Papers citing Semi-supervised machine-learning classification of materials synthesis procedures
Advances in materials informatics: a review
Journal of Materials Science · 2024
Dawn Sivan, K. Satheesh Kumar, Aziman Abdullah, Veena Raj, Izan Izwan Misnon, Seeram Ramakrishna, Rajan Jose
Read original paper ↗ ·Accelerating materials language processing with large language models
Communications Materials · 2024
Jaewoong Choi, Byungju Lee
Read original paper ↗ ·Prediction of heavy-section ductile iron fracture toughness based on machine learning
Scientific Reports · 2024
Liang Song, Hongcheng Zhang, Junxing Zhang, Hai Yang Guo
Read original paper ↗ ·Large language model enhanced corpus of CO2 reduction electrocatalysts and synthesis procedures
Scientific Data · 2024
Xueqing Chen, Yang Gao, Ludi Wang, Wenjuan Cui, Jiamin Huang, Yi Du, Bin Wang
Read original paper ↗ ·Exploring solvation structure and transport behavior for rational design of advanced electrolytes for next generation of lithium batteries
Applied Physics Reviews · 2024
Xiaozhao Liu, Volodymyr A. Koverga, Thi Thu Hoai Nguyen, Anh T. Ngo, Tao Li
Read original paper ↗ ·Overcoming Language Barrier for Scientific Studies via Unsupervised Literature Learning: Case Study on Solar Cell Materials Prediction
Solar RRL · 2024
Lei Zhang, Mu He, Endai Huang, Xiaokang Ma, Jiaxue You, Alex K.‐Y. Jen, Shengzhong Frank Liu
Read original paper ↗ ·Usage of clustering algorithms for automating route planning in transportation routing tasks
Системи обробки інформації · 2024
О. С. Чорна, П. Ю. Дідик, С.В. Тітов, O. Titova
Read original paper ↗ ·Synthesizability of materials stoichiometry using semi-supervised learning
Matter · 2024
Jidon Jang, Juhwan Noh, Lan Zhou, Geun Ho Gu, John M. Gregoire, Yousung Jung
Read original paper ↗ ·A critical reflection on attempts to machine-learn materials synthesis insights from text-mined literature recipes
Faraday Discussions · 2024
Wenhao Q. Sun, Nicholas David
Read original paper ↗ ·Reverse characterization prediction of diamond Schottky barrier power devices using machine learning: Predicting breakdown voltage and Baliga figure of merit
Diamond and Related Materials · 2024
Ali Abdellah Abdelrahman, Shinya Ohmagari, 剛 吉武
Read original paper ↗ ·Machine-Learning-Assisted Materials Discovery from Electronic Band Structure
Journal of Chemical Information and Modeling · 2024
Prashant Sinha, Ablokit Joshi, Rik Dey, Shikhar Misra
Read original paper ↗ ·Concluding remarks: Faraday Discussion on data-driven discovery in the chemical sciences
Faraday Discussions · 2024
Andrew Ian Cooper
Read original paper ↗ ·Construction and application of materials database under data-driven research paradigm
Chinese Science Bulletin (Chinese Version) · 2024
Junjie Feng, Kun Zhou, Muchen Li, Xinjiang Wang, Lijun Zhang
Read original paper ↗ ·Impact of data bias on machine learning for crystal compound synthesizability predictions
Machine Learning Science and Technology · 2024
Ali Davariashtiyani, Busheng Wang, Samad Hajinazar, Eva Zurek, Sara Kadkhodaei
Read original paper ↗ ·The role of artificial intelligence in materials science: a review
Elsevier eBooks · 2024
Dhanya Lakshmi, Rithuraj Nambiar, Parveen Kumar
Read original paper ↗ ·Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility
Machine Learning Science and Technology · 2024
Ryan M. Jacobs, Lane E. Schultz, Aristana Scourtas, K. J. Schmidt, Owen Price-Skelly, Will Engler, Ian T Foster, Ben J. Blaiszik, Paul M. Voyles, Dane D. Morgan
Read original paper ↗ ·Theoretical investigation of structure stabilities, electronic and thermodynamic properties of 2D Mo-based MXene Mon+1Xn (X = C, N and n = 1, 2, 3)
Materials Science and Engineering B · 2024
Shabir Ali, Xinhua Wang, Zuhra Tayyab, M.A.K. Yousaf Shah, Iftikhar Hussain, Khuloud A. Alibrahim, Muhammad Tayyab, Sajid Rauf
Read original paper ↗ ·Modeling Techniques
SpringerBriefs in applied sciences and technology · 2025
Arnold Ano-os Lubguban, Arnold C. Alguno, Roberto M. Malaluan, Gerard G. Dumancas
Read original paper ↗ ·Solid-state synthesizability predictions using positive-unlabeled learning from human-curated literature data
Digital Discovery · 2025
Vincent Chung, Aron Walsh, David J. Payne
Read original paper ↗ ·SynCoTrain: a dual classifier PU-learning framework for synthesizability prediction
Digital Discovery · 2025
Sasan Amariamir, Janine George, Philipp Benner
Read original paper ↗ ·Exploring the development of electrocatalysts through an automated comprehensive literature review using NLP
Journal of Alloys and Compounds Communications · 2025
Na Qin, Lei Liu, Lai Wei, Haibiao Chen
Read original paper ↗ ·Machine Learning-Based Computational Design Methods for High-Entropy Alloys
High Entropy Alloys & Materials · 2025
Yan Ming Zhao, J. Y. Zhang, Peter Kaehuei Liaw, Tao Yang
Read original paper ↗ ·English Verb Morphological Adaptive Clustering Based on Semantic Feature Mining
International Journal of High Speed Electronics and Systems · 2025
Jiwen Yin, Na Yu
Read original paper ↗ ·Applications of natural language processing and large language models in materials discovery
npj Computational Materials · 2025
Xue Feng Jiang, Weiren Wang, Shaohan Tian, Hao Wang, Turab Lookman, Yanjing Su
Read original paper ↗ ·Artificial intelligence technology in materials selection, device engineering and parameter optimisation for triboelectric nanogenerator
Materials Today Communications · 2025
Ashok Kumar Swami, Deepak Kumar Verma, Richa Soni, Dweipayan Goswami
Read original paper ↗ ·NiFe2O4 and CuFe2O4 nanofibers for the ppm-level ethanol and acetone classification: A comparison
Materials Chemistry and Physics · 2025
Nguyen Van Hoang, Phan Hong Phuoc, Nguyen Van Hieu
Read original paper ↗ ·Machine learning-driven alloy digital design for hydrogen storage: a review
Digital Twin · 2025
Tianqi Liu, Lufeng Xue, Bo Ci Cheng, Yu Zhao, Bang Dou, Marcelo Paredes, Lu-Kai Song
Read original paper ↗ ·Exploration of Lithium-Ion Conductors Based on Local Coordination Environments Using Crystallographic Site Fingerprints
Journal of the American Chemical Society · 2025
Songjia Kong, Naoki Matsui, Satoshi Hori, Masaaki Hirayama, Kazuhiro John Mori, Takashi Kei SAITO, Masaaki Hirayama, Masaaki Hirayama
Read original paper ↗ ·State‐of‐the‐Art Machine Learning Technology for Sustainable Lithium Battery Cathode Design: A Perspective
Advanced Energy Materials · 2025
Adil Saleem, Leon L. Shaw, Zhiqian Chen, Wei Lai
Read original paper ↗ ·Accelerated data-driven materials science with the Materials Project
Nature Materials · 2025
Matthew K. Horton, Patrick Huck, Ruoxi Yang, Jason M. Munro, Shyam Dwaraknath, Alex M. Ganose, Ryan Kingsbury, Mingjian Wen, Jimmy X. Shen, Tyler S. Mathis, Aaron D. Kaplan, Karlo Berket, Janosh Riebesell, Janine George, Andrew Rosen, Evan Walter Clark Spotte‐Smith, Matthew J. McDermott, Orion Cohen, Alexander Dunn, Matthew C. Kuner, Gian‐Marco Rignanese, Guido Petretto, David Waroquiers, Sinéad M. Griffin, Jeffrey B. Neaton, D. C. Chrzan, Mark Asta, Geoffroy Hautier, Shreyas Cholia, Gerbrand Ceder, Shyue Ping Ong, Anubhav Jain, Kristin Aslaug Persson
Read original paper ↗ ·Artificial intelligence in materials science and engineering: Current landscape, key challenges, and future trajectories
Composite Structures · 2025
Iman Peivaste, Salim Belouettar, Francesco Mercuri, Nicholas Fantuzzi, Hamidreza Dehghani, Razie Izadi, Halliru Ibrahim, Jakub Lengiewicz, Mael Belouettar-Mathis, Kouider Bendine, Ahmed Makradi, Martin Horsch, Peter Klein, M. Hachemi, Heinz A. Preisig, Yacine Rezgui, Natalia Konchakova, Ali Daouadji
Read original paper ↗ ·Developing machine learning for heterogeneous catalysis with experimental and computational data
Nature Reviews Chemistry · 2025
Carlota Bozal‐Ginesta, Sergio Pablo‐García, Changhyeok Choi, Albert Tarancón, Alán Aspuru‐Guzik
Read original paper ↗ ·Artificial Intelligence for Materials Discovery, Development, and Optimization
ACS Nano · 2025
Benediktus Madika, Aditi Saha, Chaeyul Kang, Batzorig Buyantogtokh, Joshua Agar, Chris M. Wolverton, Peter W. Voorhees, P. B. Littlewood, Sergei V. Kalinin, Seungbum Hong
Read original paper ↗ ·Annotated textual dataset PV600 of perovskite bandgaps for information extraction from literature
Scientific Data · 2025
Matilda Sipilä, Farrokh Mehryary, Sampo Pyysalo, Filip Ginter, Milica Todorović
Read original paper ↗ ·Pressure-dependent structural stability and enhanced electronic properties of Cubic Ti 2 C MXene for unlocking energy and photonic applications
International Journal of Modern Physics C · 2025
Maymounah N. Alharthi, Xinhua Wang, Shabir Ali, Sohail Ahmad, Noor Rehman, Shakeel Shakeel, Muhammad Ibrar, Ali El‐Rayyes
Read original paper ↗ ·A survey of AI-supported materials informatics
Computer Science Review · 2025
Sanjay Chakraborty, Jonas Björk, Martin Dahlqvist, Johanna Rosen, Fredrik Heintz
Read original paper ↗ ·Recent advances in machine learning-driven discovery of alloy electrocatalysts for hydrogen evolution reaction
Chinese Chemical Letters · 2025
Na Qin, Wenxin Guo, Fangxiu Li, Houfeng Zhang, Houfeng Zhang, Hong Liu, Chang Zhang, Chang Zhang, Lipiao Bao, Lei Liu, Muneerah Amer Alomar, Siqi Zhao, Jian Zhang, Xing Lu
Read original paper ↗ ·Language Models Enable Data-Augmented Synthesis Planning for Inorganic Materials
ACS Applied Materials & Interfaces · 2025
Thorben Prein, Elton Pan, Janik Jehkul, Steffen Weinmann, Elsa Olivetti, Jennifer L. M. Rupp
Read original paper ↗ ·Inline quality grading of commercial lithium-ion battery manufacturing via data-efficient learning and transferable assessment
Energy & Environmental Science · 2026
Chen Liang, Shengyu Tao, Chunqiu Xia, Xinghao Huang, Hang Hu, Rui Wang, Daoyi Dong, Ziyang Lyu, Guangmin Zhou, Huadong Mo
Read original paper ↗ ·MetMINE: a generative large language model-based source-tracked multi-pass framework for metallic materials information extraction
Digital Discovery · 2026
Xin Wang, Anshu Raj, Matthew Luebbe, Haiming Wen, Shuozhi Xu, Kun Lu
Read original paper ↗ ·Artificial intelligence for energy materials research: From classical machine learning to large models
ENGINEERING Energy · 2026
Mingxi Jiang, Jie Zhou, Yanggang An, Zhengran Lin, Menghao Yang
Read original paper ↗ ·Prompt Engineering Accelerates the Data‐Driven Discovery of Photocatalysts via an LLM‐Based Model Ensemble Strategy
Advanced Science · 2026
Dianyuan Li, Xichen Sun, Shaohua Sun, Runzhou Wang, Miaomiao Zhang, Meng Xiao, Yue Wang, Yuezhou Zhang
Read original paper ↗ ·Text Mining of CVD Synthesis Recipes for 2D Materials
Advanced Materials · 2026
Ang‐Yu Lu, Rui Chen, Aijia Yao, Meng-Chi Chen, Ji Hoon Park, Tianyi Zhang, Xudong Zheng, Nannan Mao, Jiangtao Wang, Zhien Wang, Tomás Palacios, Jing Kong
Read original paper ↗ ·Roadmap for High‐Throughput Ceramic Materials Synthesis and Discovery for Batteries
Advanced Energy Materials · 2026
Jesse J. Hinricher, Katarzyna P. Sokol, Philipp Simons, Kun Joong Kim, Michael Foshey, Yunsheng Tian, Thorben Prein, Lincoln J. Miara, Elsa Olivetti, Wojciech Matusik, Jennifer L. M. Rupp
Read original paper ↗ ·Quantitative analysis of operating conditions and performance trends in CO2 capture from large-scale literature
Chemical Engineering Journal Advances · 2026
So Yun Jeong, Kyuri Choi, Jeongho Choi, Kwanghwi Kim, Hong Woo Lee, Byung Chul Yeo
Read original paper ↗ ·Machine Learning‐Based Inverse Design for Functional Materials: Methods, Challenges, and Engineering Applications
Advanced Functional Materials · 2026
Weihao Lin, Liuchao Jin, Zhifei Jiang, Mingjing Cai, Zhihui Lai, Daniil Yurchenko, Bo Yan, Shengxi Zhou, Kostya S. Novoselov, Wei‐Hsin Liao, Shitong Fang
Read original paper ↗ ·Harnessing Artificial Intelligence (AI) for a greener future: a review of AI advancements in green chemistry, chemical processes and sustainable materials
Applied Intelligence · 2026
Ahmed M. Elkhatat, Shaheen A. Al‐Muhtaseb
Read original paper ↗ ·A relaxation-free training framework for task-oriented modular potentials in multi-principal element alloys
Science China Technological Sciences · 2026
Funi Zhong, Fanfan Wang, Jiarui Zeng, Siqi Shi, Wenqiang Xie, Pu Yu
Read original paper ↗ ·Entropy-based materialistic and mechanistic insights for zinc ion battery applications
Coordination Chemistry Reviews · 2026
Muhammad Asim, Sanath Kumar, Yen‐Pei Fu
Read original paper ↗ ·Toward autonomous chemical discovery: agentic AI in organic synthesis and nanochemistry
Results in Engineering · 2026
Boppudi Hari Babu, Pullaiah Chowdary Vutla, Jagadeesh Mahimaluru, Bryce Ke Jun Chong, Srinivasulu Kambam
Read original paper ↗ ·