Discovery and optimization of materials using evolutionary approaches
Materials science is undergoing a revolution, generating valuable new materials such as
flexible solar panels, biomaterials and printable tissues, new catalysts, polymers, and …
flexible solar panels, biomaterials and printable tissues, new catalysts, polymers, and …
TMM-Fast, a transfer matrix computation package for multilayer thin-film optimization: tutorial
Achieving the desired optical response from a multilayer thin-film structure over a broad
range of wavelengths and angles of incidence can be challenging. An advanced thin-film …
range of wavelengths and angles of incidence can be challenging. An advanced thin-film …
Optimization of machining parameters to minimize surface roughness using integrated ANN-GA approach
The surface roughness is a widely used index of product quality in terms of precision fit of
mating surfaces, fatigue life improvement, corrosion resistance, aesthetics, etc. Surface …
mating surfaces, fatigue life improvement, corrosion resistance, aesthetics, etc. Surface …
Multilayer optical thin film design with deep Q learning
Multilayer optical film plays a significant role in broad fields of optical application. Due to the
nonlinear relationship between the dispersion characteristics of optical materials and the …
nonlinear relationship between the dispersion characteristics of optical materials and the …
Implicit and intuitive grasp posture control for wearable robotic fingers: a data-driven method using partial least squares
FY Wu, HH Asada - IEEE Transactions on Robotics, 2016 - ieeexplore.ieee.org
Functionality of a human hand can be augmented with wearable robotic fingers to enable
gras** and manipulation of objects with a single hand. Such technology will have …
gras** and manipulation of objects with a single hand. Such technology will have …
Tailoring the mechanical properties of 3D microstructures: A deep learning and genetic algorithm inverse optimization framework
Materials-by-design has been historically challenging due to complex process-
microstructure-property relations. Conventional analytical or simulation-based approaches …
microstructure-property relations. Conventional analytical or simulation-based approaches …
[PDF][PDF] Perspective: Inverse methods for material design
arxiv:1405.4060v1 [cond-mat.mtrl-sci] 16 May 2014 Page 1 Perspective: Inverse methods
for material design Avni Jain,1 Jonathan A. Bollinger,1 and Thomas M. Truskett1, a) …
for material design Avni Jain,1 Jonathan A. Bollinger,1 and Thomas M. Truskett1, a) …
Prediction and construction of energetic materials based on machine learning methods
X Zang, X Zhou, H Bian, W **, X Pan, J Jiang… - Molecules, 2022 - mdpi.com
Energetic materials (EMs) are the core materials of weapons and equipment. Achieving
precise molecular design and efficient green synthesis of EMs has long been one of the …
precise molecular design and efficient green synthesis of EMs has long been one of the …
[LIBRO][B] Data-driven evolutionary modeling in materials technology
N Chakraborti - 2022 - taylorfrancis.com
Due to efficacy and optimization potential of genetic and evolutionary algorithms, they are
used in learning and modeling especially with the advent of big data related problems. This …
used in learning and modeling especially with the advent of big data related problems. This …
[HTML][HTML] Multi-objective optimization and modeling of age hardening process using ANN, ANFIS and genetic algorithm: Results from aluminum alloy A356/cow horn …
CC Nwobi-Okoye, BQ Ochieze, S Okiy - Journal of Materials Research and …, 2019 - Elsevier
This study reports on the modeling and multi objective optimization of age hardening
process parameters using artificial neural network (ANN) and adaptive neuro-fuzzy …
process parameters using artificial neural network (ANN) and adaptive neuro-fuzzy …