Machine learning for a sustainable energy future

The AI Economist: Taxation policy design via two-level deep multiagent reinforcement learning

(2022) Stephan Zheng et al.   Science Advances

Understanding electrified interfaces

(2021) Stephan N. Steinmann et al.   Nature Reviews Materials

Pseudo-halide anion engineering for α-FAPbI3 perovskite solar cells

(2021) Jaeki Jeong et al.   NATURE

Machine learning in materials science: From explainable predictions to autonomous design

(2021) Ghanshyam Pilania   COMPUTATIONAL MATERIALS SCIENCE

Electrode Degradation in Lithium-Ion Batteries

(2020) Joshua P. Pender et al.   ACS Nano

Beyond Ternary OPV: High‐Throughput Experimentation and Self‐Driving Laboratories Optimize Multicomponent Systems

(2020) Stefan Langner et al.   ADVANCED MATERIALS

Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks

(2020) Edward Kim et al.   Journal of Chemical Information and Modeling

Closed-loop optimization of fast-charging protocols for batteries with machine learning

(2020) Peter M. Attia et al.   NATURE

Crystal symmetry determination in electron diffraction using machine learning

(2020) Kevin Kaufmann et al.   SCIENCE

Quantum Chemistry-Informed Active Learning to Accelerate the Design and Discovery of Sustainable Energy Storage Materials

(2020) Hieu A. Doan et al.   CHEMISTRY OF MATERIALS

Accelerated discovery of CO2 electrocatalysts using active machine learning

(2020) Miao Zhong et al.   NATURE

ChemOS: An orchestration software to democratize autonomous discovery

(2020) Loïc M. Roch et al.   PLoS One

High-throughput, combinatorial synthesis of multimetallic nanoclusters

(2020) Yonggang Yao et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Self-driving laboratory for accelerated discovery of thin-film materials

(2020) B. P. MacLeod et al.   Science Advances

Developing an improved crystal graph convolutional neural network framework for accelerated materials discovery

(2020) Cheol Woo Park et al.   Physical Review Materials

Artificial Chemist: An Autonomous Quantum Dot Synthesis Bot

(2020) Robert W. Epps et al.   ADVANCED MATERIALS

Robot-Accelerated Perovskite Investigation and Discovery

(2020) Zhi Li et al.   CHEMISTRY OF MATERIALS

A mobile robotic chemist

(2020) Benjamin Burger et al.   NATURE

Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships

(2020) Steven B. Torrisi et al.   npj Computational Materials

In Situ/Operando Electrocatalyst Characterization by X-ray Absorption Spectroscopy

(2020) Janis Timoshenko et al.   CHEMICAL REVIEWS

How machine learning can help select capping layers to suppress perovskite degradation

(2020) Noor Titan Putri Hartono et al.   Nature Communications

Data-driven prediction of battery cycle life before capacity degradation

(2019) Kristen A. Severson et al.   Nature Energy

Exnovating for a renewable energy transition

(2019) Debra J. Davidson   Nature Energy

Learning-in-Templates Enables Accelerated Discovery and Synthesis of New Stable Double Perovskites

(2019) Mikhail Askerka et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Machine Learning the Voltage of Electrode Materials in Metal-Ion Batteries

(2019) Rajendra P. Joshi et al.   ACS Applied Materials & Interfaces

Machine Learning in Medicine

(2019) Alvin Rajkomar et al.   NEW ENGLAND JOURNAL OF MEDICINE

Machine learning in a data-limited regime: Augmenting experiments with synthetic data uncovers order in crumpled sheets

(2019) Jordan Hoffmann et al.   Science Advances

Screening billions of candidates for solid lithium-ion conductors: A transfer learning approach for small data

(2019) Ekin D. Cubuk et al.   JOURNAL OF CHEMICAL PHYSICS

Identifying Active Sites for CO2 Reduction on Dealloyed Gold Surfaces by Combining Machine Learning with Multiscale Simulations

(2019) Yalu Chen et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Unsupervised word embeddings capture latent knowledge from materials science literature

(2019) Vahe Tshitoyan et al.   NATURE

Stabilizing polymer electrolytes in high-voltage lithium batteries

(2019) Snehashis Choudhury et al.   Nature Communications

Learning Quality Rating of As-Cut mc-Si Wafers via Convolutional Regression Networks

(2019) Matthias Demant et al.   IEEE Journal of Photovoltaics

A Mixed Quantum Chemistry/Machine Learning Approach for the Fast and Accurate Prediction of Biochemical Redox Potentials and Its Large-Scale Application to 315 000 Redox Reactions

(2019) Adrian Jinich et al.   ACS Central Science

Semi-supervised machine-learning classification of materials synthesis procedures

(2019) Haoyan Huo et al.   npj Computational Materials

Machine Learning Optimization of p-Type Transparent Conducting Films

(2019) Lingfei Wei et al.   CHEMISTRY OF MATERIALS

A robotic platform for flow synthesis of organic compounds informed by AI planning

(2019) Connor W. Coley et al.   SCIENCE

Scanning Electrochemical Flow Cell with Online Mass Spectroscopy for Accelerated Screening of Carbon Dioxide Reduction Electrocatalysts

(2019) Yungchieh Lai et al.   ACS Combinatorial Science

Recent advances and applications of machine learning in solid-state materials science

(2019) Jonathan Schmidt et al.   npj Computational Materials

Degradation model of proton exchange membrane fuel cell based on a novel hybrid method

(2019) Kui Chen et al.   APPLIED ENERGY

A review of deep learning for renewable energy forecasting

(2019) Huaizhi Wang et al.   ENERGY CONVERSION AND MANAGEMENT

Unsupervised discovery of solid-state lithium ion conductors

(2019) Ying Zhang et al.   Nature Communications

Machine learning–assisted molecular design and efficiency prediction for high-performance organic photovoltaic materials

(2019) Wenbo Sun et al.   Science Advances

Decoding crystallography from high-resolution electron imaging and diffraction datasets with deep learning

(2019) J. A. Aguiar et al.   Science Advances

Strategies to break linear scaling relationships

(2019) Javier Pérez-Ramírez et al.   Nature Catalysis

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

(2019) Alejandro Barredo Arrieta et al.   Information Fusion

Digital twin driven prognostics and health management for complex equipment

(2018) Fei Tao et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

PyCDT: A Python toolkit for modeling point defects in semiconductors and insulators

(2018) Danny Broberg et al.   COMPUTER PHYSICS COMMUNICATIONS

Relaxed deep learning for real-time economic generation dispatch and control with unified time scale

(2018) Linfei Yin et al.   ENERGY

SCScore: Synthetic Complexity Learned from a Reaction Corpus

(2018) Connor W. Coley et al.   Journal of Chemical Information and Modeling

Exploration versus Exploitation in Global Atomistic Structure Optimization

(2018) Mathias S. Jørgensen et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Crystal Structure Prediction via Deep Learning

(2018) Kevin Ryan et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Neural Network Approach for Characterizing Structural Transformations by X-Ray Absorption Fine Structure Spectroscopy

(2018) Janis Timoshenko et al.   PHYSICAL REVIEW LETTERS

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

(2018) Tian Xie et al.   PHYSICAL REVIEW LETTERS

On-the-Fly Machine Learning of Atomic Potential in Density Functional Theory Structure Optimization

(2018) T. L. Jacobsen et al.   PHYSICAL REVIEW LETTERS

Carbothermal shock synthesis of high-entropy-alloy nanoparticles

(2018) Yonggang Yao et al.   SCIENCE

Insightful classification of crystal structures using deep learning

(2018) Angelo Ziletti et al.   Nature Communications

Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules

(2018) Rafael Gómez-Bombarelli et al.   ACS Central Science

Thermodynamic limit for synthesis of metastable inorganic materials

(2018) Muratahan Aykol et al.   Science Advances

Data-driven proton exchange membrane fuel cell degradation predication through deep learning method

(2018) Rui Ma et al.   APPLIED ENERGY

State-of-charge estimation of Li-ion batteries using deep neural networks: A machine learning approach

(2018) Ephrem Chemali et al.   JOURNAL OF POWER SOURCES

Controlling an organic synthesis robot with machine learning to search for new reactivity

(2018) Jarosław M. Granda et al.   NATURE

Machine learning for molecular and materials science

(2018) Keith T. Butler et al.   NATURE

Planning chemical syntheses with deep neural networks and symbolic AI

(2018) Marwin H. S. Segler et al.   NATURE

Inverse molecular design using machine learning: Generative models for matter engineering

(2018) Benjamin Sanchez-Lengeling et al.   SCIENCE

Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learning

(2018) Shuaihua Lu et al.   Nature Communications

High entropy oxides for reversible energy storage

(2018) Abhishek Sarkar et al.   Nature Communications

Machine Learning Enabled Computational Screening of Inorganic Solid Electrolytes for Suppression of Dendrite Formation in Lithium Metal Anodes

(2018) Zeeshan Ahmad et al.   ACS Central Science

Machine Learning-Assisted Discovery of Solid Li-Ion Conducting Materials

(2018) Austin D. Sendek et al.   CHEMISTRY OF MATERIALS

Solar cell designs by maximizing energy production based on machine learning clustering of spectral variations

(2018) J. M. Ripalda et al.   Nature Communications

Identification of the Selective Sites for Electrochemical Reduction of CO to C2+ Products on Copper Nanoparticles by Combining Reactive Force Fields, Density Functional Theory, and Machine Learning

(2018) Yufeng Huang et al.   ACS Energy Letters

Performance analysis of perovskite solar cells in 2013–2018 using machine-learning tools

(2018) Çağla Odabaşı et al.   Nano Energy

Holistic computational structure screening of more than 12 000 candidates for solid lithium-ion conductor materials

(2017) Austin D. Sendek et al.   Energy & Environmental Science

MultiDK: A Multiple Descriptor Multiple Kernel Approach for Molecular Discovery and Its Application to Organic Flow Battery Electrolytes

(2017) Sungjin Kim et al.   Journal of Chemical Information and Modeling

Fault detection and isolation of high temperature proton exchange membrane fuel cell stack under the influence of degradation

(2017) Christian Jeppesen et al.   JOURNAL OF POWER SOURCES

Gaussian process regression for forecasting battery state of health

(2017) Robert R. Richardson et al.   JOURNAL OF POWER SOURCES

Use machine learning to find energy materials 

(2017) Phil De Luna et al.   NATURE

The path towards sustainable energy

(2017) Steven Chu et al.   NATURE MATERIALS

Materials for solar fuels and chemicals

(2017) Joseph H. Montoya et al.   NATURE MATERIALS

Atomic structure of sensitive battery materials and interfaces revealed by cryo–electron microscopy

(2017) Yuzhang Li et al.   SCIENCE

Combining theory and experiment in electrocatalysis: Insights into materials design

(2017) Zhi Wei Seh et al.   SCIENCE

To address surface reaction network complexity using scaling relations machine learning and DFT calculations

(2017) Zachary W. Ulissi et al.   Nature Communications

Universal fragment descriptors for predicting properties of inorganic crystals

(2017) Olexandr Isayev et al.   Nature Communications

Machine-Learning Methods Enable Exhaustive Searches for Active Bimetallic Facets and Reveal Active Site Motifs for CO2 Reduction

(2017) Zachary W. Ulissi et al.   ACS Catalysis

Unsupervised energy prediction in a Smart Grid context using reinforcement cross-building transfer learning

(2016) Elena Mocanu et al.   ENERGY AND BUILDINGS

Acceleration of saddle-point searches with machine learning

(2016) Andrew A. Peterson   JOURNAL OF CHEMICAL PHYSICS

Online state of health estimation on NMC cells based on predictive analytics

(2016) Maitane Berecibar et al.   JOURNAL OF POWER SOURCES

Direct calorimetric verification of thermodynamic instability of lead halide hybrid perovskites

(2016) G. P. Nagabhushana et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

A review on planning, configurations, modeling and optimization techniques of hybrid renewable energy systems for off grid applications

(2016) Rajanna Siddaiah et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Dynamic Pricing and Energy Consumption Scheduling With Reinforcement Learning

(2016) Byung-Gook Kim et al.   IEEE Transactions on Smart Grid

Neural Networks for the Prediction of Organic Chemistry Reactions

(2016) Jennifer N. Wei et al.   ACS Central Science

The thermodynamic scale of inorganic crystalline metastability

(2016) W. Sun et al.   Science Advances

Machine learning bandgaps of double perovskites

(2016) G. Pilania et al.   Scientific Reports

A Novel Dual Iterative $Q$-Learning Method for Optimal Battery Management in Smart Residential Environments

(2015) Qinglai Wei et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Multi-Agent Correlated Equilibrium Q(λ) Learning for Coordinated Smart Generation Control of Interconnected Power Grids

(2015) T. Yu et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Numerical modeling of non-planar hydraulic fracture propagation in brittle and ductile rocks using XFEM with cohesive zone method

(2015) HanYi Wang   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Introducing structural sensitivity into adsorption–energy scaling relations by means of coordination numbers

(2015) Federico Calle-Vallejo et al.   Nature Chemistry

Enhancement of the chemical stability in confined δ-Bi 2 O 3

(2015) Simone Sanna et al.   NATURE MATERIALS

Review of energy system flexibility measures to enable high levels of variable renewable electricity

(2015) Peter D. Lund et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Machine learning: Trends, perspectives, and prospects

(2015) M. I. Jordan et al.   SCIENCE

On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

(2015) Sebastian Bach et al.   PLoS One

Key performance indicators: A useful tool to assess Smart Grid goals

(2014) Enrique Personal et al.   ENERGY

Trends in electrochemical CO2 reduction activity for open and close-packed metal surfaces

(2014) Chuan Shi et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Darwin at High Temperature: Advancing Solar Cell Material Design Using Defect Kinetics Simulations and Evolutionary Optimization

(2014) David P. Fenning et al.   Advanced Energy Materials

Representation Learning: A Review and New Perspectives

(2013) Y. Bengio et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Learning policies for battery usage optimization in electric vehicles

(2013) Stefano Ermon et al.   MACHINE LEARNING

On representing chemical environments

(2013) Albert P. Bartók et al.   PHYSICAL REVIEW B

Solar and wind energy production in relation to the electricity load curve and hydroelectricity in the northeast region of Brazil

(2013) P. de Jong et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Highly Efficient Light-Trapping Structure Design Inspired By Natural Evolution

(2013) Chen Wang et al.   Scientific Reports

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

(2013) Anubhav Jain et al.   APL Materials

Intelligent Hybrid Vehicle Power Control—Part II: Online Intelligent Energy Management

(2012) Yi Lu Murphey et al.   IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY

The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid

(2011) Johannes Hachmann et al.   Journal of Physical Chemistry Letters

Assessing Synthetic Accessibility of Chemical Compounds Using Machine Learning Methods

(2010) Yevgeniy Podolyan et al.   Journal of Chemical Information and Modeling

Design, synthesis and selection of DNA-encoded small-molecule libraries

(2009) Matthew A Clark et al.   Nature Chemical Biology

Design of multilayer antireflection coatings made from co-sputtered and low-refractive-index materials by genetic algorithm

(2008) Martin F. Schubert et al.   OPTICS EXPRESS