Papers citing Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning
Paradigm Shift: The Promise of Deep Learning in Molecular Systems Engineering and Design
Frontiers in Chemical Engineering · 2021-06-08
Abdulelah S. Alshehri, Fengqi You
Read original paper ↗ ·Graphical Gaussian Process Regression Model for Aqueous Solvation Free Energy Prediction of Organic Molecules in Redox Flow Battery
eScholarship (California Digital Library) · 2021-06-15
Peiyuan Gao, Xiu Yang, Yuhang Tang, Muqing Zheng, Amity Anderson, Vijayakumar Murugesan, Aaron Hollas, Wei Wang
Read original paper ↗ ·Computationally Enabled Sensors
ACS Sensors · 2021-06-25
Michael J. Sailor
Read original paper ↗ ·A method for predicting mechanical properties of composite microstructure with reduced dataset based on transfer learning
Composite Structures · 2021-08-05
Yangjian Xu, Huanbo Weng, Xiaozhe Ju, Hongshi Ruan, Junjun Chen, Chenyu Nan, Jing Ming Guo, Lihua Liang
Read original paper ↗ ·Matrix Manipulation of Directly‐Synthesized PbS Quantum Dot Inks Enabled by Coordination Engineering
Advanced Functional Materials · 2021-08-06
Fei Li, Yang Liu, Guozheng Shi, Wei Chen, Renjun Guo, Dong Liu, Yaohong Zhang, Yongjie Wang, Xing Meng, Xuliang Zhang, You Lv, Wei Deng, Qing Zhang, Yao Shi, Yifan Chen, Kai Wang, Qing Shen, Zeke Liu, Peter Müller‐Buschbaum, Wanli Ma
Read original paper ↗ ·Accelerating materials discovery with Bayesian optimization and graph deep learning
Materials Today · 2021-10-01
Yunxing Zuo, Mingde Qin, Chi Chen, Weike Ye, Xiangguo Li, Jian Luo, Shyue Ping Ong
Read original paper ↗ ·Innovative Materials Science via Machine Learning
Advanced Functional Materials · 2021-10-04
Chaochao Gao, Xin Min, Minghao Fang, Tianyi Tao, Xiaohong Zheng, Yangai Liu, Xiaowen Wu, Zhaohui Huang
Read original paper ↗ ·Symmetry-aware recursive image similarity exploration for materials microscopy
npj Computational Materials · 2021-10-08
Tri N. M. Nguyen, Yichen Guo, Shuyu Qin, Kylie S. Frew, Ruijuan Xu, Joshua Agar
Read original paper ↗ ·AtomSets as a hierarchical transfer learning framework for small and large materials datasets
npj Computational Materials · 2021-10-22
Chi Chen, Shyue Ping Ong
Read original paper ↗ ·Machine learning for multiscale modeling in computational molecular design
Current Opinion in Chemical Engineering · 2021-10-25
Abdulelah S. Alshehri, Fengqi You
Read original paper ↗ ·Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data
Nature Communications · 2021-11-15
Vishu Gupta, Kamal Kumar Choudhary, Francesca Tavazza, Carelyn E. Campbell, Wei‐keng Liao, Alok Choudhary, Ankit Agrawal
Read original paper ↗ ·DeepTMC: A deep learning platform to targeted design doped transition metal compounds
Energy storage materials · 2021-11-15
Zhilong Wang, Yanqiang Han, Junfei Cai, Sicheng Wu, Jinjin Li
Read original paper ↗ ·Structural, electronic, elastic, phonon and thermoelectric properties of Heusler-structured intermetallic HfCu2In: Using density functional theory
Physica B Condensed Matter · 2021-12-22
Aditi Jain, Deepika Shrivastava, Rajnish Kurchania
Read original paper ↗ ·Molecular representations for machine learning applications in chemistry
International Journal of Quantum Chemistry · 2021-12-27
Shampa Raghunathan, U. Deva Priyakumar
Read original paper ↗ ·Mechanistic artificial intelligence (mechanistic-AI) for modeling, design, and control of advanced manufacturing processes: Current state and perspectives
Journal of Materials Processing Technology · 2021-12-30
Mojtaba Mozaffar, Shuheng Liao, Xiaoyu Xie, Sourav Saha, Chanwook Park, Jian Feng Cao, Wing Kam Liu, Zhengtao Gan
Read original paper ↗ ·A small-data-driven model for predicting adsorption properties in polymeric thin films
Chemical Communications · 2022-01-01
Uiyoung Han, Taegyu Kang, Jongho Im, Jinkee Hong
Read original paper ↗ ·Application of transfer learning to predict diffusion properties in metal–organic frameworks
Molecular Systems Design & Engineering · 2022-01-01
Yunsung Lim, Jihan Kim
Read original paper ↗ ·Contrastive representation learning of inorganic materials to overcome lack of training datasets
Chemical Communications · 2022-01-01
Gyoung S. Na, Hyun Woo Kim
Read original paper ↗ ·High-cycle fatigue S-N curve prediction of steels based on a transfer learning-guided convolutional neural network
Journal of Materials Informatics · 2022-01-01
Xiaolu Wei, Chenchong Wang, Zixi Jia, Wei Xu
Read original paper ↗ ·Scientific Validation in Materials AI—A Critical Survey of Conceptual Approaches: A Review Study
Journal of Artificial Intelligence for Materials Science · 2022-01-01
Daniel Fischer, Laura Meier, Thomas Braun, Stefan Koch, Felix Roth
Read original paper ↗ ·The Illusion of Generalization: A Critique of Random Train-Test Splitting in Small-Crystal Property Prediction
Journal of Computational and Data-Driven Materials Engineering · 2022-01-01
Claire Martin, Julien Robert, Sophie Bernard, Antoine Girard
Read original paper ↗ ·光谱域编码的压缩光谱测量技术
Infrared and Laser Engineering · 2022-01-01
徐亦静 Xu Yijing, 吴志鹏 Wu Zhipeng, 王琦龙 Wang Qilong
Read original paper ↗ ·Mapping Oxidation and Wafer Cleaning to Device Characteristics Using Physics-Assisted Machine Learning
ACS Omega · 2022-01-03
Sparsh Pratik, Po-Ning Liu, Jun Ota, Yen-Liang Tu, Guan-Wen Lai, Ya-Wen Ho, Zheng-Kai Yang, Tejender Singh Rawat, Albert Shihchun Lin
Read original paper ↗ ·Computer Simulations of Deep Eutectic Solvents: Challenges, Solutions, and Perspectives
International Journal of Molecular Sciences · 2022-01-07
Dmitry A. Tolmachev, N. V. Lukasheva, Ruslan R. Ramazanov, Victor M. Nazarychev, Natalia I. Borzdun, Igor V. Volgin, Maria V. Andreeva, Artyom D. Glova, Sofia D. Melnikova, Alexey Yu. Dobrovskiy, Steven A. Silber, Sergey V. Larin, Rafael Maglia de Souza, Mauro C. C. Ribeiro, Sergey V. Lyulin, Mikko Karttunen
Read original paper ↗ ·An Easy, Simple, and Accessible Web-based Machine Learning Platform, SimPL-ML
Integrating materials and manufacturing innovation · 2022-01-21
Seunghun Jang, Gyoung S. Na, Jung‐Ho Lee, Jung‐Ho Shin, Hyun Woo Kim, Hyunju Chang
Read original paper ↗ ·MgO/CaO Nanocomposite Facilitates Economical Production of d -Fructose and d -Allulose Using Glucose and Its Response Prediction Using a DNN Model
Industrial & Engineering Chemistry Research · 2022-02-02
Senthil Murugan Arumugam, Dalwinder Singh, Sangeeta Mahala, Bhawana Devi, Sandeep Kumar, Sunaina Jakhu, Sasikumar Elumalai
Read original paper ↗ ·Deep transfer learning correlation study of electronic and spin properties in buckled III–V monolayers
Physica E Low-dimensional Systems and Nanostructures · 2022-02-04
Alireza Kokabi, Mohammadreza Bahramy, Shoeib Babaee Touski
Read original paper ↗ ·Transfer (machine) learning approaches coupled with target data augmentation to predict the mechanical properties of concrete
Machine Learning with Applications · 2022-02-09
Emily Ford, Kailasnath Maneparambil, Aditya Kumar, Gaurav Sant, Narayanan Neithalath
Read original paper ↗ ·Predicting Diffusion Coefficients of Binary and Ternary Supercritical Water Mixtures via Machine and Transfer Learning with Deep Neural Network
Industrial & Engineering Chemistry Research · 2022-02-25
Xiao Feng Zhao, Tengfei Luo, Hui Jin
Read original paper ↗ ·Recent advances in the application of machine-learning algorithms to predict adsorption energies
Trends in Chemistry · 2022-03-01
Liang Cao
Read original paper ↗ ·Quantifying transfer learning synergies in infinite-layer and perovskite nitrides, oxides, and fluorides
Journal of Physics Condensed Matter · 2022-03-02
Armin Sahinovic, Benjamin Geisler
Read original paper ↗ ·Deep learning approach for chemistry and processing history prediction from materials microstructure
Scientific Reports · 2022-03-16
Amir Abbas Kazemzadeh Farizhandi, Omar Betancourt, Mahmood Mamivand
Read original paper ↗ ·Extensible Structure-Informed Prediction of Formation Energy with improved accuracy and usability employing neural networks
Computational Materials Science · 2022-03-17
Adam M. Krajewski, Jonathan W. Siegel, Jinchao Xu, Zi‐Kui Liu
Read original paper ↗ ·CrysXPP: An explainable property predictor for crystalline materials
npj Computational Materials · 2022-03-18
Kishalay Das, Bidisha Samanta, Pawan Goyal, Seung‐Cheol Lee, Satadeep Bhattacharjee, Niloy Ganguly
Read original paper ↗ ·Revealing geometrically necessary dislocation density from electron backscatter patterns via multi-modal deep learning
Ultramicroscopy · 2022-03-29
Qi Lu, Jiayi Wu, Shilong Liu, Shiqi Zhang, Xiaorong Cai, Wei Li, Jun Jiang, Xuejun Jin
Read original paper ↗ ·Text Mining for Energy Materials
Journal of Research in Science and Engineering · 2022-03-31
Read original paper ↗ ·Machine learning predicted magnetic entropy change using chemical descriptors across a large compositional landscape
Computational Materials Science · 2022-04-04
Huseyin Ucar, Durga Paudyal, Kamal Kumar Choudhary
Read original paper ↗ ·Deep dive into machine learning density functional theory for materials science and chemistry
Physical Review Materials · 2022-04-05
Lenz Fiedler, Karan Shah, Michael Bußmann, Attila Cangi
Read original paper ↗ ·Recent advances and applications of deep learning methods in materials science
npj Computational Materials · 2022-04-05
Kamal Kumar Choudhary, Brian DeCost, Chi Chen, Anubhav Jain, Francesca Tavazza, Ryan Cohn, Cheol Woo Park, Alok Choudhary, Ankit Agrawal, Simon J. L. Billinge, Elizabeth A. Holm, Shyue Ping Ong, Chris M. Wolverton
Read original paper ↗ ·Data-Driven Multi-Scale Modeling and Optimization for Elastic Properties of Cubic Microstructures
Integrating materials and manufacturing innovation · 2022-04-06
Mahmudul Hasan, Yuwei Mao, Kamal Kumar Choudhary, Francesca Tavazza, Alok Choudhary, Ankit Agrawal, Pınar Acar
Read original paper ↗ ·Design and prediction of metal organic framework-based mixed matrix membranes for CO2 capture via machine learning
Cell Reports Physical Science · 2022-04-21
Jian Guan, Tan Huang, Wei Liu, Fan Feng, Susilo Japip, Jiali Li, Ji Wu, Xiaonan Wang, Sui Zhang
Read original paper ↗ ·Data‐Driven Materials Innovation and Applications
Advanced Materials · 2022-04-22
Zhuo Wang, Zhehao Sun, Hang Yin, Xinghui Liu, Jinlan Wang, Haitao Zhao, Cheng Heng Pang, Tao Wu, Shuzhou Li, Zongyou Yin, Xue‐Feng Yu
Read original paper ↗ ·Big Data Seismology
Reviews of Geophysics · 2022-04-23
Stephen Arrowsmith, Daniel Taylor Trugman, J. MacCarthy, Karianne J. Bergen, David Lumley, Maria Beatrice Magnani
Read original paper ↗ ·Transfer learning using attentions across atomic systems with graph neural networks (TAAG)
The Journal of Chemical Physics · 2022-04-25
Adeesh Kolluru, Nima Shoghi, Muhammed Shuaibi, Siddharth Goyal, Abhishek Das, C. Lawrence Zitnick, Zachary W. Ulissi
Read original paper ↗ ·Studying Complex Evolution of Hyperelastic Materials under External Field Stimuli using Artificial Neural Networks with Spatiotemporal Features in a Small‐Scale Dataset
Advanced Materials · 2022-04-28
Songlin Yu, Haiyang Chai, Yuqi Xiong, Ming Kang, Chengzhen Geng, Yu Liu, Yanqiu Chen, Yaling Zhang, Qian Zhang, Changlin Li, Hao Wei, Yuhang Zhao, Fengmei Yu, Ai Lu
Read original paper ↗ ·Predicting stress–strain curves using transfer learning: Knowledge transfer across polymer composites
Materials & Design · 2022-04-29
Ziyang Zhang, Qingyang Liu, Dazhong Wu
Read original paper ↗ ·Using Multi-Resolution Data to Accelerate Neural Network Training in Scientific Applications
IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid) · 2022-05-01
Kewei Wang, Sunwoo Lee, J. T. Balewski, Alex Sim, P. Nugent, Ankit Agrawal, Alok Choudhary, Kesheng John Wu, Wei‐keng Liao
Read original paper ↗ ·Effect of reducible and irreducible search space representations on adaptive design efficiency: a case study on maximizing packing fraction for solid rocket fuel propellant simulations
ChemRxiv · 2022-05-10
Sterling G. Baird, Jason R. Hall, Taylor D. Sparks
Read original paper ↗ ·High-dimensional Bayesian optimization of 23 hyperparameters over 100 iterations for an attention-based network to predict materials property: A case study on CrabNet using Ax platform and SAASBO
Computational Materials Science · 2022-05-19
Sterling G. Baird, Marianne Liu, Taylor D. Sparks
Read original paper ↗ ·High cycle fatigue S-N curve prediction of steels based on transfer learning guided long short term memory network
International Journal of Fatigue · 2022-06-02
Xiaolu Wei, Chi Zhang, Siyu Han, Zixi Jia, Chenchong Wang, Wei Xu
Read original paper ↗ ·