Prediction and Analysis of Tensile Properties of Austenitic Stainless Steel Using Artificial Neural Network

Predicting the Tensile Behaviour of Cast Alloys by a Pattern Recognition Analysis on Experimental Data

(2019) Cristiano Fragassa et al.   Metals

Physical metallurgy-guided machine learning and artificial intelligent design of ultrahigh-strength stainless steel

(2019) Chunguang Shen et al.   ACTA MATERIALIA

Hybrid Machine Learning Optimization Approach to Predict Hot Deformation Behavior of Medium Carbon Steel Material

(2019) Mohanraj Murugesan et al.   Metals

A machine learning approach for engineering bulk metallic glass alloys

(2018) Logan Ward et al.   ACTA MATERIALIA

Accelerated search for materials with targeted properties by adaptive design

(2016) Dezhen Xue et al.   Nature Communications

Mechanical properties of Austenitic Stainless Steel 304L and 316L at elevated temperatures

(2016) Raghuram Karthik Desu et al.   Journal of Materials Research and Technology-JMR&T

Machine Learning Strategy for Accelerated Design of Polymer Dielectrics

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

A Mathematical Formulation to Estimate the Effect of Grain Refiners on the Ultimate Tensile Strength of Al-Zn-Mg-Cu Alloys

(2015) Halil Kurt et al.   Metals

Identification of Potential Photovoltaic Absorbers Based on First-Principles Spectroscopic Screening of Materials

(2012) Liping Yu et al.   PHYSICAL REVIEW LETTERS

Microstructure informatics using higher-order statistics and efficient data-mining protocols

(2011) Surya R. Kalidindi et al.   JOM

Effect of Nb, Ti and cold deformation on microstructure and mechanical properties of austenitic stainless steels

(2010) Ahmed Ismail Zaky Farahat et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Effect of different environmental parameters on pitting behavior of AISI type 316L stainless steel: Experimental studies and neural network modeling

(2009) K.V.S. Ramana et al.   MATERIALS & DESIGN

Application of neural networks to predict the elevated temperature flow behavior of a low alloy steel

(2008) Y.C. Lin et al.   COMPUTATIONAL MATERIALS SCIENCE

Artificial neural network modeling of composition–process–property correlations in austenitic stainless steels

(2007) Sumantra Mandal et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING