Papers citing Machine-learned and codified synthesis parameters of oxide materials
Retrosynthesis from transforms to predictive sustainable chemistry and nanotechnology: a brief tutorial review
Green Chemistry · 2023
Alicja Mikołajczyk, Uladzislau Zhdan, Sylvain Antoniotti, Adam Smoliński, Karolina Jagiełło, Piotr Skurski, Moussab Harb, Tomasz Puzyn, Jarosław Polański
Read original paper ↗ ·Search without Coverage: Exploration Blind Spots in AI-Guided Materials Discovery
Journal of Computational and Data-Driven Materials Engineering · 2023
Claire Martin, Julien Robert, Sophie Bernard
Read original paper ↗ ·Transcription between human-readable synthetic descriptions and machine-executable instructions: an application of the latest pre-training technology
Chemical Science · 2023
Zheni Zeng, Yi-Chen Nie, Ning Ding, Qian-Jun Ding, Wei-Ting Ye, Cheng Hong Yang, Maosong Sun, E Weinan, Rong Xia Zhu, Zhiyuan Liu
Read original paper ↗ ·Transformation of aluminosilicate materials into high value zeolites
Queensland University of Technology · 2023
Andrea Lucia Rocha Hidalgo
Read original paper ↗ ·Chemistry-Informed Machine Learning for Polymer Electrolyte Discovery
ACS Central Science · 2023
Gabriel Bradford, Jeffrey Lopez, Jurğis Ruža, Michael A. Stolberg, Richard Osterude, Jeremiah A. Johnson, Rafael Gómez‐Bombarelli, Yang Shao‐Horn
Read original paper ↗ ·Generating, Managing, and Mining Big Data in Zeolite Simulations
Venue not supplied by source · 2023
Daniel Schwalbe‐Koda, Rafael Gómez‐Bombarelli
Read original paper ↗ ·Interpretable Machine Learning Enabled Inorganic Reaction Classification and Synthesis Condition Prediction
Chemistry of Materials · 2023
Christopher J. Karpovich, Elton Pan, Zach Jensen, Elsa Olivetti
Read original paper ↗ ·Prediction of lattice thermal conductivity with two-stage interpretable machine learning
Chinese Physics B · 2023
Jinlong Hu, Yuting Zuo, Yuzhou Hao, Guoyu Shu, Yang Wang, Minxuan Feng, Xuejie Li, Xiaoying Wang, Jun Sun, Xiangdong Ding, Zhibin Gao, Guimei Zhu, Baowen Li
Read original paper ↗ ·Deep language models for interpretative and predictive materials science
APL Machine Learning · 2023
Yiwen Hu, Markus J. Buehler
Read original paper ↗ ·The role of machine learning in carbon neutrality: Catalyst property prediction, design, and synthesis for carbon dioxide reduction
eScience · 2023
Zhuo Wang, Zhehao Sun, Hang Yin, Honghe Wei, Zicong Peng, Yoong Xin Pang, Guohua Jia, Haitao Zhao, Cheng Heng Pang, Zongyou Yin
Read original paper ↗ ·Data-driven-aided strategies in battery lifecycle management: Prediction, monitoring, and optimization
Energy storage materials · 2023
Liqianyun Xu, Feng Wu, Renjie Chen, Li Li
Read original paper ↗ ·Designing materials acceleration platforms for heterogeneous CO2 photo(thermal)catalysis
Matter · 2023
Andrew Wang, Carlota Bozal‐Ginesta, Sai Govind Hari Kumar, Alán Aspuru‐Guzik, Geoffrey Alan Ozin
Read original paper ↗ ·Fatigue database of additively manufactured alloys
Scientific Data · 2023
Zian Zhang, Zhiping Xu
Read original paper ↗ ·Achieving Digital Catalysis: Strategies for Data Acquisition, Storage and Use
Angewandte Chemie International Edition · 2023
Clara Patricia Marshall, Julia Schumann, Annette Trunschke
Read original paper ↗ ·Achieving Digital Catalysis: Strategies for Data Acquisition, Storage and Use
Angewandte Chemie · 2023
Clara Patricia Marshall, Julia Schumann, Annette Trunschke
Read original paper ↗ ·Functional Material Systems Enabled by Automated Data Extraction and Machine Learning
Advanced Functional Materials · 2023
Payam Kalhor, Nicole Jung, Stefan Bräse, Christof Wöll, Manuel M. Tsotsalas, Pascal Friederich
Read original paper ↗ ·Natural Language Processing Techniques for Advancing Materials Discovery: A Short Review
International Journal of Precision Engineering and Manufacturing-Green Technology · 2023
Joo Hyuk Lee, Myeonghun Lee, Kyoungmin Min
Read original paper ↗ ·Precursor recommendation for inorganic synthesis by machine learning materials similarity from scientific literature
Science Advances · 2023
Tanjin He, Haoyan Huo, Christopher J. Bartel, Zheren Wang, Kevin Cruse, Gerbrand Ceder
Read original paper ↗ ·Identify novel elements of knowledge with word embedding
PLoS ONE · 2023
Deyun Yin, Zhao Yu Wu, Kazuki Yokota, Kuniko Matsumoto, Sotaro Shibayama
Read original paper ↗ ·Material Property Prediction by Integrating Literature-mining and Crossed Feature Selection
International Conference on Information Systems Engineering (ICISE) · 2023
Rui Zhang, Jiawang Zhang, Yuexing Han, Qiaochuan Chen
Read original paper ↗ ·Fatigue database of complex metallic alloys
Scientific Data · 2023
Zian Zhang, Haoxuan Tang, Zhiping Xu
Read original paper ↗ ·Antennas and Propagation Research From Large-Scale Unstructured Data With Machine Learning: A review and predictions
IEEE Antennas and Propagation Magazine · 2023
Young‐Ok Cha, Achintha Avin Ihalage, Yang Hao
Read original paper ↗ ·A literature-mining method of integrating text and table extraction for materials science publications
Computational Materials Science · 2023
Rui Zhang, Jiawang Zhang, Qiaochuan Chen, Bing Wang, Yi Liu, Quan Qian, Deng Pan, Jinhua Xia, Yinggang Wang, Yuexing Han
Read original paper ↗ ·A Model Ensemble Approach Enables Data-Driven Property Prediction for Chemically Deconstructable Thermosets in the Low-Data Regime
ACS Central Science · 2023
Yasmeen S. AlFaraj, Somesh Mohapatra, Peyton Shieh, Keith E. L. Husted, Douglas G. Ivanoff, Evan M. Lloyd, Julian C. Cooper, Yutong Dai, Avni P. Singhal, Jeffrey S. Moore, Nancy R. Sottos, Rafael Gómez‐Bombarelli, Jeremiah A. Johnson
Read original paper ↗ ·EXSCLAIM!: Harnessing materials science literature for self-labeled microscopy datasets
Patterns · 2023
Eric Schwenker, Weixin Jiang, Trevor Spreadbury, Nicola Ferrier, Oliver Cossairt, Maria K. Y. Chan
Read original paper ↗ ·Optimizing the growth of vertically aligned carbon nanotubes by literature mining and high-throughput experiments
New Carbon Materials · 2023
Zhang-dan GAO, Zhong-Hai Ji, Lili Zhang, Dai‐Ming Tang, Meng-Ke Zou, Rui-Hong Xie, Shaokang Liu, Chang Liu, Chang Liu
Read original paper ↗ ·Alloy synthesis and processing by semi-supervised text mining
npj Computational Materials · 2023
Weiren Wang, Xue Feng Jiang, Shaohan Tian, Pei Liu, Turab Lookman, Yanjing Su, Jianxin Xie
Read original paper ↗ ·Extracting the Synthetic Route of Pd-Based Catalysts in Methanol Steam Reforming from the Scientific Literature
Journal of Chemical Information and Modeling · 2023
Shuyuan Li, Yunjiang Zhang, Zhaolin Fang, Kong Meng, Rui Tian, Hong He, Shaorui Sun
Read original paper ↗ ·Snowball 2.0: Generic Material Data Parser for ChemDataExtractor
Journal of Chemical Information and Modeling · 2023
Qingyang Dong, Jacqueline M. Cole
Read original paper ↗ ·Prediction of hydrogen generation from perhydro-dibenzyltoluene empowered with machine learning
International Journal of Hydrogen Energy · 2023
Ahsan Ali, Muhammad Adnan Khan, Hoimyung Choi
Read original paper ↗ ·A rule-free workflow for the automated generation of databases from scientific literature
npj Computational Materials · 2023
Luke P. J. Gilligan, Matteo Cobelli, Valentin Taufour, Stefano Sanvito
Read original paper ↗ ·Text Mining the Literature to Inform Experiments and Rationalize Impurity Phase Formation for BiFeO3
Chemistry of Materials · 2023
Kevin Cruse, Viktoriia Baibakova, Maged Abdelsamie, Kootak Hong, Christopher J. Bartel, Amalie Trewartha, Anubhav Jain, Carolin M. Sutter‐Fella, Gerbrand Ceder
Read original paper ↗ ·Document-Level Iterative Entity and Relation Extraction for Materials Scientific Literature
Lecture notes in computer science · 2024
Qiqi Geng, Jinguo You, Huayi Guo, Xingrui Huang, Jingmei Tao, Jianhong Yi
Read original paper ↗ ·Supervised Machine Learning-Based Prediction of Hydrogen Storage Classes Utilizing Dibenzyltoluene as an Organic Carrier
Molecules · 2024
Ahsan Ali, Muhammad Adnan Khan, Hoimyung Choi
Read original paper ↗ ·High-Throughput Extraction of Phase–Property Relationships from Literature Using Natural Language Processing and Large Language Models
Integrating materials and manufacturing innovation · 2024
Luca Montanelli, Vineeth Venugopal, Elsa Olivetti, Marat I. Latypov
Read original paper ↗ ·Evolution of artificial intelligence as a modern technology in advanced cancer therapy
Journal of Drug Delivery Science and Technology · 2024
Mohammad Sameer Khan, Mohammad Yahya Alshahrani, Shadma Wahab, Garima Gupta, Prashant Kesharwani
Read original paper ↗ ·Accelerating Computational Materials Discovery with Machine Learning and Cloud High-Performance Computing: from Large-Scale Screening to Experimental Validation
Journal of the American Chemical Society · 2024
Chi Chen, Dan Thien Nguyen, Shannon Lee, Nathan Baker, Ajay Singh Karakoti, Linda Lauw, Craig Owen, Karl Todd Mueller, Brian A. Bilodeau, Vijayakumar Murugesan, Matthias Troyer
Read original paper ↗ ·Life Cycle Inventory Availability: Status and Prospects for Leveraging New Technologies
ACS Sustainable Chemistry & Engineering · 2024
Mark Mba Wright, Eric C. D. Tan, Qingshi Tu, António A. Martins, Abhijeet G. Parvatker, Yuan Yao, Aydın K. Sunol, Raymond L. Smith
Read original paper ↗ ·Machine Learning‐Based Assessment and Optimization of Electrode Materials for Supercapacitors
Venue not supplied by source · 2024
Srikanta Moharana, Bibhuti Bhusan Sahu, Jayakishan K. Meher, Rozalin Nayak, Ram Naresh Mahaling, Karthik Dhandapani, Kalim Deshmukh
Read original paper ↗ ·MPNTEXT: An Interactive Platform for Automatically Extracting Metal-Polyphenol Networks and Their Applications from Scientific Literature
Journal of Chemical Information and Modeling · 2024
Zihui Huang, Xinyi Li, Andi Li, Yuhang Yang, Liqiang He, Zhiwen Zhang, Siwei Wu, Yang Wang, Shuting Cai, Yan He, Xujie Liu
Read original paper ↗ ·Data-driven analysis of text-mined seed-mediated syntheses of gold nanoparticles
Digital Discovery · 2024
Sanghoon Lee, Kevin Cruse, Samuel P. Gleason, A. Paul Alivisatos, Gerbrand Ceder, Anubhav Jain
Read original paper ↗ ·A Generative Adversarial Network Approach to Predict Nanoparticle Size in Microfluidics
ACS Biomaterials Science & Engineering · 2024
Sara Mihandoost, Sima Rezvantalab, Roger M. Pallares, Volkmar Schulz, Fabian M. Kiessling
Read original paper ↗ ·Comprehensive overview of machine learning applications in MOFs: from modeling processes to latest applications and design classifications
Journal of Materials Chemistry A · 2024
Yutong Liu, Yawen Dong, Hua Wu
Read original paper ↗ ·Data-driven atomistic modeling of crystalline and glassy solid-state electrolytes
Chemical Communications · 2025
Rongkang Zhou, Kun Luo, Qi An
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 ↗ ·How to accelerate the inorganic materials synthesis: from computational guidelines to data-driven method?
National Science Review · 2025
Yilei Wu, Xiangyang Li, Rong Guo, Rui Xu, Ming‐Gang Ju, Jinlan Wang
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 ↗ ·Rapid Adaptation of Chemical Named Entity Recognition Using Few-Shot Learning and LLM Distillation
Journal of Chemical Information and Modeling · 2025
Yue Zhang, Dionisios G. Vlachos, Dongxia Liu, Hui Fang
Read original paper ↗ ·Emerging Microelectronic Materials by Design: Navigating Combinatorial Design Space with Scarce and Dispersed Data
Accounts of Materials Research · 2025
Hengrui Zhang, Alexandru Bogdan Georgescu, Suraj Yerramilli, Christopher J. Karpovich, Daniel W. Apley, Elsa Olivetti, James M. Rondinelli, Wei Chen
Read original paper ↗ ·Language models for materials discovery and sustainability: Progress, challenges, and opportunities
Progress in Materials Science · 2025
Zongrui Pei, Junqi Yin, Jiaxin Zhang
Read original paper ↗ ·