Papers citing Materials discovery and design using machine learning
The onset temperature (Tg) of As Se1 glasses transition prediction: A comparison of topological and regression analysis methods
Computational Materials Science · 2017
Yue Liu, Tianlu Zhao, Guang Yang, Wangwei Ju, Siqi Shi
Read original paper ↗ ·Substantiation of the structure theory of design of technological machines and devices
Technology audit and production reserves · 2017
Л. В. Лось, Savelii Kukharets, Nataliya Tsyvenkova, Anna Нolubenko, Marina Tereshchuk
Read original paper ↗ ·Challenges for Theory and Computation
Computation · 2017
Karlheinz Schwarz
Read original paper ↗ ·Materials genome: research progress, challenges and outlook
Scientia Sinica Chimica · 2017
Yunqi Li, Lunyang Liu, Wenduo Chen, Lijia An
Read original paper ↗ ·Substatiation of quantitative criteria of structural parts and units manufacturability evaluation
Technology audit and production reserves · 2017
Yaroslav Yarosh, Nataliya Tsyvenkova, Savelii Kukharets, Anna Нolubenko, Л. В. Лось
Read original paper ↗ ·A Mathematical Framework for Deep Learning in Elastic Source Imaging
SIAM Journal on Applied Mathematics · 2018
Jaejun Yoo, Abdul Wahab, Jong Chul Ye
Read original paper ↗ ·FS4RVDD: A Feature Selection Algorithm for Random Variables with Discrete Distribution
Communications in computer and information science · 2018
Fiorella Cravero, Santiago A. Schustik, María Jimena Martínez, Mónica F. Díaz, Ignacio Ponzoni
Read original paper ↗ ·Towards the systematic crystallisation of molecular ionic cocrystals: insights from computed crystal form landscapes
Faraday Discussions · 2018
Sharmarke Mohamed, Ahmad A. Alwan, Tomislav Friščić, Andrew J. Morris, Mihails Arhangelskis
Read original paper ↗ ·Understanding structural adaptability: a reactant informatics approach to experiment design
Molecular Systems Design & Engineering · 2018
Rosalind J. Xu, Jacob H. Olshansky, Philip Adler, Yongjia Huang, Matthew D. Smith, Matthias Zeller, Joshua Schrier, Alexander J. Norquist
Read original paper ↗ ·Using neural networks to predict the low curves and processing maps of TNM-B1
Computer Methods in Materials Science. · 2018
Johan Andreas Stendal, Aliakbar Emdadi, Irina Sizova, Markus� Bambach
Read original paper ↗ ·Modeling and characterization of mechanical properties in laser powder bed fusion additive manufactured Inconel 718
Digital Collections of Colorado (Colorado State University) · 2018
Senthamilaruvi Moorthy
Read original paper ↗ ·Ridge regression for predicting elastic moduli and hardness of calcium aluminosilicate glasses
Materials Research Express · 2018
Yifan Deng, Huidan Zeng, Yejia Jiang, Guorong Chen, Jianding Chen, Luyi Sun
Read original paper ↗ ·A living foundry for Synthetic Biological Materials: A synthetic biology roadmap to new advanced materials
Synthetic and Systems Biotechnology · 2018
Rosalind Le Feuvre, Nigel Shaun Scrutton
Read original paper ↗ ·Predictive and generative machine learning models for photonic crystals
Nanophotonics · 2018
Thomas Christensen, Charlotte Loh, Stjepan Picek, Domagoj Jakobović, Li Jing, Sophie Fisher, Vladimir Čeperić, John D. Joannopoulos, Marin Soljacic A
Read original paper ↗ ·Comparative study of various cathodes for lithium ion batteries using an enhanced Peukert capacity model
Journal of Power Sources · 2018
Ryan O'Malley, Lin Liu, Christopher Depcik
Read original paper ↗ ·Applying machine learning to accelerate new materials development
Zhongguo kexue. Wulixue Lixue Tianwenxue · 2018
Wei Wu, Qiang Sun
Read original paper ↗ ·Interface Characterization and Control of 2D Materials and Heterostructures
Advanced Materials · 2018
Xiaolong Liu, Mark C. Hersam
Read original paper ↗ ·Rapid Evaluation of Dynamic Electronic Disorder in Molecular Semiconductors
The Journal of Physical Chemistry C · 2018
Alessandro Landi, Alessandro Troisi
Read original paper ↗ ·Machine Learning Enabled Computational Screening of Inorganic Solid Electrolytes for Suppression of Dendrite Formation in Lithium Metal Anodes
ACS Central Science · 2018
Zeeshan Ahmad, Tian Xie, Chinmay Maheshwari, Jeffrey C. Grossman, Venkatasubramanian Viswanathan
Read original paper ↗ ·Hunting for Organic Molecules with Artificial Intelligence: Molecules Optimized for Desired Excitation Energies
ACS Central Science · 2018
Masato Sumita, Xiufeng Yang, Shinsuke Ishihara, Ryo Tamura, Koji Tsuda
Read original paper ↗ ·Predicting the effective thermal conductivities of composite materials and porous media by machine learning methods
International Journal of Heat and Mass Transfer · 2018
Han Wei, Shuaishuai Zhao, Qingyuan Rong, Hua Bao
Read original paper ↗ ·Design of efficient blue phosphorescent bottom emitting light emitting diodes by machine learning approach
Organic Electronics · 2018
Muhammad Asyraf Bin Janai, Kai Lin Woon, Chee Seng Chan
Read original paper ↗ ·Towards Simulation-Data Science – A Case Study on Material Failures
IEEE International Conference on Data Science and Advanced Analytics (DSAA) · 2018
Holger Trittenbach, Martin Gauch, Klemens Böhm, Katrin Schulz
Read original paper ↗ ·Modelling feasibility constraints for materials design: Application to inverse crystallographic texture problem
Computational Materials Science · 2018
Jaimyun Jung, Jae Ik Yoon, Seong‐Jun Park, Jun‐Yun Kang, Gwang Lyeon Kim, Yi Hwa Song, Sung Taek Park, Kyeong Won Oh, Hyoung Seop Kim
Read original paper ↗ ·Machine learning band gap and alignment of nitride semiconductors
arXiv (Cornell University) · 2018
Yang Huang, Fei Wang, Changyou Yu, Yuhuai Liu, Chong Li, Chunyao Niu, Yu Jia
Read original paper ↗ ·Committee machine that votes for similarity between materials
IUCrJ · 2018
Duong‐Nguyen Nguyen, Tien-Lam Pham, Viet-Cuong Nguyen, Tuan-Dung Ho, Truyen Tran, KEISUKE G. TAKAHASHI, Hieu‐Chi Dam
Read original paper ↗ ·Important Descriptors and Descriptor Groups of Curie Temperatures of Rare-earth Transition-metal Binary Alloys
Journal of the Physical Society of Japan · 2018
Hieu‐Chi Dam, Viet-Cuong Nguyen, Tien-Lam Pham, Anh Tuan Nguyen, Kiyoyuki Terakura, Takashi Miyake, Hiori Kino
Read original paper ↗ ·Combining electronic and structural features in machine learning models to predict organic solar cells properties
Materials Horizons · 2018
Daniele Padula, Jack D. Simpson, Alessandro Troisi
Read original paper ↗ ·Applications of Knowledge Technology in Construction Industry
International Conference on Emerging eLearning Technologies and Applications (ICETA) · 2018
Peter Mésároš, Tomáš Mandičák, Marcel Behún, Jana Smetanková
Read original paper ↗ ·The material influence factors on the actual capacity of lithium ion battery
Chinese Science Bulletin (Chinese Version) · 2018
Ning Chen, Bo Wang, Yang Liu, Lijun Wang, Yang Li, Fushen Li, Hailei Zhao
Read original paper ↗ ·Synthesis of Lithium-ion Conducting Polymers Designed by Machine Learning-based Prediction and Screening
Chemistry Letters · 2018
Kan Hatakeyama‐Sato, Toshiki Tezuka, Yoshinori Nishikitani, Hiroyuki Nishide, Kenichi Oyaizu
Read original paper ↗ ·Thermal performance of a novel ultrasonic evaporator based on machine learning algorithms
Applied Thermal Engineering · 2018
Jitian Song, Wei Tian, Xiaofei Xu, Yening Wang, Zhanyong Li
Read original paper ↗ ·3D Deep Learning with voxelized atomic configurations for modeling atomistic potentials in complex solid-solution alloys
arXiv (Cornell University) · 2018
Rahul Singh, Aayush Sharma, Onur Rauf Bingöl, Aditya Balu, Ganesh Balasubramanian, Duane D. Johnson, Soumik Sarkar
Read original paper ↗ ·Predictive Analytics for Biomineralization Peptide Binding Affinity
BioNanoScience · 2018
Jose Isagani B. Janairo
Read original paper ↗ ·Rationalizing Perovskite Data for Machine Learning and Materials Design
The Journal of Physical Chemistry Letters · 2018
Qichen Xu, Zhenzhu Li, Miao Liu, Wan‐Jian Yin
Read original paper ↗ ·Machine learning of ab-initio energy landscapes for crystal structure predictions
Computational Materials Science · 2018
Shreyas J. Honrao, Bryan E. Anthonio, Rohit Ramanathan, Joshua J. Gabriel, Richard G. Hennig
Read original paper ↗ ·Impact of dataset uncertainties on machine learning model predictions: the example of polymer glass transition temperatures
Modelling and Simulation in Materials Science and Engineering · 2018
Anurag Jha, Anand R. Chandrasekaran, Chiho Kim, Rampi Ramprasad
Read original paper ↗ ·Machine learning in materials design and discovery: Examples from the present and suggestions for the future
Physical Review Materials · 2018
James E. Gubernatis, Turab Lookman
Read original paper ↗ ·Artificial neural networks and vector regression models for prediction of lattice constants of half-Heusler compounds
Materials Research Express · 2018
Rashid Ahmad, Aqsa Gul, Nasir Mehmood
Read original paper ↗ ·Recent Advances in Metallic Glass Nanostructures: Synthesis Strategies and Electrocatalytic Applications
Advanced Materials · 2018
Jinyang Li, Gustavo Doubek, Lyndsey McMillon‐Brown, André D. Taylor
Read original paper ↗ ·Optimization of Machine Learning in Predicting Fracture Behaviour of Materials in AI
Türk bilgisayar ve matematik eğitimi dergisi · 2018
Gaurav Joshi
Read original paper ↗ ·Band gap and band alignment prediction of nitride-based semiconductors using machine learning
Journal of Materials Chemistry C · 2019
Yang Huang, Changyou Yu, Weiguang Chen, Yuhuai Liu, Chong Li, Chunyao Niu, Fei Wang, Yu Jia
Read original paper ↗ ·Bulk and surface DFT investigations of inorganic halide perovskites screened using machine learning and materials property databases
Physical Chemistry Chemical Physics · 2019
Deepak Jain, Suryanaman Chaube, Prerna Khullar, Sriram Goverapet Srinivasan, Beena Rai
Read original paper ↗ ·Deformation Correlations and Machine Learning: Microstructural inference and crystal plasticity predictions
Venue not supplied by source · 2019
Michail Tzimas
Read original paper ↗ ·First-principles study of alkali-metal intercalation in disordered carbon anode materials
Journal of Materials Chemistry A · 2019
Jianxing Huang, Gábor Cśanyi, Jinbao Zhao, Jun Jie Cheng, Volker L. Deringer
Read original paper ↗ ·Hammett neural networks: prediction of frontier orbital energies of tungsten–benzylidyne photoredox complexes
Chemical Science · 2019
Alexander M. Chang, Jessica G. Freeze, Víctor S. Batista
Read original paper ↗ ·Machine learning for renewable energy materials
Journal of Materials Chemistry A · 2019
Geun Ho Gu, Juhwan Noh, I. P. Kim, Yousung Jung
Read original paper ↗ ·Mathematical Strategies for Design Optimization of Multiphase Materials
Mathematical Problems in Engineering · 2019
Rick Catania, Abdalla Diraz, Dominic Maier, Armani Tagle, Pınar Acar
Read original paper ↗ ·Nanoinformatics, and the big challenges for the science of small things
Nanoscale · 2019
Amanda Susan Barnard, Benyamin Motevalli, Amanda J. Parker, Julia Melisande Theresa Agatha Fischer, Christopher A. Feigl, George Opletal
Read original paper ↗ ·Rationalizing the interphase stability of Li|doped-Li 7 La 3 Zr 2 O 12 via automated reaction screening and machine learning
Journal of Materials Chemistry A · 2019
Bo Liu, Jiong Yang, Hongliang Yang, Caichao Ye, Yuanqing Mao, Jiping Wang, Siqi Shi, Jihui Yang, Wenqing Zhang
Read original paper ↗ ·