Chemical Reaction Prediction

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24 papers8 papers in the last four weeks, against 1 the four weeks before. 0.1% of all new papers.

OPRD-Imp: a dataset of experimentally observed impurities and side products in multi-step pharmaceutical syntheses
Nov 5, 2026Heejeong Kim, Seonbin Kim, Jihwan Kim +6Chemical Reaction Prediction
Department of Chemistry and Nanoscience, Ewha Womans University, Seoul, 03760, South Korea · Department of Chemistry, Kookmin University, Seoul, 02707, South Korea · Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA +2
Cloudra: Geometric Reasoning and Scientific Validation for Autonomous Reaction Mechanism Exploration
Nov 2, 2026Chengyi Yang, Qianxin Zhou, Yang LiChemical Reasoning in LLMs Chemical Reaction Prediction
College of Chemistry and Pharmaceutical Engineering, Changsha University of Science and Technology, Changsha 410114, China · State Key Laboratory of Photocatalysis on Energy and Environment, College of Chemistry, Fuzhou University, Fuzhou 350002, China
Shock Loading Accesses Reaction Pathways beyond Accelerated Thermolysis
Oct 30, 2026Mingjie Wen, Jiahe Han, Zihan Zhou +4Materials Science Molecular Dynamics Simulation
State Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, P. R. China
Reaction precedents extend retrosynthetic prediction beyond training coverage
Oct 29, 2026Jiaxing Sun, Xuli Shen, Jiang Wu +17Retrosynthesis Chemical Reaction Prediction
Shanghai Artificial Intelligence Laboratory · Fudan University · Peking University +5
All Paths All at Once: A Quantum Monte Carlo and Neural Committor Approach to Reaction Pathway Search
Oct 29, 2026Chien-Chai ChangChemical Reaction Prediction
Department of Engineering and System Science, National Tsing Hua University (NTHU), Hsinchu City, 300044, Taiwan
Distillation, Self-Training, and the Fragility of Learned Chemical Reasoning
Oct 16, 2026Anagha Aneesh, Sebastian Ibarraran, Frank Hu +2Chemical Reasoning in LLMs Chemical Reaction Prediction
Stanford University
Synthetic reaction data from transformation rules for graph-to-sequence pretraining in biodegradation pathway prediction
Oct 14, 2026Irsyaad Rijwan, Liam Brydon, Aidan Jared +1Chemical Reaction Prediction Synthetic Data Pretraining
School of Computer Science, University of Auckland, Auckland, New Zealand. · enviPath Limited, Auckland, New Zealand.
Elucidating the Space of Enzymatic Reaction: A Unified Benchmark and Pretrained Model
Oct 8, 2026Yutong Hu, Tianming Huang, Yanbo Zhao +6Sequence-to-Sequence Models Chemical Reaction Prediction
Shanghai Jiao Tong University · Shanghai Artificial Intelligence Laboratory · The University of Sydney
Neural Petri flows for chemical reactions
Oct 6, 2026Jose Eduardo Escrig Molina, Daniel ProbstAI-Assisted Scientific Research Petri Nets
Bioinformatics Group Bioprocess Engineering Group Wageningen Unversity Wageningen, the Netherlands
FREA: A Multi-Source Expert Benchmark for Reaction Feasibility Verification
Oct 5, 2026Botao Yu, Bo Zhou, Daniel Adu-Ampratwum +7LLM Evaluation AI-Assisted Scientific Research
Department of Computer Science and Engineering, The Ohio State University · Department of Pharmaceutical Sciences, University of Illinois Chicago · College of Pharmacy, The Ohio State University +3
Learning Transferable Reaction Mechanisms from Visual Chemical Knowledge
Sep 27, 2026Yujian Yuan, Jiaxin Xu, Xin Cai +4Visual Representation Learning Transfer Learning
The Hong Kong University of Science and Technology · The Chinese University of Hong Kong · University of Edinburgh
Mechanistic Reaction Prediction via Discrete Flow Matching on Graph-Structured Electron Occupation
Aug 27, 2026Nguyen Xuan-Vu, Octavian Susanu, Daniel Armstrong +1Chemical Reaction Prediction Discrete Flow Matching
École Polytechnique Fédérale de Lausanne (EPFL) · National Centre of Competence in Research (NCCR) Catalysis
Role-Aware Morgan Fingerprints for Reaction Yield Prediction
Aug 26, 2026Chinmay Mirji, Prashant Shekhar, Foram Madiyar +1Chemical Reaction Prediction Molecular Property Prediction
Aerospace Engineering Embry-Riddle Aeronautical University Daytona Beach, Florida · Mathematics Embry-Riddle Aeronautical University Daytona Beach, Florida · Chemistry Bethune Cookman University Daytona Beach, Florida
Training Chemical Plausibility-Aware Large Language Models for Single-Step Retrosynthesis
Aug 19, 2026Bogdan Zagribelnyy, Ivan Ilin, Nikita Bondarev +5Chemical Reaction Prediction Retrosynthesis
Insilico Medicine AI Limited, Abu Dhabi, UAE · Insilico Medicine Canada Inc., Montreal, Quebec, Canada · Insilico Medicine Hong Kong Ltd., Hong Kong SAR, China
RxnCLF: Contrastive Transformation-Aware Reaction Foundation Model for Improved Reactivity Prediction
Aug 6, 2026Yiting Zheng, Cheng Fang, Anthony Donofrio +1Representation Learning Graph Representation Learning
Discovery Chemistry, Merck & Co., Inc. Boston, MA, USA · Discovery Chemistry, Merck & Co., Inc. Cambridge, MA, USA
ReactionAtlas: Ab origine exploration of chemical reaction networks with machine learning
Jun 29, 2026Stefan Gugler, Max Eissler, Khaled Kahouli +1Generative Modeling Chemical Reaction Prediction
BIFOLD – Berlin Institute for the Foundations of Learning and Data, Berlin, Germany. · Machine Learning Group, TU Berlin, Berlin, Germany. · Department of Artificial Intelligence, Korea University, Seoul, South Korea. +1
RETROSPECT: RETROsynthesis via Sequential Prediction, and Chemically Transformed-ranking
Jun 5, 2026Raja Sekhar Pappala, Shreyas Vinaya Sathyanarayana, Ronit Kumar Choudhary +2Transformer Learning to Rank
Mstack AI
From Answers to States: Verifiable Process-Level Evaluation of Chemical Reasoning in Large Language Models
Jun 2, 2026Hongyu Guo, Hao Li, He Cao +2LLM Evaluation Chemical Reasoning in LLMs
Peking University, Shenzhen Graduate School · International Digital Economy Academy (IDEA)
SciCore-Mol: Augmenting Large Language Models with Pluggable Molecular Cognition Modules
May 21, 2026Yuxuan Chen, Changwei Lv, Yunduo Xiao +5AI-Assisted Scientific Research Chemical Reaction Prediction
School of Electronic and Computer Engineering, Peking University, Shenzhen, China · Tsinghua University, Beijing, China · School of Intelligence Science and Technology, Nanjing University, Suzhou, China
HiRes: Inspectable Precedent Memory for Reaction Condition Recommendation
May 20, 2026Shreyas Vinaya Sathyanarayana, Raja Sekhar Pappala, Deepak WarrierRepresentation Learning Molecular Representation Learning
Mstack AI Bangalore, India
ConRetroBert: EMA Stabilized Dual Encoders for Template-Based Single-Step Retrosynthesis
May 12, 2026Mohammad Jahid Ibna Basher, Ali Khodabandeh Yalabadi, Ivan Garibay +1Dense Retrieval Retrosynthesis
Department of Industrial Engineering University of Central Florida Orlando, FL 32816
ARMOR: An Agentic Framework for Reaction Feasibility Prediction via Adaptive Utility-aware Multi-tool Reasoning
May 8, 2026Ye Liu, Botao Yu, Xinyi Ling +2Computational Quantum Chemistry LLM Tool Use
Department of Biomedical Informatics The Ohio State University · Department of Computer Science and Engineering The Ohio State University · Division of Medicinal Chemistry and Pharmacognosy The Ohio State University +1
ChemBART: Pre-training a Reaction Language Model for Comprehensive Synthesis Planning
Jan 6, 2026Kenan Li, Yijian Zhang, Jin Wang +4Chemical Language Models Chemical Reaction Prediction
State Key Laboratory of Analytical Chemistry for Life Science, Kuang Yaming Honors School, Chemistry and Biomedicine Innovation Centre (ChemBIC), ChemBioMed Interdisciplinary Research Centre at Nanjing University, Engineering Research Centre of Protein and Peptide Medicine of the Ministry of Education, Institute for Brain Sciences, Nanjing University, Nanjing 210023, China. · Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China
Large Language Models Transform Organic Synthesis From Reaction Prediction to Automation
Aug 7, 2025Kartar Kumar, Rajesh Kumar, Nikesh LagunAI-Assisted Scientific Research Laboratory Automation
Department of Computer Science, Institute of Business Administration (IBA), Karachi, Pakistan · International Research Center for Complexity Sciences, Hangzhou International Innovation Institute, Beihang University, Hangzhou 311115, China · School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

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OPRD-Imp: a dataset of experimentally observed impurities and side products in multi-step pharmaceutical syntheses

Heejeong Kim, Seonbin Kim, Jihwan Kim, Tim Pinkhassik+5

Department of Chemistry and Nanoscience, Ewha Womans University, Seoul, 03760, South Korea · Department of Chemistry, Kookmin University, Seoul, 02707, South Korea · Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA+2

Chemical Reaction Prediction

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Predicting reaction impurities is a critical yet persistently data-limited challenge in pharmaceutical process chemistry. While machine learning models for reaction outcome prediction have advanced rapidly, benchmarking their ability to predict impurities remains impractical due to the absence of curated, publicly accessible datasets. We present OPRD-Imp, a dataset of 229 organic reactions drawn from 62 publications in Organic Process Research & Development, each annotated with experimentally observed impurities and their mechanistic origins. A total of 784 impurity entries is provided, classified into four origin categories. Reactions are represented as reaction SMILES and impurities as individual SMILES strings, with multi-step synthetic route connectivity preserved. All data were manually extracted from the source publications by trained chemists following a standardized extraction protocol, with expert chemical validation and manual structure drawing. OPRD-Imp is intended to serve as a benchmark resource for evaluating models that predict reaction impurities, providing experimentally reported impurity annotations and mechanistic origin labels that are not systematically represented in conventional reaction datasets.