Papers citing An informatics approach to transformation temperatures of NiTi-based shape memory alloys
High-Dimensional Materials and Process Optimization Using Data-Driven Experimental Design with Well-Calibrated Uncertainty Estimates
Integrating materials and manufacturing innovation · 2017
Julia Ling, Maxwell Hutchinson, Erin Antono, Sean Paradiso, Bryce Meredig
Read original paper ↗ ·An materials informatics approach to Ni-based single crystal superalloys lattice misfit prediction
Computational Materials Science · 2017
Xue Feng Jiang, Haiqing Yin, Cong Zhang, Rui-Jie Zhang, Kai-Qi Zhang, Zhenghua Deng, Guoquan Liu, Xuanhui Qu
Read original paper ↗ ·Building data-driven models with microstructural images: Generalization and interpretability
Materials Discovery · 2017
Julia Ling, Maxwell Hutchinson, Erin Antono, Brian DeCost, Elizabeth A. Holm, Bryce Meredig
Read original paper ↗ ·Identifying models of dielectric breakdown strength from high-throughput data via genetic programming
Scientific Reports · 2017
Fenglin Yuan, Tim Mueller
Read original paper ↗ ·Doping Effects of Point Defects in Shape Memory Alloys
Acta Materialia · 2018
Yuanchao Yang, Dezhen Xue, Ruihao Yuan, Yumei Zhou, Turab Lookman, Xiangdong Ding, Xiaobing Ren, Jun Sun
Read original paper ↗ ·Importance of Feature Selection in Machine Learning and Adaptive Design for Materials
Springer series in materials science · 2018
Prasanna V. Balachandran, Dezhen Xue, James P. Theiler, John Hogden, James E. Gubernatis, Turab Lookman
Read original paper ↗ ·Materials informatics
Journal of Intelligent Manufacturing · 2018
Seeram Ramakrishna, Tong‐Yi Zhang, Wencong Lu, Quan Qian, Jonathan Sze Choong Low, Jeremy H. Yune, Daren Zong Loong Tan, Stéphane Bressan, Stefano Sanvito, Surya R. Kalidindi
Read original paper ↗ ·Multi-objective Optimization for Materials Discovery via Adaptive Design
Scientific Reports · 2018
Abhijith Gopakumar, Prasanna V. Balachandran, Dezhen Xue, James E. Gubernatis, Turab Lookman
Read original paper ↗ ·Effects of Wire Electro-Discharge Machining Process Parameters on the Machined Surface of Ti50Ni49Co1 Shape Memory Alloy
Silicon · 2018
Hargovind Soni, S. Narendranath, Motagondanahalli Rangarasaiah Ramesh
Read original paper ↗ ·Tunability of martensitic behavior through coherent nanoprecipitates and other nanostructures
Acta Materialia · 2018
Samuel Temple Reeve, Karthik Guda Vishnu, Alexis Belessiotis‐Richards, Alejandro H. Strachan
Read original paper ↗ ·Machine leaning aided study of sintered density in Cu-Al alloy
Computational Materials Science · 2018
Zhenghua Deng, Haiqing Yin, Xue Feng Jiang, Cong Zhang, Kaiqi Zhang, Tong Zhang, Bin Xu, Qingjun Zheng, Xuanhui Qu
Read original paper ↗ ·Two-way design of alloys for advanced ultra supercritical plants based on machine learning
Computational Materials Science · 2018
Xiaobing Hu, Jincheng Wang, Yanyan Wang, Junjie Li, Zhijun Wang, Yingying Dang, Yuefeng Gu
Read original paper ↗ ·Patchy Particle Model of the Hierarchical Self-Assembly of π-Conjugated Optoelectronic Peptides
The Journal of Physical Chemistry B · 2018
Rachael A. Mansbach, Andrew L. Ferguson
Read original paper ↗ ·The materials data ecosystem: Materials data science and its role in data-driven materials discovery
Chinese Physics B · 2018
Hai-Qing Yin, Xue Jiang, Guo-Quan Liu, Sharon Elder, Bin Xu, Qing-Jun Zheng, Xuan-Hui Qu
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 ↗ ·Materials informatics: From the atomic-level to the continuum
Acta Materialia · 2019
Jeffrey M. Rickman, Turab Lookman, Sergei V. Kalinin
Read original paper ↗ ·A novel approach to predict green density by high-velocity compaction based on the materials informatics method
International Journal of Minerals Metallurgy and Materials · 2019
Kai-Qi Zhang, Haiqing Yin, Xue Feng Jiang, Xiuqin Liu, Fei He, Zhenghua Deng, Dil Faraz Khan, Qingjun Zheng, Xuanhui Qu
Read original paper ↗ ·Active learning in materials science with emphasis on adaptive sampling using uncertainties for targeted design
npj Computational Materials · 2019
Turab Lookman, Prasanna V. Balachandran, Dezhen Xue, Ruihao Yuan
Read original paper ↗ ·Machine learning assisted design of high entropy alloys with desired property
Acta Materialia · 2019
Cheng Wen, Yan Zhang, Changxin Wang, Dezhen Xue, Yang Bai, Stoichko Antonov, Lan-Hong Dai, Turab Lookman, Yanjing Su
Read original paper ↗ ·Systems Approaches to Materials Design: Past, Present, and Future
Annual Review of Materials Research · 2019
Raymundo Arróyave, David L. McDowell
Read original paper ↗ ·A two-stage predicting model for γ′ solvus temperature of L12-strengthened Co-base superalloys based on machine learning
Intermetallics · 2019
Jinxin Yu, Shun Guo, Yuechao Chen, Jiajia Han, Yong Lu, Qingshan Jiang, Cuiping Wang, Xingjun Liu
Read original paper ↗ ·Data analysis of multi-dimensional thermophysical properties of liquid substances based on clustering approach of machine learning
Chemical Physics Letters · 2019
Gota Kikugawa, Yuta Nishimura, Koji Shimoyama, Taku Ohara, Tomonaga Okabe, Fumio S. Ohuchi
Read original paper ↗ ·Machine Learning Techniques for the Segmentation of Tomographic Image Data of Functional Materials
Frontiers in Materials · 2019
Orkun Furat, Mingyan Wang, Matthias Neumann, Lukas Petrich, Matthias Weber, Carl E. Krill, Volker Schmidt
Read original paper ↗ ·Accelerated Search for BaTiO3‐Based Ceramics with Large Energy Storage at Low Fields Using Machine Learning and Experimental Design
Advanced Science · 2019
Ruihao Yuan, Yuan Tian, Dezhen Xue, Deqing Xue, Deqing Xue, Deqing Xue, Yumei Zhou, Xiangdong Ding, Jun Feng Sun, Turab Lookman
Read original paper ↗ ·Virtual Issue on Machine-Learning Discoveries in Materials Science
Chemistry of Materials · 2019
Anton O. Oliynyk, Jillian M. Buriak
Read original paper ↗ ·Nanocalorimetry and ab initio study of ternary elements in CuZr-based shape memory alloy
Acta Materialia · 2019
Yucong Miao, Ruben Villarreal, Anjana Talapatra, Raymundo Arróyave, Joost J. Vlassak
Read original paper ↗ ·Assessing the Frontier: Active Learning, Model Accuracy, and Multi-objective Materials Discovery and Optimization
arXiv (Cornell University) · 2019
Zachary del Rosario, Matthias Rupp, Yoolhee Kim, Erin Antono, Julia Ling
Read original paper ↗ ·A machine-learning approach to predicting and understanding the properties of amorphous metallic alloys
Materials & Design · 2019
Jie Xiong, San‐Qiang Shi, Tong‐Yi Zhang
Read original paper ↗ ·Phase prediction in high entropy alloys with a rational selection of materials descriptors and machine learning models
Acta Materialia · 2019
Yan Zhang, Cheng Wen, Changxin Wang, Stoichko Antonov, Dezhen Xue, Yang Bai, Yanjing Su
Read original paper ↗ ·Wire electro spark machining and characterization studies on Ti50Ni49Co1, Ti50Ni45Co5 and Ti50Ni40Co10 alloys
Materials Research Express · 2019
Hargovind Soni, P M Mashinni
Read original paper ↗ ·A progressive learning method for predicting the band gap of ABO 3 perovskites using an instrumental variable
Journal of Materials Chemistry C · 2020
Changjiao Li, Hua Hao, Ben Xu, Guanghui Zhao, Lihao Chen, Shujun J. Zhang, Hanxing Liu
Read original paper ↗ ·Bayesian Global Optimization applied to the design of shape-memory alloys
Elsevier eBooks · 2020
Dezhen Xue, Yuan Tian, Ruihao Yuan, Turab Lookman
Read original paper ↗ ·Cost-effective materials discovery: Bayesian optimization across multiple information sources
Materials Horizons · 2020
Henry Herbol, Matthias Poloczek, Paulette Clancy
Read original paper ↗ ·Dramatically Enhanced Combination of Ultimate Tensile Strength and Electric Conductivity of Alloys via Machine Learning Screening
Acta Materialia · 2020
Hongtao Zhang, Huadong Fu, Xingqun He, Changsheng Wang, Lei Jiang, Long‐Qing Chen, Jianxin Xie
Read original paper ↗ ·Learning with Small Databases
Synthesis lectures on materials and optics · 2020
Ghanshyam Pilania, Prasanna V. Balachandran, James E. Gubernatis, Turab Lookman
Read original paper ↗ ·Navigating the design space of inorganic materials synthesis using statistical methods and machine learning
Dalton Transactions · 2020
Erick J. Braham, Rachel D. Davidson, Mohammed Al‐Hashimi, Raymundo Arróyave, Sarbajit Banerjee
Read original paper ↗ ·Accelerating the development of multi-component Cu-Al-based shape memory alloys with high elastocaloric property by machine learning
Computational Materials Science · 2020
Xinpeng Zhao, Haiyou Huang, Cheng Wen, Yanjing Su, Ping Qian
Read original paper ↗ ·Corrosion rate prediction and influencing factors evaluation of low-alloy steels in marine atmosphere using machine learning approach
Science and Technology of Advanced Materials · 2020
Luchun Yan, Yupeng Diao, Zhaoyang Lang, Kewei Gao
Read original paper ↗ ·Physics-informed machine learning for composition-process-property alloy design: shape memory alloy demonstration
arXiv (Cornell University) · 2020
Sen Liu, Branden B. Kappes, Behnam Amin-Ahmadi, Othmane Benafan, Xiaoli Zhang, Aaron P. Stebner
Read original paper ↗ ·Data-Based Methods for Materials Design and Discovery: Basic Ideas and General Methods
Synthesis lectures on materials and optics · 2020
Ghanshyam Pilania, Prasanna V. Balachandran, James E. Gubernatis, Turab Lookman
Read original paper ↗ ·Development of database and information management system for data-driven materials design
Scientia Sinica Technologica · 2020
Xuemei Liu, XiaoYan SONG, Kai Guo, Dong Liu, Fei MAO
Read original paper ↗ ·Estimating DFT calculated voltage using machine learning regression models
Materials Today Proceedings · 2020
Rapela R. Maphanga, Tshepiso Mokoena, Mahlatse Ratsoma
Read original paper ↗ ·Gallium–Boron–Phosphide ($$\hbox {GaBP}_{2}$$): a new III–V semiconductor for photovoltaics
Journal of Materials Science · 2020
Upendra Kumar, Sanjay Nayak, Soubhik Chakrabarty, Satadeep Bhattacharjee, Seung-Cheol Lee
Read original paper ↗ ·Combinatorial Synthesis and High-Throughput Characterization of Microstructure and Phase Transformation in Ni–Ti–Cu–V Quaternary Thin-Film Library
Engineering · 2020
Naila Al Hasan, Huilong Hou, Suchismita Sarkar, Sigurd Thienhaus, Apurva Mehta, Alfred Ludwig, Ichiro Takeuchi
Read original paper ↗ ·Machine Learning in Materials Discovery: Confirmed Predictions and Their Underlying Approaches
Annual Review of Materials Research · 2020
James E. Saal, Anton O. Oliynyk, Bryce Meredig
Read original paper ↗ ·Machine learning of mechanical properties of steels
Science China Technological Sciences · 2020
Jie Xiong, Tong‐Yi Zhang, San‐Qiang Shi
Read original paper ↗ ·A strategy combining machine learning and multiscale calculation to predict tensile strength for pearlitic steel wires with industrial data
Scripta Materialia · 2020
Xue Feng Jiang, Baorui Jia, Guofei Zhang, Cong Zhang, Xin Wang, Ruijie Zhang, Haiqing Yin, Xuanhui Qu, Yong Hui Song, Lan Su, Zhenli Mi, Lei Hu, Han Ma
Read original paper ↗ ·Optimization of thermal conductivity of UO2–Mo composite with continuous Mo channel based on finite element method and machine learning
International Journal of Heat and Mass Transfer · 2020
Biaojie Yan, Rui Gao, Pengchuang Liu, Pengcheng Zhang, Liang Cheng
Read original paper ↗ ·Machine learning assisted multi-objective optimization for materials processing parameters: A case study in Mg alloy
Journal of Alloys and Compounds · 2020
Yifei Chen, Yuan Tian, Yumei Zhou, Daqing Fang, Xiangdong Ding, Jun Feng Sun, Dezhen Xue
Read original paper ↗ ·Predicting the Parabolic Rate Constants of High-Temperature Oxidation of Ti Alloys Using Machine Learning
Oxidation of Metals · 2020
Somesh Kr. Bhattacharya, Ryoji Sahara, Takayuki Narushima
Read original paper ↗ ·