Accelerating materials discovery using machine learning

A review on cooling performance enhancement for phase change materials integrated systems—flexible design and smart control with machine learning applications

(2020) Yuekuan Zhou et al.   BUILDING AND ENVIRONMENT

A machine learning based decision aid for lameness in dairy herds using farm-based records

(2020) Daniel Warner et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Machine learning explainability via microaggregation and shallow decision trees

(2020) Alberto Blanco-Justicia et al.   KNOWLEDGE-BASED SYSTEMS

Ultrafast machine vision with 2D material neural network image sensors

(2020) Lukas Mennel et al.   NATURE

Deterministic generative adversarial imitation learning

(2020) Guoyu Zuo et al.   NEUROCOMPUTING

Crystallization Mechanism in Spark Plasma Sintered Bulk Metallic Glass Analyzed using Small Angle Neutron Scattering

(2020) Tanaji Paul et al.   Scientific Reports

Learning to learn from data: Using deep adversarial learning to construct optimal statistical procedures

(2020) Alex Luedtke et al.   Science Advances

Vanadium is an optimal element for strengthening in both fcc and bcc high-entropy alloys

(2020) Binglun Yin et al.   ACTA MATERIALIA

Predicting creep rupture life of Ni-based single crystal superalloys using divide-and-conquer approach based machine learning

(2020) Yue Liu et al.   ACTA MATERIALIA

Regulating the effect of element doping on the CO2 capture performance of kaolinite: A density functional theory study

(2020) Jialiang Hou et al.   APPLIED SURFACE SCIENCE

Application of Artificial Neural Networks to predict fibre orientation in long fibre compression moulded composite materials

(2020) Trevor Sabiston et al.   COMPOSITES SCIENCE AND TECHNOLOGY

Using machine learning and feature engineering to characterize limited material datasets of high-entropy alloys

(2020) Dongbo Dai et al.   COMPUTATIONAL MATERIALS SCIENCE

Using deep learning to extend the range of air pollution monitoring and forecasting

(2020) Philipp Hähnel et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Thermodynamics and kinetics of phase transformation in rare earth–magnesium alloys: A critical review

(2020) Qun Luo et al.   JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY

Predicting the band gap of ZnO quantum dots via supervised machine learning models

(2020) Paul Rossener Regonia et al.   OPTIK

Enhanced optical path and electron diffusion length enable high-efficiency perovskite tandems

(2020) Bin Chen et al.   Nature Communications

Designing Rules of Laser-Clad High-Entropy Alloy Coatings with Simple Solid Solution Phases

(2020) Yongfei Juan et al.   Acta Metallurgica Sinica-English Letters

Classifying post-traumatic stress disorder using the magnetoencephalographic connectome and machine learning

(2020) Jing Zhang et al.   Scientific Reports

Multiscale computational understanding and growth of 2D materials: a review

(2020) Kasra Momeni et al.   npj Computational Materials

Assessment of critical materials and cell design factors for high performance lithium-sulfur batteries using machine learning

(2020) Aysegul Kilic et al.   CHEMICAL ENGINEERING JOURNAL

Hybrid decision tree-based machine learning models for short-term water quality prediction

(2020) Hongfang Lu et al.   CHEMOSPHERE

Fatigue life prediction of metallic materials considering mean stress effects by means of an artificial neural network

(2020) Joelton Fonseca Barbosa et al.   INTERNATIONAL JOURNAL OF FATIGUE

A data-driven framework to predict the morphology of interfacial Cu6Sn5 IMC in SAC/Cu system during laser soldering

(2020) Anil Kunwar et al.   JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY

Classification of femur fracture in pelvic X-ray images using meta-learned deep neural network

(2020) Changhwan Lee et al.   Scientific Reports

Deformation behavior of annealed Cu64Zr36 metallic glass via molecular dynamics simulations

(2020) Xingxing Yue et al.   MATERIALS & DESIGN

Machine learning assisted materials design and discovery for rechargeable batteries

(2020) Yue Liu et al.   Energy Storage Materials

Predictive ANN models for varying filler content for cotton fiber/PVC composites based on experimental load displacement curves

(2020) Monzure-Khoda Kazi et al.   COMPOSITE STRUCTURES

Accelerating materials science with high-throughput computations and machine learning

(2019) Shyue Ping Ong   COMPUTATIONAL MATERIALS SCIENCE

Combination of Support Vector Machine and K-Fold cross validation to predict compressive strength of concrete in marine environment

(2019) Hao Ling et al.   CONSTRUCTION AND BUILDING MATERIALS

CWV-BANN-SVM Ensemble Learning Classifier for Early Diagnosis of Breast Cancer

(2019) Moloud Abdar   MEASUREMENT

Between-Subclass Piece-wise Linear Solutions in Large Scale Kernel SVM Learning

(2019) Tejas Indulal Dhamecha et al.   PATTERN RECOGNITION

Density functional theory calculations: A powerful tool to simulate and design high-performance energy storage and conversion materials

(2019) Xi Wu et al.   Progress in Natural Science-Materials International

Three-dimensional structure and formation mechanisms of Y2O3 hollow-precipitates in a Cu-based metallic glass

(2019) Oriane Baulin et al.   MATERIALS & DESIGN

Thermodynamic Assessment of the Solar-to-fuel Performance of La0.6Sr0.4Mn1-yCryO3- Perovskite Solid Solution Series

(2019) Alexander H. Bork et al.   ACTA MATERIALIA

ReviewModus: Text classification and sentiment prediction of unstructured reviews using a hybrid combination of machine learning and evaluation models

(2019) Fouad Zablith et al.   APPLIED MATHEMATICAL MODELLING

Understanding adsorption of nucleobases on CH3NH3PbI3 surfaces toward biological applications of halide perovskite materials

(2019) Lei Zhang et al.   APPLIED SURFACE SCIENCE

Decision tree-based machine learning to optimize the laminate stacking of composite cylinders for maximum buckling load and minimum imperfection sensitivity

(2019) H.N.R. Wagner et al.   COMPOSITE STRUCTURES

A new evidential K-nearest neighbor rule based on contextual discounting with partially supervised learning

(2019) Thierry Denœux et al.   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

On the formulation of the kinematics and thermodynamics for polycrystalline materials undergoing phase transformation

(2019) Adetokunbo A. Adedoyin et al.   INTERNATIONAL JOURNAL OF PLASTICITY

Towards an integrated machine-learning framework for model evaluation and uncertainty quantification

(2019) Bertrand Buisson et al.   NUCLEAR ENGINEERING AND DESIGN

Recent progress in the simulation of microstructure evolution in titanium alloys

(2019) Jinhu Zhang et al.   Progress in Natural Science-Materials International

Hybrid machine intelligent SVR variants for wind forecasting and ramp events

(2019) Harsh S. Dhiman et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Predicting the onset temperature (Tg) of Ge Se1− glass transition: a feature selection based two-stage support vector regression method

(2019) Yue Liu et al.   Science Bulletin

Short-range order structure motifs learned from an atomistic model of a Zr50Cu45Al5 metallic glass

(2019) Jason J. Maldonis et al.   ACTA MATERIALIA

DScribe: Library of descriptors for machine learning in materials science

(2019) Lauri Himanen et al.   COMPUTER PHYSICS COMMUNICATIONS

Speeding up k-Nearest Neighbors classifier for large-scale multi-label learning on GPUs

(2019) Przemysław Skryjomski et al.   NEUROCOMPUTING

Robotic retail surveying by deep learning visual and textual data

(2019) Marina Paolanti et al.   ROBOTICS AND AUTONOMOUS SYSTEMS

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

(2019) Jonathan Schmidt et al.   npj Computational Materials

The effect of cracks on the stability of the functionally graded plates with variable-thickness using HSDT and phase-field theory

(2019) Phuc Pham Minh et al.   COMPOSITES PART B-ENGINEERING

Materials data specification: Methods and use cases

(2019) Quan Qian et al.   COMPUTATIONAL MATERIALS SCIENCE

Comprehensive analysis of machine learning models for prediction of sub-clinical mastitis: Deep Learning and Gradient-Boosted Trees outperform other models

(2019) Mansour Ebrahimi et al.   COMPUTERS IN BIOLOGY AND MEDICINE

Advanced modeling and numerical simulations for the thermo-chemico-mechanical behaviour of materials with damage and hydrogen, based on the thermodynamics of irreversible processes

(2019) K. Saliya et al.   FINITE ELEMENTS IN ANALYSIS AND DESIGN

On the performance of adjusted bootstrapping methods for intermittent demand forecasting

(2019) M. Hasni et al.   INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS

Stable lithium–sulfur batteries with high sulfur content fabricated by ultralight ochroma lagopus-derived carbon with dopamine shell as sulfur host

(2019) Yinze Zuo et al.   JOURNAL OF ALLOYS AND COMPOUNDS

Remaining useful life estimation of lithium-ion cells based on k-nearest neighbor regression with differential evolution optimization

(2019) Yapeng Zhou et al.   JOURNAL OF CLEANER PRODUCTION

Using machine learning to estimate a key missing geochemical variable in mining exploration: Application of the Random Forest algorithm to multi-sensor core logging data

(2019) N. Schnitzler et al.   JOURNAL OF GEOCHEMICAL EXPLORATION

Cathode porosity is a missing key parameter to optimize lithium-sulfur battery energy density

(2019) Ning Kang et al.   Nature Communications

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

Noise prediction of axial piston pump based on different valve materials using a modified artificial neural network model

(2019) Hassan A. Babikir et al.   Alexandria Engineering Journal

Phase prediction in high entropy alloys with a rational selection of materials descriptors and machine learning models

(2019) Yan Zhang et al.   ACTA MATERIALIA

MOFs-derived nitrogen-doped carbon interwoven with carbon nanotubes for high sulfur content lithium–sulfur batteries

(2019) Maru Dessie Walle et al.   APPLIED SURFACE SCIENCE

Ternary-task convolutional bidirectional neural turing machine for assessment of EEG-based cognitive workload

(2019) Weizheng Qiao et al.   Biomedical Signal Processing and Control

Integration of continuous restricted Boltzmann machine and SVR in NOx emissions prediction of a tangential firing boiler

(2019) Wei Fan et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Study on time-temperature-transformation diagrams of stainless steel using machine-learning approach

(2019) Xiaoya Huang et al.   COMPUTATIONAL MATERIALS SCIENCE

Analyzing the robotic behavior in a smart city with deep enforcement and imitation learning using IoRT

(2019) Yan Liu et al.   COMPUTER COMMUNICATIONS

Automatic driver stress level classification using multimodal deep learning

(2019) Mohammad Naim Rastgoo et al.   EXPERT SYSTEMS WITH APPLICATIONS

Machine learning-based design support system for the prediction of heterogeneous machine parameters in industry 4.0

(2019) Luca Romeo et al.   EXPERT SYSTEMS WITH APPLICATIONS

SEHC: A high-throughput materials computing framework with automatic self-evaluation filtering

(2019) Wenhao Zhu et al.   Materials Science and Engineering B-Advanced Functional Solid-State Materials

Joint Ranking SVM and Binary Relevance with robust Low-rank learning for multi-label classification

(2019) Guoqiang Wu et al.   NEURAL NETWORKS

Recognition of words from brain-generated signals of speech-impaired people: Application of autoencoders as a neural Turing machine controller in deep neural networks

(2019) Behzad Boloukian et al.   NEURAL NETWORKS

A meta-learning approach for selecting image segmentation algorithm

(2019) Gabriel Jonas Aguiar et al.   PATTERN RECOGNITION LETTERS

Decision tree machine learning applied to bovine tuberculosis risk factors to aid disease control decision making

(2019) M. Pilar Romero et al.   PREVENTIVE VETERINARY MEDICINE

Random Forests machine learning applied to gas chromatography – Mass spectrometry derived average mass spectrum data sets for classification and characterisation of essential oils

(2019) Leo Lebanov et al.   TALANTA

Design and Development of Lubricating Material Database and Research on Performance Prediction Method of Machine Learning

(2019) Dan Jia et al.   Scientific Reports

Global discovery of stable and non-toxic hybrid organic-inorganic perovskites for photovoltaic systems by combining machine learning method with first principle calculations

(2019) Tianmin Wu et al.   Nano Energy

A machine-learning approach to predicting and understanding the properties of amorphous metallic alloys

(2019) Jie Xiong et al.   MATERIALS & DESIGN

OCPMDM: Online computation platform for materials data mining

(2018) Qing Zhang et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

AFLOW-ML: A RESTful API for machine-learning predictions of materials properties

(2018) Eric Gossett et al.   COMPUTATIONAL MATERIALS SCIENCE

Materials data validation and imputation with an artificial neural network

(2018) P.C. Verpoort et al.   COMPUTATIONAL MATERIALS SCIENCE

Multivariate modeling via artificial neural network applied to enhance methylene blue sorption using graphene-like carbon material prepared from edible sugar

(2018) Lakshmi Prasanna Lingamdinne et al.   JOURNAL OF MOLECULAR LIQUIDS

Applications of machine learning for facies and fracture prediction using Bayesian Network Theory and Random Forest: Case studies from the Appalachian basin, USA

(2018) Shuvajit Bhattacharya et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Machine learning for people detection in guidance functionality of enabling health applications by means of cascaded SVM classifiers

(2018) Alexandros Gavriilidis et al.   JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS

Speech emotion recognition based on feature selection and extreme learning machine decision tree

(2018) Zhen-Tao Liu et al.   NEUROCOMPUTING

Managing the computational cost of model selection and cross-validation in extreme learning machines via Cholesky, SVD, QR and eigen decompositions

(2018) Yiannis Kokkinos et al.   NEUROCOMPUTING

BP neural network based flexural strength prediction of open-porous Cu-Sn-Ti composites

(2018) Biao Zhao et al.   Progress in Natural Science-Materials International

BP neural network based flexural strength prediction of open-porous Cu-Sn-Ti composites

(2018) Biao Zhao et al.   Progress in Natural Science-Materials International

Crystal nucleation in metallic alloys using x-ray radiography and machine learning

(2018) Enzo Liotti et al.   Science Advances

Modified criterions for phase prediction in the multi-component laser-clad coatings and investigations into microstructural evolution/wear resistance of FeCrCoNiAlMox laser-clad coatings

(2018) Y.F. Juan et al.   APPLIED SURFACE SCIENCE

Property prediction and properties-to-microstructure inverse analysis of steels by a machine-learning approach

(2018) Zhi-Lei Wang et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Physical descriptor for the Gibbs energy of inorganic crystalline solids and temperature-dependent materials chemistry

(2018) Christopher J. Bartel et al.   Nature Communications

An imprecise extension of SVM-based machine learning models

(2018) Lev V. Utkin   NEUROCOMPUTING

The linear random forest algorithm and its advantages in machine learning assisted logging regression modeling

(2018) Yile Ao et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Evolution in microstructure and corrosion behavior of AlCoCrxFeNi high-entropy alloy coatings fabricated by laser cladding

(2018) Y.Q. Jiang et al.   JOURNAL OF ALLOYS AND COMPOUNDS

Noise reduction for near-infrared spectroscopy data using extreme learning machines

(2018) Pablo A. Henríquez et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning

(2018) Cheng Fan et al.   APPLIED ENERGY

Landslide spatial modeling: Introducing new ensembles of ANN, MaxEnt, and SVM machine learning techniques

(2017) Wei Chen et al.   GEODERMA

Computational development of the nanoporous materials genome

(2017) Peter G. Boyd et al.   Nature Reviews Materials

Machine learning unifies the modeling of materials and molecules

(2017) Albert P. Bartók et al.   Science Advances

Application of machine learning methods for the prediction of crystal system of cathode materials in lithium-ion batteries

(2016) M. Attarian Shandiz et al.   COMPUTATIONAL MATERIALS SCIENCE

ChemDataExtractor: A Toolkit for Automated Extraction of Chemical Information from the Scientific Literature

(2016) Matthew C. Swain et al.   Journal of Chemical Information and Modeling

A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM) forecasts using a GPR (Gaussian Process Regression) model

(2015) Jianzhou Wang et al.   ENERGY

Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines

(2015) Tarek Lajnef et al.   JOURNAL OF NEUROSCIENCE METHODS

A hybrid method based on extreme learning machine and k-nearest neighbor for cloud classification of ground-based visible cloud image

(2015) Min Xia et al.   NEUROCOMPUTING

An SVM-based machine learning method for the separation of alteration zones in Sungun porphyry copper deposit

(2013) Maliheh Abbaszadeh et al.   CHEMIE DER ERDE-GEOCHEMISTRY

Machine learning using Bernoulli mixture models: Clustering, rule extraction and dimensionality reduction

(2013) Mehreen Saeed et al.   NEUROCOMPUTING

Classification of diesel pool refinery streams through near infrared spectroscopy and support vector machines using C-SVC and ν-SVC

(2013) Julio Cesar L. Alves et al.   SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY

Landslide susceptibility assessment using SVM machine learning algorithm

(2011) Miloš Marjanović et al.   ENGINEERING GEOLOGY

Prediction of brake friction materials recovery performance using artificial neural networks

(2010) Dragan Aleksendrić et al.   TRIBOLOGY INTERNATIONAL

Prediction of mechanical properties in magnesia based refractory materials using ANN

(2009) N. Sinan Koksal   COMPUTATIONAL MATERIALS SCIENCE

Friction materials development by using DOE/RSM and artificial neural network

(2009) Guipu Xiao et al.   TRIBOLOGY INTERNATIONAL

Hybrid computational strategy based on ANN and GAPS: Application for identification of a non-linear model of composite material

(2008) David Hicham Bassir et al.   COMPOSITE STRUCTURES