Papers citing Artificial intelligence and machine learning in design of mechanical materials
Artificial intelligence assisted with designing metal‐organic frameworks (MOFs)
Clinical and Translational Discovery · 2023
Navid Rabiee
Read original paper ↗ ·Artificial intelligence-enhanced bioinspiration: Design of optimized mechanical lattices beyond deep-sea sponges
Extreme Mechanics Letters · 2023
Zongliang Du, Wenyu Hao, Xiaodong Chen, Xiuquan Hou, Wendong Huo, Chang Liu, Weisheng Zhang, Tianchen Cui, Xu Guo
Read original paper ↗ ·Recognition of rock materials after high-temperature deterioration based on SEM images via deep learning
Journal of Materials Research and Technology · 2023
Yuan Gao, Zixuan Yu, Weiqiang Chen, Qian Yin, Jiangyu Wu, Wei Wang
Read original paper ↗ ·Accelerated multiscale mechanics modeling in a deep learning framework
Mechanics of Materials · 2023
Ashwini Gupta, Anindya Bhaduri, Lori L. Graham-Brady
Read original paper ↗ ·Deep Learning in Mechanical Metamaterials: From Prediction and Generation to Inverse Design
Advanced Materials · 2023
Xiaoyang Zheng, Xubo Zhang, Ta‐Te Chen, Ikumu Watanabe
Read original paper ↗ ·GRIDS-Net: Inverse shape design and identification of scatterers via geometric regularization and physics-embedded deep learning
Computer Methods in Applied Mechanics and Engineering · 2023
Siddharth Nair, Timothy Walsh, Greg W. Pickrell, Fabio Semperlotti
Read original paper ↗ ·Evaluating Generalized Feature Importance via Performance Assessment of Machine Learning Models for Predicting Elastic Properties of Materials
Computational Materials Science · 2023
Suvo Banik, Karthik Balasubramanian, Sukriti Manna, Sybil Derrible, Subramanian Sankaranarayananan
Read original paper ↗ ·Potential of machine learning approaches for predicting mechanical properties of spruce wood in the transverse direction
Journal of Wood Science · 2023
Shuoye Chen, Rei Shiina, Kazushi Nakai, Tatsuya Awano, Arata Yoshinaga, Junji Sugiyama
Read original paper ↗ ·Programmable multi-physical mechanics of mechanical metamaterials
Materials Science and Engineering R Reports · 2023
P K Sinha, Tanmoy Mukhopadhyay
Read original paper ↗ ·Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material properties in solid mechanics
Applied Mathematics and Mechanics · 2023
W. Wu, Mitchell Daneker, Matthew A. Jolley, Kevin T. Turner, Lu Lu
Read original paper ↗ ·Magnetosurgery: Principles, design, and applications
Smart Materials in Medicine · 2023
Daniil V. Kladko, Vladimir V. Vinogradov
Read original paper ↗ ·Machine learning dislocation density correlations and solute effects in Mg-based alloys
Scientific Reports · 2023
Henri Salmenjoki, Stefanos Papanikolaou, Dongfeng Shi, Damien Tourret, Carmen María Cepeda-Jiménez, María Teresa Pérez-Prado, Lasse Laurson, Mikko J. Alava
Read original paper ↗ ·Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review
Applied Mechanics Reviews · 2023
Hanxun Jin, Enrui Zhang, Horacio Dante Espinosa
Read original paper ↗ ·Can Artificial Intelligence Accelerate Fluid Mechanics Research?
Fluids · 2023
Dimitris Drikakis, Filippos D. Sofos
Read original paper ↗ ·Investigating deep learning model calibration for classification problems in mechanics
Mechanics of Materials · 2023
Saeed Mohammadzadeh, Peerasait Prachaseree, Emma Lejeune
Read original paper ↗ ·Exploiting the use of deep learning techniques to identify phase separation in self-assembled microstructures with localized graphene domains in epoxy blends
Computational Materials Science · 2023
Anuradha Kamble, Suihua He, Jonathan R. Howse, Carwyn Ward, Ian Hamerton
Read original paper ↗ ·Deep learning aided inverse design of the buckling-guided assembly for 3D frame structures
Journal of the Mechanics and Physics of Solids · 2023
Tianqi Jin, Xu Cheng, Shiwei Xu, Yuchen Lai, Yihui Zhang
Read original paper ↗ ·Machine learning–based estimation method for the mechanical response of composite cellular structures
Polymer Testing · 2023
Aoi Takagi, Ryo Ichikawa, Takeru Miyagawa, Jinlan Song, Akio Yonezu, Hideki Nagatsuka
Read original paper ↗ ·Artificial intelligence enhanced sensors - enabling technologies to next-generation healthcare and biomedical platform
Bioelectronic Medicine · 2023
Chan Wang, Tianyiyi He, Hong Zhou, Zixuan Zhang, Chengkuo Lee
Read original paper ↗ ·Artificial Intelligence in the Design of Innovative Metamaterials: A Comprehensive Review
International Journal of Precision Engineering and Manufacturing · 2023
Junho Song, JaeHoon Lee, Namjung Kim, Kyoungmin Min
Read original paper ↗ ·Prediction of Cutting Forces in Hard Turning Process Using Machine Learning Methods: A Case Study
Journal of Materials Engineering and Performance · 2023
Souâd Makhfi, Abdelhakim Dorbane, Fouzi Harrou, Ying Sun
Read original paper ↗ ·An accelerated strategy to characterize mechanical properties of polymer composites using the ensemble learning approach
Computational Materials Science · 2023
Hamed Esmaeili, Reza R. Rizvi
Read original paper ↗ ·Predicting the Fracture Propensity of Amorphous Silica Using Molecular Dynamics Simulations and Machine Learning
International Journal of Applied Mechanics · 2023
Jiahao Liu, Jingjie Yeo
Read original paper ↗ ·Untapped Potential of Deep Eutectic Solvents for the Synthesis of Bioinspired Inorganic–Organic Materials
Chemistry of Materials · 2023
Marcin Wysokowski, Rachel K. Luu, Sofia E. Arevalo, Eesha Khare, Witold Stachowiak, Michał Niemczak, Teofil Jesionowski, Markus J. Buehler
Read original paper ↗ ·A machine learning tool for future prediction of heat release capacity of in-situ flame retardant hybrid Mg(OH)2-Epoxy nanocomposites
Polymer Testing · 2023
Aurelio Bifulco, Angelo Casciello, Claudio Imparato, Stanislao Forte, Sabyasachi Gaan, Antonio Aronne, Giulio Malucelli
Read original paper ↗ ·From Nature to the Skies: Exploring Bio-Inspired Polymer Coatings for Aerospace Advancements
Preprints.org · 2023
Thinesh Sharma Balakrishnan, Mohamed Thariq Hameed Sultan, Farah Syazwani Shahar, Andrzej Łukaszewicz, Jerzy Jóźwik, Ain Umaira Md Shah, Rafał Grzejda
Read original paper ↗ ·Unleashing the Power of Artificial Intelligence in Materials Design
Materials · 2023
Silvia Badini, Stefano Regondi, Raffaele Pugliese
Read original paper ↗ ·Application of Machine Learning in Material Synthesis and Property Prediction
Materials · 2023
Guannan Huang, Yani Guo, Ye Chen, Zhengwei Nie
Read original paper ↗ ·Artificial Intelligence in Predicting Mechanical Properties of Composite Materials
Journal of Composites Science · 2023
Fasikaw Kibrete, Tomasz Trzepieciński, Hailu Shimels Gebremedhen, Dereje Engida Woldemichael
Read original paper ↗ ·IRMSwin-T: A lightweight shifted windows transformer based on inverted residual structure and residual multi-layer perceptron for rolling bearing fault diagnosis
Review of Scientific Instruments · 2023
Shanshan Ding, Renwen Chen, Hao Liu, Fei Liu, Junyi Zhang
Read original paper ↗ ·Machine learning-based prediction and interpretation of decomposition temperatures of energetic materials
Energetic Materials Frontiers · 2023
Junnan Wu, Siwei Song, Xiaolan Tian, Yi Wang, Xiujuan Qi
Read original paper ↗ ·Inverse design of multi-material gyroid structures made by additive manufacturing
International Journal of Mechanical Sciences · 2023
Ladpha Teawdeswan, Guoying Dong
Read original paper ↗ ·Prediction of complex strain fields in concrete using a deep learning approach
Construction and Building Materials · 2023
Pujin Wang, Jianzhuang Xiao, Chang Sun, Xu Wu, Long Li, Kequan Yu
Read original paper ↗ ·Recent progress on noble-free substrates for surface-enhanced Raman spectroscopy analysis
Coordination Chemistry Reviews · 2023
Ying Gu, Yonghui Li, Huimin Qiu, Yukun Yang, Qiyue Wu, Xuejing Fan, Yangyue Ding, Lunzhao Yi, Kun Ge, Yizhong Shen
Read original paper ↗ ·Cubically Symmetric Mechanical Metamaterials Projected from 4th-Dimensional Geometries Reveal High Specific Properties in Shear
ACS Applied Engineering Materials · 2023
Gabrielis Cerniauskas, Parvez Alam
Read original paper ↗ ·Differentiable graph-structured models for inverse design of lattice materials
Cell Reports Physical Science · 2023
Dominik Dold, Derek Aranguren van Egmond
Read original paper ↗ ·Multilevel resistive switching in thin oxide films for neuromorphic systems of artificial intillegence: simulation & experimental investigation
Scientific School Dynamics of Complex Networks and their Applications (DCNA) · 2023
Roman V. Tominov, Zakhar Vakulov, Victor Kazantsev, Chander Prakash, Ivan Ugryumov, Vladimir A. Smirnov
Read original paper ↗ ·Contemporary Role and Applications of Artificial Intelligence in Dentistry
F1000Research · 2023
Talal Bonny, Wafaa Al Nassan, Khaled Obaideen, Maryam Nooman Al Mallahi, Yara Mohammad, Hatem Mostafa El-Damanhoury
Read original paper ↗ ·Rapid design of top-performing metal-organic frameworks with qualitative representations of building blocks
npj Computational Materials · 2023
Yigitcan Comlek, Thang Duc Pham, Randall Q. Snurr, Wei Chen
Read original paper ↗ ·A deep neural multi-model ensemble (DNM2E) framework for modelling groundwater levels over Kerala using dynamic variables
Stochastic Environmental Research and Risk Assessment · 2023
Keerthana A V, Archana Nair
Read original paper ↗ ·Perspective: Machine Learning in Design for 3D/4D Printing
Journal of Applied Mechanics · 2023
Xiaohao Sun, Kun Zhou, Frédéric Demoly, Ruike Renee Zhao, Hang Jerry Qi
Read original paper ↗ ·Designing high elastic modulus magnesium-based composite materials via machine learning approach
Materials Today Communications · 2023
Zhihong Zhu, Wenhang Ning, Xuanyang Niu, Qiaoling Wang, Renhai Shi, Yuhong Zhao
Read original paper ↗ ·MeLM, a generative pretrained language modeling framework that solves forward and inverse mechanics problems
Journal of the Mechanics and Physics of Solids · 2023
Markus J. Buehler
Read original paper ↗ ·Prediction of shear strength in UHPC beams using machine learning-based models and SHAP interpretation
Construction and Building Materials · 2023
Meng Ye, Lifeng Li, Doo‐Yeol Yoo, Huihui Li, Cong Zhou, Xudong Shao
Read original paper ↗ ·AI‐Based Metamaterial Design for Wearables
Advanced Sensor Research · 2023
Defne Yigci, Abdollah Ahmadpour, Savaş Taşoğlu
Read original paper ↗ ·Neural Networks for Constitutive Modeling: From Universal Function Approximators to Advanced Models and the Integration of Physics
Archives of Computational Methods in Engineering · 2023
Johannes Dornheim, Lukas Morand, Hemanth Janarthanam Nallani, Dirk Helm
Read original paper ↗ ·New Artificial Intelligence System Based on Information Processing Technology
International Conference on Data Analytics, Computing and Artificial Intelligence (ICDACAI) · 2023
Ziye Tian
Read original paper ↗ ·Learning from nature by leveraging integrative biomateriomics modeling toward adaptive and functional materials
MRS Bulletin · 2023
Sofia E. Arevalo, Markus J. Buehler
Read original paper ↗ ·A machine learning approach for accelerated design of magnesium alloys. Part B: Regression and property prediction
Journal of Magnesium and Alloys · 2023
M. Ghorbani, Mario Boley, Philip N. H. Nakashima, N. Birbilis
Read original paper ↗ ·Characterization and optimization of mechanical properties in design materials using convolutional neural networks and particle swarm optimization
Asian Journal of Civil Engineering · 2023
Mohamad Wijayanuddin Ali, Mohammad Hussein
Read original paper ↗ ·