Development of artificial intelligence based model for the prediction of Young’s modulus of polymer/carbon-nanotubes composites

Development of user-friendly kernel-based Gaussian process regression model for prediction of load-bearing capacity of square concrete-filled steel tubular members

(2021) Tien-Thinh Le et al.   MATERIALS AND STRUCTURES

Effects of variability in experimental database on machine-learning-based prediction of ultimate load of circular concrete-filled steel tubes

(2021) Nang Xuan Ho et al.   MEASUREMENT

Nanoscale Effect Investigation for Effective Bulk Modulus of Particulate Polymer Nanocomposites Using Micromechanical Framework

(2021) Tien-Thinh Le et al.   Advances in Materials Science and Engineering

Prediction of axial load capacity of rectangular concrete-filled steel tube columns using machine learning techniques

(2021) Tien-Thinh Le et al.   ENGINEERING WITH COMPUTERS

An empirical model for bending capacity of defected pipe combined with axial load

(2021) Hieu Chi Phan et al.   INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING

Applying Bayesian Optimization for Machine Learning Models in Predicting the Surface Roughness in Single-Point Diamond Turning Polycarbonate

(2021) Van-Hai Nguyen et al.   MATHEMATICAL PROBLEMS IN ENGINEERING

Soft computing based closed form equations correlating L and N-type Schmidt hammer rebound numbers of rocks

(2021) Panagiotis G. Asteris et al.   Transportation Geotechnics

The Coarse Mesh Condensation Multiscale Method for parallel computation of heterogeneous linear structures without scale separation

(2020) Minh Vuong Le et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Probabilistic modeling of surface effects in nano-reinforced materials

(2020) Tien-Thinh Le   COMPUTATIONAL MATERIALS SCIENCE

Probabilistic investigation of the effect of stochastic imperfect interfaces in nanocomposites

(2020) Tien-Thinh Le   MECHANICS OF MATERIALS

Optimization design of rectangular concrete-filled steel tube short columns with Balancing Composite Motion Optimization and data-driven model

(2020) Huan Thanh Duong et al.   Structures

Predicting burst pressure of defected pipeline with Principal Component Analysis and adaptive Neuro Fuzzy Inference System

(2020) Hieu Chi Phan et al.   INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING

Artificial bee colony-based neural network for the prediction of the fundamental period of infilled frame structures

(2019) Panagiotis G. Asteris et al.   NEURAL COMPUTING & APPLICATIONS

A new form of a Halpin–Tsai micromechanical model for characterizing the mechanical properties of carbon nanotube-reinforced polymer nanocomposites

(2019) Mohammad Kazem Hassanzadeh-Aghdam et al.   BULLETIN OF MATERIALS SCIENCE

Challenges and opportunities of polymer design with machine learning and high throughput experimentation

(2019) Jatin N. Kumar et al.   MRS Communications

Neural Networks Are Promising Tools for the Prediction of the Viscosity of Unsaturated Polyester Resins

(2019) Julien Molina et al.   Frontiers in Chemistry

New frontiers for the materials genome initiative

(2019) Juan J. de Pablo et al.   npj Computational Materials

Radial Basis Function Neural Network-Based Modeling of the Dynamic Thermo-Mechanical Response and Damping Behavior of Thermoplastic Elastomer Systems

(2019) Ivan Kopal et al.   Polymers

Thermal characteristics of evacuated tube solar collectors with coil inside: An experimental study and evolutionary algorithms

(2019) Gholamabbas Sadeghi et al.   RENEWABLE ENERGY

Invasive Weed Optimization Technique-Based ANN to the Prediction of Rock Tensile Strength

(2019) Lei Huang et al.   Applied Sciences-Basel

Automatic recognition of asphalt pavement cracks using metaheuristic optimized edge detection algorithms and convolution neural network

(2018) Hoang Nhat-Duc et al.   AUTOMATION IN CONSTRUCTION

Crystal Structure Prediction via Deep Learning

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

Prediction of the Tensile Response of Carbon Black Filled Rubber Blends by Artificial Neural Network

(2018) Ivan Kopal et al.   Polymers

Strategies for accelerating the adoption of materials informatics

(2018) Logan Ward et al.   MRS BULLETIN

Machine learning material properties from the periodic table using convolutional neural networks

(2018) Xiaolong Zheng et al.   Chemical Science

Fulfilling the promise of the materials genome initiative with high-throughput experimental methodologies

(2017) M. L. Green et al.   Applied Physics Reviews

Prediction of thermal conductivity of polyvinylpyrrolidone (PVP) electrospun nanocomposite fibers using artificial neural network and prey-predator algorithm

(2017) Waseem S. Khan et al.   PLoS One

From Organized High-Throughput Data to Phenomenological Theory using Machine Learning: The Example of Dielectric Breakdown

(2016) Chiho Kim et al.   CHEMISTRY OF MATERIALS

Classifying Crystal Structures of Binary Compounds AB through Cluster Resolution Feature Selection and Support Vector Machine Analysis

(2016) Anton O. Oliynyk et al.   CHEMISTRY OF MATERIALS

Mechanical properties of single-walled carbon nanotube reinforced polymer composites with varied interphase’s modulus and thickness: A finite element analysis study

(2016) Dilip Banerjee et al.   COMPUTATIONAL MATERIALS SCIENCE

Stochastic continuum modeling of random interphases from atomistic simulations. Application to a polymer nanocomposite

(2016) T.T. Le et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Effect of various material parameters on barrier properties of high-density polyethylene/polyamide 6/clay nanocomposites

(2016) Mehdi Moghri et al.   JOURNAL OF ELASTOMERS AND PLASTICS

Boosting materials modelling

(2016)   NATURE MATERIALS

Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach

(2016) Rafael Gómez-Bombarelli et al.   NATURE MATERIALS

Optimization of mechanical properties of PP/EPDM/ clay nanocomposite fabricated by friction stir processing with response surface methodology and neural networks

(2016) Mohammad Reza Nakhaei et al.   POLYMER COMPOSITES

YCuTe2: a member of a new class of thermoelectric materials with CuTe4-based layered structure

(2016) Umut Aydemir et al.   Journal of Materials Chemistry A

Machine Learning Strategy for Accelerated Design of Polymer Dielectrics

(2016) Arun Mannodi-Kanakkithodi et al.   Scientific Reports

The Electrolyte Genome project: A big data approach in battery materials discovery

(2015) Xiaohui Qu et al.   COMPUTATIONAL MATERIALS SCIENCE

Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation

(2015) Alex Goldstein et al.   JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS

Generating Information-Rich High-Throughput Experimental Materials Genomes using Functional Clustering via Multitree Genetic Programming and Information Theory

(2015) Santosh K. Suram et al.   ACS Combinatorial Science

A Neural Network Model for Predicting the Dielectric Permittivity of Epoxy- Aluminum Nanocomposite and Its Experimental Validation

(2015) Siny Paul et al.   IEEE Transactions on Components Packaging and Manufacturing Technology

Remarks on the recent progress of Materials Genome Initiative

(2015) Xiao-Gang Lu   Science Bulletin

The Materials Genome Initiative, the interplay of experiment, theory and computation

(2014) Juan J. de Pablo et al.   CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE

Multiscale micromechanical modeling of the constitutive response of carbon nanotube-reinforced structural adhesives

(2014) J.M. Wernik et al.   INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES

Mechanical properties of carbon nanotube/polymer composites

(2014) B. Arash et al.   Scientific Reports

Stochastic framework for modeling the linear apparent behavior of complex materials: Application to random porous materials with interphases

(2013) J. Guilleminot et al.   ACTA MECHANICA SINICA

Computational modeling of elastic properties of carbon nanotube/polymer composites with interphase regions. Part II: Mechanical modeling

(2013) Fei Han et al.   COMPUTATIONAL MATERIALS SCIENCE

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

(2013) Anubhav Jain et al.   APL Materials

Improved Dispersion of Carbon Nanotubes in Polymers at High Concentrations

(2012) Chao-Xuan Liu et al.   Nanomaterials

Numerical characterization of CNT-based polymer composites considering interface effects

(2010) Hossein Golestanian et al.   COMPUTATIONAL MATERIALS SCIENCE

Carbon nanotube–polymer composites: Chemistry, processing, mechanical and electrical properties

(2009) Zdenko Spitalsky et al.   PROGRESS IN POLYMER SCIENCE