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RESEARCH PAPER · Nature Computational Science · 2023

Chemical reaction networks and opportunities for machine learning

Mingjian Wen, Evan Walter Clark Spotte‐Smith, Samuel M. Blau, Matthew J. McDermott, Aditi S. Krishnapriyan, Kristin Aslaug Persson

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Chemical reaction networks and opportunities for machine learningOriginalModernist materials synthesis: Finding thermodynamic shortcuts with hyperdimensional chemistry19Chemical Reaction Networks Explain Gas Evolution Mechanisms in Mg-Ion Batteries40Statistics and Bias-Free Sampling of Reaction Mechanisms from Reaction Network Models3Patogénesis a través de los sistemas: un modelo conceptual de redes de reacción del proceso de infección de Salmonella enterica1Machine Learning-Based Prediction of Activation Energies for Chemical Reactions on Metal Surfaces14Physics-informed machine learning and its structural integrity applications: state of the art60Data driven design of compositionally complex energy materials13A knowledge-driven approach for automatic generation of reaction networks of methanol-to-olefins process5A query-response causal analysis of reaction events in biochemical reaction networks0Accelerating the Design of Multishell Upconverting Nanoparticles through Bayesian Optimization37Removal of the textile dyes by a resin adsorbent polymeric: Insight into optimization, kinetics and isotherms adsorption phenomenally43Probabilistic prediction of material stability: integrating convex hulls into active learning10Deep mechanism reduction (DeePMR) method for fuel chemical kinetics25Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview14Communication efficiency enhanced federated learning derived from quantum reinforcement learning for retrosynthesis1Learning nonequilibrium statistical mechanics and dynamical phase transitions27A possibility to infer frustrations of supported catalytic clusters from macro-scale observations1Iterative design of training data to control intricate enzymatic reaction networks16Exploring Chemical Reaction Space with Machine Learning Models: Representation and Feature Perspective26Distilling dynamical knowledge from stochastic reaction networks6Networks of Hydrogen Bond Networks in Water Clusters4Establishing C-C electro-coupling mechanism via big data analyses of reaction networks0A human-machine interface for automatic exploration of chemical reaction networks26Python tools for structural tasks in chemistry15Adsorption techniques including polymer resin for the removal of the micropollutants organics and metallics: A comprehensive review9Charge govern ion-selective mechanism of YX2 desalination pore using high-throughput computations and machine learning8RETRACTED ARTICLE: Comparing ANI-2x, ANI-1ccx neural networks, force field, and DFT methods for predicting conformational potential energy of organic molecules19Trendbericht: Technische Chemie 20242A Cellular Automaton Approach for Efficient Computing on Surface Chemical Reaction Networks3SCINE—Software for chemical interaction networks20An algorithmic framework for synthetic cost-aware decision making in molecular design34Chemical Networks from Scratch with Reaction Prediction and Kinetics-Guided Exploration4MACE: A Machine-learning Approach to Chemistry Emulation12Enabling high throughput deep reinforcement learning with first principles to investigate catalytic reaction mechanisms31Transition State Searching Accelerated by Deep Learning Potential2Computer‐Aided Synthesis Planning (CASP) and Machine Learning: Optimizing Chemical Reaction Conditions15Deep Learning Reaction Network: a machine learning framework for modeling time resolved data0Quantum chemical package Jaguar: A survey of recent developments and unique features62Machine Learning Big Data Set Analysis Reveals C–C Electro-Coupling Mechanism972024 roadmap for sustainable batteries34Chemical reaction enhanced graph learning for molecule representation5Traceback: A Fault Localization Technique for Molecular Programs0When Metal Nanoclusters Meet Smart Synthesis31Chemical Roadmap toward Stable Electrolyte–Electrode Interfaces in All-Solid-State Batteries10Basal State Calibration of a Chemical Reaction Network Model for Autophagy0Enhancing reliability of composed non-output-oblivious chemical reaction networks0Estimating reaction barriers with deep reinforcement learning1Uncertainty Qualification for Deep Learning-Based Elementary Reaction Property Prediction7Rate coefficients for C and O2 reactive collisions relevant to interstellar clouds from QCT and machine learning0Role of Artificial Intelligence in Teaching and Learning Chemical Sciences0Surface restructuring and predictive design of heterogeneous catalysts213Uncertainty quantification and propagation in atomistic machine learning29Unveiling hidden reaction kinetics of carbon dioxide in supercritical aqueous solutions9Atomistic catalytic reaction networks: case study on electrochemical reduction of CO, NO & combinations0Inferring networks of chemical reactions by curvature analysis of kinetic trajectories0Lowering the exponential wall: accelerating high-entropy alloy catalysts screening using local surface energy descriptors from neural network potentials10Precursor reaction pathway leading to BiFeO 3 formation: insights from text-mining and chemical reaction network analyses2Sparse identification of chemical reaction mechanisms from limited concentration profiles1Machine Learning Potentials for Heterogeneous Catalysis109A Topological Approach to Enhancing Consistency in Machine Learning via Recurrent Neural Networks1ChemComp: A Compilation Framework for Computing with Chemical Reaction Networks4Derivative-Free Domain-Informed Data-Driven Discovery of Sparse Kinetic Models14Chemical Reaction Networks from Scratch with Reaction Prediction and Kinetics-Guided Exploration19Highly Precise Prediction of Micro‐ and Supra‐p K a Based on 3D Descriptors Integrating Non‐Covalent Interactions14Highly Precise Prediction of Micro‐ and Supra‐p K a Based on 3D Descriptors Integrating Non‐Covalent Interactions2Efficient machine learning method for supercritical combustion: Predicting real-fluid properties and chemical ODEs8Integrating operando spectroscopies and transient analysis for dynamic catalytic insights5Ten Problems in Polymer Reactivity Prediction13Transition State Searching Accelerated by Neural Network Potential12Machine Learning Accelerated Analysis of Chemical Reaction Networks for Gas-Phase Reaction Systems2ChemComp: Compiling and Computing with Chemical Reaction Networks3In Silico Exploration of Metabolite-Derived Soft Materials Using a Chemical Reaction Network0Modeling Chemical Reaction Networks Using Neural Ordinary Differential Equations8Deep Learning Reaction Framework (DLRN) for kinetic modeling of time-resolved data2Topological constraints on proton dynamics in water clusters0Thermodynamic Constraints on the Citric Acid Cycle and Related Reactions in Ocean World Interiors2Automated Microsolvation for Minimum Energy Path Construction in Solution10Multilayered substructures of a non-enzymatic chemical reaction network for synthesizing sugars1A framework to evaluate machine learning crystal stability predictions154Machine Learning Interatomic Potential‐Enabled Discovery of Chlorofullerenes0An open-source family of large encoder-decoder foundation models for chemistry19Electrocatalytic CO 2 Reduction to Multi‐Carbon Products on Non‐Copper‐Based Catalysts: Reaction Pathways, Enhancement Strategies, and Future Challenges11High-precision prediction of fluorescence wavelength of organic based on ensemble automatic machine learning method and online querying6Harnessing Machine Learning to Enhance Transition State Search with Interatomic Potentials and Generative Models16Integrating AI into OLED material design: a comprehensive review of computational frameworks, challenges, and opportunities16Exploring the Reaction Network of Acetic Acid in Supercritical Water via Machine Learning Interatomic Potential2Toward data-driven predictive modeling of electrocatalyst stability and surface reconstruction24Experimentally Guided Iterative Parameter Estimation for Predictive Chemical Oscillator Models2Experimentally Guided Iterative Parameter Estimation for Predictive Chemical Oscillator Models0Agnostic Tools for Life Detection: A Multiscale Approach to Biological and Chemical Reaction Networks0Digital Twin for Chemical Science: a case study on water interactions on the Ag(111) surface13Ultrafast synthesis of ternary oxides via a design-test-make-analyze workflow1Lifelong Machine Learning Potentials for Chemical Reaction Network Explorations5Sustainable Catalytic Production of Biodiesel from Waste Corn Oil: Efficiency Evaluation1Improving Reaction Yield Prediction with Chemical Atom-Level Reaction Learning1Transferable Learning of Reaction Pathways from Geometric Priors1Bond-editing driven electron flow mapping for reaction mechanism modeling0Therapeutic targeting of lncRNAs in Age-Related Ocular Disease0A kinetic mechanism reduction method for fuel combustion based on random forests model4Understanding Multistationarity of Fully Open Reaction Networks0On the use of chemical bonding descriptors in machine learning18Chemical Reactor Network and Agent Model for Hypersonic Strut–Cavity Combustor Flames1A GPU-accelerated stiff ODE solver for combustion CFD with fully analytical chemical kinetics and heterogeneous CPU/GPU integration0A Large Scale Molecular Hessian Database for Optimizing Reactive Machine Learning Interatomic Potentials0Higher order structures in chemistry: hypergraphs reshape the molecule and the reaction1Informatics for thermodynamics: Stability to synthesizability0Mapping connections and pathways0On the Preservation of Input/Output Directed Graph Informativeness Under Crossover0Thermodynamic effects of solid electrolyte interphase formation from solvation and ionic association in water-in-salt electrolytes0Emergent synchrony in oscillator networks with adaptive arbitrary-order interactions2DeepTherm: A unified deep learning approach to thermochemistry prediction for gas-phase molecules2Probing entropic control of stacking phase preference in layered oxide cathodes for sodium-ion batteries via machine-learning potentials8Challenges and Opportunities of Pretrained Machine Learning Interatomic Potentials in Heterogeneous Catalysis8Exploring chemistry and catalysis by biasing skewed distributions via deep learning3Data-driven prediction of solid state reaction pathways in the synthesis of ferrites2Uncertainty Quantification for In Silico Chemistry13RxnNet: An AI Framework for Reaction Mechanism Discovery─A Case Study of Carbocations2An end-to-end framework for reactivity in heterogeneous catalysis9A machine learning based method for hydrogen oxidation mechanisms classification in solid oxide cells2Photoelectrocatalytic Chemical Pathways in Photoassisted Lithium–Sulfur Batteries via a Multiscale Graph-Based Machine Learning Framework6Accelerating multiscale modeling in heterogeneous catalysis0Energy-efficient scientific computing using chemical reservoirs2Computation-Driven Experimental Discovery of Reactivity Space of Organoboron Compounds2SOT-RM: An equivariant shortcut and optimal transport-based flow model for exploring chemical reaction mechanisms0A Comprehensive Dataset of Chemical Reactions Covering Second and Third Row Elements with Million-Scale Quantum Chemical Calculations0Spiking Neuron Memory Enhancement Model Based on Short-Term Synaptic Plasticity0CRN2DB: Chemical Reaction Networks to Database Matching via Dynamic Programming in ChemComp0Quantum chemistry unifies phosphorus removal and recovery through environmental affinity1Organic Chemistry as a Catalyst for AI Innovation: Challenges, Methods, and Emerging Paradigms1Reaction-to-fire characterization data driving the AI-assisted design of flame-retardant polymeric materials1Graph-Based Generation and Reduction of Complex Chemical Reaction Networks0Identifying reaction network structures for lithium-ion battery cathodes at thermal-runaway onset temperatures0Machine Learning in Molecular Dynamics from Reactive Chemistry to Astrophysical Systems0Introduction to random rule-based chemical networks0New Frontiers in Single-Atom Catalysis: Active-Site Dynamics and AI-Enabled Design1Knowledge-based overlapping reaction community detection for interpretable simplification of petrochemical reaction networks0Euclidean Embedding of Reaction Networks for Dimensionality Reduction of Chemical Spaces1Chemically informed community detection for topological analysis and simplification of complex chemical reaction networks0Dynamics of Catalyst Structures1AIMNet2-rxn: A machine-learned potential for generalized reaction modeling on a millions-of-pathways scale13

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