Papers citing Artificial intelligence design algorithm for nanocomposites optimized for shear crack resistance
Biological Material Interfaces as Inspiration for Mechanical and Optical Material Designs
Chemical Reviews · 2019
Jing Ren, Yu Wang, Yuan Yao, Yang Wang, Xiang Fei, Ping Qi, Shihui Lin, David Lee Kaplan, Markus J. Buehler, Shengjie Ling
Read original paper ↗ ·Nanoengineering in biomedicine: Current development and future perspectives
Nanotechnology Reviews · 2020
Wei Jian, David Hui, Denvid Lau
Read original paper ↗ ·Sonification based de novo protein design using artificial intelligence, structure prediction, and analysis using molecular modeling
APL Bioengineering · 2020
Chi‐Hua Yu, Markus J. Buehler
Read original paper ↗ ·Designing an Adhesive Pillar Shape with Deep Learning-Based Optimization
ACS Applied Materials & Interfaces · 2020
Yongtae Kim, Charles Yang, Youngsoo Kim, Grace X. Gu, Seunghwa Ryu
Read original paper ↗ ·Using Deep Learning to Predict Fracture Patterns in Crystalline Solids
Matter · 2020
Yu-Chuan Hsu, Chi‐Hua Yu, Markus J. Buehler
Read original paper ↗ ·Digital and experimental synergies to design high-heeled shoes
The International Journal of Advanced Manufacturing Technology · 2020
Mario Milazzo, Andrea Spezzaneve, Alessandro Persichetti, Massimo Tomasi, Valentina Peselli, Angelo Messina, Francesca Gambineri, Giacomo Aringhieri, Stefano Roccella
Read original paper ↗ ·Polymer nanodielectrics—Short history and future perspective
Journal of Applied Physics · 2020
Linda S. Schadler, J. K. Nelson
Read original paper ↗ ·A semi-supervised approach to architected materials design using graph neural networks
Extreme Mechanics Letters · 2020
Kai Guo, Markus J. Buehler
Read original paper ↗ ·WebNet: A biomateriomic three-dimensional spider web neural net
Extreme Mechanics Letters · 2020
Eric L. Buehler, Isabelle Su, Markus J. Buehler
Read original paper ↗ ·Hydration-induced reversible deformation of biological materials
Nature Reviews Materials · 2020
Haocheng Quan, David Kisailus, Marc André Meyers
Read original paper ↗ ·Surrogate Model via Artificial Intelligence Method for Accelerating Screening Materials and Performance Prediction
Advanced Functional Materials · 2020
Tian Wang, Mingqi Shao, Rong Guo, Fei Tao, Gang Zhang, Hichem Snoussi, Xingling Tang
Read original paper ↗ ·Artificial intelligence and machine learning in design of mechanical materials
Materials Horizons · 2020
Kai Guo, Zhenze Yang, Chi‐Hua Yu, Markus J. Buehler
Read original paper ↗ ·Exploring the potential of transfer learning for metamodels of heterogeneous material deformation
Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials · 2020
Emma Lejeune, Bingxiao Zhao
Read original paper ↗ ·Characterising soft matter using machine learning
Soft Matter · 2021
Paul S. Clegg
Read original paper ↗ ·Pragmatic generative optimization of novel structural lattice metamaterials with machine learning
Materials & Design · 2021
Anthony P. Garland, Benjamin C. White, Scott Jensen, Brad L. Boyce
Read original paper ↗ ·Taking the leap between analytical chemistry and artificial intelligence: A tutorial review
Analytica Chimica Acta · 2021
Lucas B. Ayres, Federico J.V. Gómez, Jeb R. Linton, María Fernanda Silva, Carlos D. García
Read original paper ↗ ·Deep learning model to predict complex stress and strain fields in hierarchical composites
Science Advances · 2021
Zhenze Yang, Chi‐Hua Yu, Markus J. Buehler
Read original paper ↗ ·End-to-end deep learning method to predict complete strain and stress tensors for complex hierarchical composite microstructures
Journal of the Mechanics and Physics of Solids · 2021
Zhenze Yang, Chi‐Hua Yu, Kai Guo, Markus J. Buehler
Read original paper ↗ ·A stochastic multiscale method for the prediction of the thermal conductivity of Polymer nanocomposites through hybrid machine learning algorithms
Composite Structures · 2021
Bokai Liu, N. Vu‐Bac, Timon Rabczuk
Read original paper ↗ ·Autonomous reinforcement learning agent for stretchable kirigami design of 2D materials
npj Computational Materials · 2021
Pankaj Rajak, Beibei Wang, Ken‐ichi Nomura, Ye Luo, Aiichiro Nakano, Rajiv K. Kalia, Priya D. Vashishta
Read original paper ↗ ·Deep learning approach to assess damage mechanics of bone tissue
Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials · 2021
Sabrina Chin-yun Shen, Marta Peña Fernández, Gianluca Tozzi, Markus J. Buehler
Read original paper ↗ ·Machine Learning‐Based and Experimentally Validated Optimal Adhesive Fibril Designs
Small · 2021
Donghoon Son, Ville Liimatainen, Metin Sitti
Read original paper ↗ ·Words to Matter: De novo Architected Materials Design Using Transformer Neural Networks
Frontiers in Materials · 2021
Zhenze Yang, Markus J. Buehler
Read original paper ↗ ·Machine Learning‐Driven Biomaterials Evolution
Advanced Materials · 2021
Ady Suwardi, Fuke Wang, Kun Xue, Ming‐Yong Han, Peili Teo, Pei Wang, Shijie Wang, Ye Liu, Enyi Ye, Li Zibiao, Xian Jun Loh
Read original paper ↗ ·ColGen: An end-to-end deep learning model to predict thermal stability of de novo collagen sequences
Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials · 2021
Chi‐Hua Yu, Eesha Khare, Om Prakash Narayan, Rachael N. Parker, David Lee Kaplan, Markus J. Buehler
Read original paper ↗ ·Biomimicry for natural and synthetic composites and use of machine learning in hierarchical design
Elsevier eBooks · 2022
Mario Milazzo, Flavia Libonati, Shengfei Zhou, Kai Guo, Markus J. Buehler
Read original paper ↗ ·Physically soft magnetic films and devices: fabrication, properties, printability, and applications
Journal of Materials Chemistry C · 2022
Anjali Dhamsania, William Mah, Arjun Sivarajan, John Ting, Stephen Chung, Elizabeth Carlson, Alex Wang, Gillian Hiu Man Lee, Bryan Huynh, Anson Chen, Lillian Mueller, Caius Kim, Swarup Kumar Subudhi, Beihan Zhao, Bhargav Sai Chava, Siddhartha Das
Read original paper ↗ ·Rapid prediction of protein natural frequencies using graph neural networks
Digital Discovery · 2022
Kai Guo, Markus J. Buehler
Read original paper ↗ ·End-to-End Deep Learning Model to Predict and Design Secondary Structure Content of Structural Proteins
ACS Biomaterials Science & Engineering · 2022
Chi‐Hua Yu, Wei Chen, Yu-Hsuan Chiang, Kai Guo, Zaira Martín‐Moldes, David Lee Kaplan, Markus J. Buehler
Read original paper ↗ ·Deep learning based design of porous graphene for enhanced mechanical resilience
Computational Materials Science · 2022
Chi‐Hua Yu, Chang-Yan Wu, Markus J. Buehler
Read original paper ↗ ·The Synergistic Role of Additive Manufacturing and Artificial Intelligence for the Design of New Advanced Intelligent Systems
Advanced Intelligent Systems · 2022
Mario Milazzo, Flavia Libonati
Read original paper ↗ ·PRESTO: Rapid protein mechanical strength prediction with an end-to-end deep learning model
Extreme Mechanics Letters · 2022
Frank Y.C. Liu, Bo Ni, Markus J. Buehler
Read original paper ↗ ·The philosophy of extreme biomimetics
Sustainable materials and technologies · 2022
Hermann Ehrlich, Marcin Wysokowski, Teofil Jesionowski
Read original paper ↗ ·Fracture at the two-dimensional limit
MRS Bulletin · 2022
Bo Ni, Doug Steinbach, Zhenze Yang, Andrew James Lew, Boyu Zhang, Qiyi Fang, Markus J. Buehler, Jun Lou
Read original paper ↗ ·A State-of-the-Art Review on Machine Learning-Based Multiscale Modeling, Simulation, Homogenization and Design of Materials
Archives of Computational Methods in Engineering · 2022
Dana Bishara, Yuxi Xie, Wing Kam Liu, Shaofan Li
Read original paper ↗ ·Hierarchical Multiresolution Design of Bioinspired Structural Composites Using Progressive Reinforcement Learning
Advanced Theory and Simulations · 2022
Chi‐Hua Yu, Bor‐Yann Tseng, Zhenze Yang, Cheng‐Che Tung, Elena Zhao, Zhi‐Fan Ren, Shengsheng Yu, Po‐Yu Chen, Chuin‐Shan Chen, Markus J. Buehler
Read original paper ↗ ·A Review of Performance Prediction Based on Machine Learning in Materials Science
Nanomaterials · 2022
Ziyang Fu, Weiyi Liu, Chen Shi. Huang, Tao Mei
Read original paper ↗ ·Linking atomic structural defects to mesoscale properties in crystalline solids using graph neural networks
npj Computational Materials · 2022
Zhenze Yang, Markus J. Buehler
Read original paper ↗ ·Al-Sn-Al Bonding Strength Investigation Based on Deep Learning Model
Processes · 2022
Jiang Min, Min Yu, Bao Li, Hongze Zhang, Zhiyuan Zhu
Read original paper ↗ ·Fractal Geometry and Convolutional Neural Networks for the Characterization of Thermal Shock Resistances of Ultra-High Temperature Ceramics
Fractal and Fractional · 2022
Shanxiang Wang, Zailiang Chen, Fei Qi, Chenghai Xu, Chunju Wang, Tao Chen, Hao Guo
Read original paper ↗ ·Data-Driven Machine Learning to Predict Mechanical Properties of Monolayer Transition-Metal Dichalcogenides for Applications in Flexible Electronics
ACS Applied Nano Materials · 2022
Prottay Malakar, Md Shajedul Hoque Thakur, Shahriar Muhammad Nahid, Md Mahbubul Islam
Read original paper ↗ ·Prediction of punching shear strength of slab-column connections: A comprehensive evaluation of machine learning and deep learning based approaches
Mechanics of Advanced Materials and Structures · 2022
Shahram Derogar, Ceren Ince, Hakan Yekta Yatbaz, Enver Ever
Read original paper ↗ ·In silico approaches for polymeric nanocomposites
Elsevier eBooks · 2023
Tânia F. G. G. Cova, Sandra C. C. Nunes, Carla Vitorino, Márcio Ferreira, Paola Rondón-Villarreal, Alberto A. C. C. Pais
Read original paper ↗ ·Predicting the Mechanical Response Profile of Porous Materials Via Microstructure-Informed Neural Networks
SSRN Electronic Journal · 2023
Winston F Lindqwister, Jacob Peloquin, Laura E. Dalton, Ken Gall, Manolis Veveakis
Read original paper ↗ ·Designing Bioinspired Composite Structures via Genetic Algorithm and Conditional Variational Autoencoder
Polymers · 2023
Yi-Hung Chiu, Ya-Hsuan Liao, Jia‐Yang Juang
Read original paper ↗ ·Advanced ocean wave energy harvesting: current progress and future trends
Journal of Zhejiang University. Science A · 2023
Fang He, Yibei Liu, Jiapeng Pan, Xinghong Ye, Pengcheng Jiao
Read original paper ↗ ·Fill in the Blank: Transferrable Deep Learning Approaches to Recover Missing Physical Field Information
Advanced Materials · 2023
Zhenze Yang, Markus J. Buehler
Read original paper ↗ ·Accelerated Design of Architected Materials with Multifidelity Bayesian Optimization
Journal of Engineering Mechanics · 2023
Chengyang Mo, Paris G. Perdikaris, Jordan R. Raney
Read original paper ↗ ·Reinforcement learning design framework for nacre-like structures optimized for pre-existing crack resistance
Journal of Materials Research and Technology · 2023
Bor‐Yann Tseng, You-Cheng Cai, Chen‐Wei Conan Guo, Elena Zhao, Chi‐Hua Yu
Read original paper ↗ ·Deep Learning Model to Predict Ice Crystal Growth
Advanced Science · 2023
Bor‐Yann Tseng, Chen‐Wei Conan Guo, Yu‐Chen Chien, Jyn‐Ping Wang, Chi‐Hua Yu
Read original paper ↗ ·