee, H Han, D Noh, J Lee, DD Lim, J Park, GX Gu, and W Choi. Multiscale Porous Architecture Consisting of Graphene Aerogels and Metastructures Enabling Robust Thermal and Mechanical Functionalities of Phase Change Materials. Advanced Functional Materials, 2024
D Park, J Lee, H Lee, GX Gu, and S Ryu. Deep generative spatiotemporal learning for integrating fracture mechanics in composite materials: inverse design, discovery, and optimization. Materials Horizons, 2024
B Zheng, GX Gu, CD Santos, R Neumann Barros Ferreira, M Steiner, and B Luan. Simulating CO2 diffusivity in rigid and flexible Mg-MOF-74 with machine-learning force fields. APL Machine Learning, 2024 [PDF]
J Jung, A Chen, and GX Gu. Aperiodicity is all you need: Aperiodic monotiles for high-performance composites. Materials Today, 2024 [PDF]
S Lee, H Sheikh, D Lim, GX Gu, and P Marcus. Bayesian-optimized riblet surface design for turbulent drag reduction via design-by-morphing with large eddy simulation. Journal of Mechanical Design, 2024
Z Wei, Z Zhang, D Lim, J Rey, M Jones, and GX Gu. Influence of bioinspired riblet topographies on the mitigation of flow-induced noise in towed sonar arrays. Extreme Mechanics Letters, 2024
Z Jin, D Lim, X Zhao, M Mamunuru, S Roham, and GX Gu. Machine learning enabled optimization of showerhead design for semiconductor deposition process. Journal of Intelligent Manufacturing, 2024 [PDF]
E Antimirova, J Jung, Z Zhang, A Machuca, and GX Gu. Overview of computational methods to predict flutter in aircraft. Journal of Applied Mechanics, 2024 [PDF]
C Lee, H Shi, J Jung, B Zheng, K Wang, R Tutika, R Long, B Lee, GX Gu, and MD Bartlett. Bioinspired materials for underwater adhesion with pathways to switchability. Cell Reports Physical Science, 2023
B Zheng, C Liu, Z Li, C Carraro, R Maboudian, DG Senesky, and GX Gu. Investigation of mechanical properties and structural integrity of graphene aerogels via molecular dynamics simulations. Physical Chemistry Chemical Physics, 2023 [PDF]
Z Jin, B Zheng, C Kim, and GX Gu. Leveraging graph neural networks and neural operator techniques for high-fidelity mesh-based physics simulations. APL Machine Learning, 2023
JH Lee, Z Zhang, and GX Gu. Dynamic homogenization of heterogeneous piezoelectric media: a polarization approach using infinite-body Green’s function. Journal of the Mechanics and Physics of Solids, 2023
RA Smaldone, KA Brown, GX Gu, and C Ke. Using 3D printing as a research tool for materials discovery. Device, 2023
B Zheng, F Oliveira, R Neumann Barros Ferreira, M Steiner, H Hamann, GX Gu, and B Luan. Quantum informed machine-learning potentials for molecular dynamics simulations of CO2’s chemisorption and diffusion in Mg-MOF-74. ACS Nano, 2023 [PDF]
Z Jin, G Hu, Z Zhang, SY Yu, and GX Gu. Modeling and analysis of post-processing conditions on 4D-bioprinting of deformable hydrogel-based biomaterial inks. Bioprinting, 2023
S Lee, Z Zhang, and GX Gu. Deep learning accelerated design of mechanically efficient architected materials. ACS Applied Materials & Interfaces, 2023 acs_lee_v2.pdf
CT Chen and GX Gu. Physics-informed deep-learning for elasticity: Forward, inverse, and mixed problems. Advanced Science, 2023
M Abed, E Archibeck, R Isied, Y Feteih, G O’Connell, and GX Gu. Influence of radial stiffness gradients on porous composite bulk mechanics. Advanced Engineering Materials, 2023 [PDF]
SY Yu, S Lee, Z Zhang, Z Jin, and GX Gu. From brittle to ductile: Symmetry breaking in strut-based architected materials. ACS Materials Letters, 2023 [PDF]
B Zheng, Z Jin, G Hu, J Gu, SY Yu, JH Lee, and GX Gu. Machine learning and experiments: A synergy for the development of functional materials. MRS Bulletin, 2023 [PDF]
AY Chen, A Chen, A Fitzhugh, A Hartman, P Kaiser, I Nwaogwugwu, J Zeng, and GX Gu. Multi Jet Fusion printed lattice materials: Characterization and prediction of mechanical performance. Materials Advances, 2023 [PDF]
JH Lee, Z Zhang, and GX Gu. Maximum electro-momentum coupling in piezoelectric metamaterial scatterers. Journal of Applied Physics, 2022
AY Chen, A Chen, J Wright, A Fitzhugh, A Hartman, J Zeng, and GX Gu. Effect of build parameters on the mechanical behavior of polymeric materials produced by multi-jet fusion. Advanced Engineering Materials, 2022
D Park, J Jung, GX Gu, and S Ryu. A generalizable and interpretable deep learning model to improve the prediction accuracy of strain fields in grid composites. Materials & Design, 2022
S Lee, W Choi, JW Park, D Kim, S Nahm, W Jeon, GX Gu, M Kim, and S Ryu. Machine learning-enabled development of high performance gradient-index phononic crystals for energy focusing and harvesting. Nano Energy, 2022
Z Zhang, JH Lee, and GX Gu. Rational design of piezoelectric metamaterials with tailored electro-momentum coupling. Extreme Mechanics Letters, 2022
S Lee, DD Lim, E Pegg, and GX Gu. The origin of high-velocity impact response and damage mechanisms for bioinspired composites. Cell Reports Physical Science, 2022
V Shah, S Zadourian, C Yang, Z Zhang, and GX Gu. Data-driven approach for the prediction of mechanical properties of carbon fiber reinforced composites, Materials Advances, 2022
B Zheng, Z Zheng, and GX Gu. Designing mechanically tough graphene oxide materials using deep reinforcement learning. npj Computational Materials, 2022 [PDF]
Z Zhang, Z Jin, and GX Gu. Efficient pneumatic actuation modeling using hybrid physics-based and data-driven framework. Cell Reports Physical Science, 2022 [PDF]
S Lee, Z Zhang, and GX Gu. Generative machine learning algorithm for lattice structures with superior mechanical properties. Materials Horizons, 2022 [PDF]
Z Zhang, Z Zhang, F Di Caprio, and GX Gu. Machine learning for accelerating the design process of double-double composite structures. Composite Structures, 2022
B Zheng, Z Zheng, and GX Gu. Uncertainty quantification and prediction for mechanical properties of graphene aerogels via Gaussian process metamodels. Nano Futures, 2021
K Brown and GX Gu. Dimensions of smart additive manufacturing. Advanced Intelligent Systems, 2021 [PDF]
Y Kim, Y Kim, C Yang, K Park, GX Gu, and S Ryu. Deep learning framework for material design space exploration using active transfer learning and data augmentation. npj Computational Materials, 2021
A Chen, K Thind, K Demir, and GX Gu. Modeling bioinspired fish scale designs via a geometric and numerical approach. Materials, 2021
B Zheng, Z Zheng, and GX Gu. Scalable graphene defect prediction using transferable learning. Nanomaterials, 2021
F Sui, R Guo, Z Zhang, GX Gu, and L Lin. Deep reinforcement learning for digital materials design. ACS Materials Letters, 2021
AY Chen, E Pegg, A Chen, Z Jin, and GX Gu. 4D-printing of electro-active materials. Advanced Intelligent Systems, 2021
CT Chen and GX Gu. Learning hidden elasticity with deep neural networks. Proceedings of the National Academy of Sciences, 2021 [PDF]
T Shu, Z Lv, CT Chen, GX Gu, J Ren, L Cao, Y Pei, S Ling, and DL Kaplan. Mechanical training‐driven structural remodeling: A rational route for outstanding highly hydrated silk materials. Small, 2021
K Demir, Z Zhang, A Ben-Artzy, P Hosemann, and GX Gu. Laser scan strategy descriptor for defect prognosis in metal additive manufacturing using neural networks. Journal of Manufacturing Processes, 2021 [PDF]
Z Jin, Z Zhang, X Shao, and GX Gu. Monitoring anomalies in 3D-bioprinting with deep neural networks. ACS Biomaterials Science & Engineering, 2021 [PDF]
AY Chen, S Baehr, A Turner, Z Zhang, and GX Gu. Carbon-fiber reinforced polymer composites: A comparison of manufacturing methods on mechanical properties. International Journal of Lightweight Materials and Manufacture, 2021
B Zheng and GX Gu. Prediction of Graphene Oxide Functionalization using Gradient Boosting: Implications for Material Chemical Composition Identification. ACS Applied Nano Materials, 2021 [PDF]
T Shu, K Zheng, Z Zhang, J Ren, Z Wang, Y Pei, J Yeo, GX Gu, and S Ling. Birefringent Silk Fibroin Hydrogel Constructed via Binary Solvent-Exchange-Induced Self-Assembly. Biomacromolecules, 2021
Z Jin, Z Zhang, J Ott, and GX Gu. Precise localization and semantic segmentation detection of printing conditions in fused filament fabrication technologies using machine learning. Additive Manufacturing, 2021 [PDF]
Z Zhang and GX Gu. Physics-informed deep learning for digital materials. Theoretical & Applied Mechanics Letters, 2021 [PDF]
Z Jin, Z Zhang, K Demir, and GX Gu. Machine learning for advanced additive manufacturing. Matter, 2020 [PDF]
E Jacobs, C Yang, K Demir, and GX Gu. Vibrational detection of delamination in composites using a combined finite element analysis and machine learning approach. Journal of Applied Physics, 2020 [PDF]
B Zheng and GX Gu. Machine learning‑based detection of graphene defects with atomic precision. Nano-Micro Letters, 2020 [PDF]
CT Chen, D Chrzan, and GX Gu. Nano-topology optimization for materials design with atom-by-atom control. Nature Communications, 2020 [PDF]
YT Kim, C Yang, YS Kim, GX Gu, and S Ryu. Designing adhesive pillar shape with deep learning-based optimization. ACS Applied Materials & Interfaces, 2020 [PDF]
Z Zhang and GX Gu. Finite element based deep learning model for deformation behavior of digital materials. Advanced Theory and Simulations, 2020 [PDF]
K Demir, Z Zhang, J Yang, and GX Gu. Computational and experimental design exploration of 3D‐printed soft pneumatic actuators. Advanced Intelligent Systems, 2020 [PDF]
B Zheng and GX Gu. Stress field characteristics and collective mechanical properties of defective graphene. Journal of Physical Chemistry C, 2020 [PDF]
Z Vangelatos, Z Zhang, GX Gu, and CP Grigoropoulos. Tailoring the dynamic actuation of 3D printed mechanical metamaterials through inherent and extrinsic instabilities. Advanced Engineering Materials, 2020 [PDF]
C Yang, YS Kim, S Ryu, and GX Gu. Prediction of composite microstructure stress-strain curves using convolutional neural networks. Materials & Design, 2020 [PDF]
CT Chen and GX Gu. Generative deep neural networks for inverse materials design using backpropagation and active learning. Advanced Science, 2020 [PDF]
JD Ott, MT Lazalde, GX Gu. Algorithmic-driven design of shark denticle bioinspired structures for superior aerodynamic properties. Bioinspiration & Biomimetics, 2020 [PDF]
J Wilt, C Yang, and GX Gu. Accelerating auxetic metamaterial design with deep learning. Advanced Engineering Materials, 2020 [PDF]
Z Jin, Z Zhang, and GX Gu. Automated real‐time detection and prediction of inter‐Layer imperfections in additive manufacturing processes using artificial intelligence. Advanced Intelligent Systems, 2020 [PDF]
B Zheng and GX Gu. Recovery from mechanical degradation of graphene by defect enlargement. Nanotechnology, 2019 [PDF]
Z Vangelatos, GX Gu, C Grigoropoulos. Architected metamaterials with tailored 3D buckling mechanisms at the microscale. Extreme Mechanics Letters, 2019 [PDF]
B Zheng and GX Gu. Tuning graphene mechanical anisotropy via defect engineering. Carbon, 2019 [PDF]
Z Jin, Z Zhang, and GX Gu. Autonomous in-situ correction of fused deposition modeling printers using computer vision and deep learning. Manufacturing Letters, 2019 [PDF]
C Yang, YS Kim, S Ryu, and GX Gu. Using convolutional neural networks to predict composite properties beyond the elastic limit. MRS Communications, 2019 [PDF]
YS Kim, H Jeong, GX Gu, and S Ryu. A three-dimensional fracture pattern diagram of staggered platelet structures. Composite Structures, 2019
CT Chen and GX Gu. Effect of Constituent Materials on Composite Performance: Exploring Design Strategies via Machine Learning. Advanced Theory and Simulations, 2019 [PDF]
Z Zhang, K Demir, and GX Gu. Computational analysis of thermally induced stress concentration in structures with geometric constraints. Mechanics of Materials, 2019 [PDF]
CT Chen and GX Gu. Machine learning for composite materials. MRS Communications, 2019 [PDF]
Z Zhang, K Demir, and GX Gu. Developments in 4D-printing: A review on current smart materials, technologies, and applications. International Journal of Smart and Nano Materials, 2019 [PDF]
GX Gu, CT Chen, D Richmond, and MJ Buehler. Bioinspired hierarchical composite design using machine learning: Simulation, additive manufacturing, and experiment. Materials Horizons, 2018 [PDF]
GX Gu and MJ Buehler. Tunable mechanical properties through texture control of polycrystalline additively manufactured materials using adjoint- based gradient optimization. Acta Mechanica, 2018 [PDF]
J Yeo, GS Jung, FM Martinez, S Ling, GX Gu, Z Qin, and MJ Buehler. Materials-by-design: Computation, synthesis, and characterization from atoms to structures, Physica Scripta, 93 (5), 2018 [PDF]
GX Gu, CT Chen, and MJ Buehler. De novo composite design based on machine learning algorithm. Extreme Mechanics Letters, 18:19-28, 2018 [PDF]
GX Gu, M Takaffoli, and MJ Buehler. Hierarchically enhanced impact resistance of bioinspired composites. Advanced Materials, 29 (28), 2017 [PDF]
GX Gu, S Wettermark, and MJ Buehler. Algorithm driven design of fracture resistant composite materials realized through additive manufacturing. Additive Manufacturing, 17:47-54, 2017 [PDF]
GX Gu, F Libonati, S Wettermark, and MJ Buehler. Printing nature: Unraveling the role of nacre’s mineral bridges. Journal of the Mechanical Behavior of Biomedical Materials, 76:135-144, 2017 [PDF]
GX Gu, I Su, S Sharma, J Voros, Z Qin, and MJ Buehler. Three-dimensional-printing of bio-inspired composites. Journal of Biomechanical Engineering, 138 (2), 2016 [PDF]
GX Gu, L Dimas, Z Qin, and MJ Buehler. Optimization of composite fracture properties: Method, validation, and applications. Journal of Applied Mechanics, 83 (7), 2016 [PDF]
GX Gu, M Takaffoli, A Hsieh, and MJ Buehler. Biomimetic additive manufactured polymer composites for improved impact resistance. Extreme Mechanics Letters, 9:317-323, 2016 [PDF]
F Libonati, GX Gu, Z Qin, L Vergani, and MJ Buehler. Bone-inspired materials by design: Toughness amplification observed using 3D printing and testing. Advanced Engineering Materials, 18 (8), 2016 [PDF]