Computational microstructure characterization and reconstruction: Review of the state-of-the-art techniques
Building sensible processing-structure-property (PSP) links to gain fundamental insights and
understanding of materials behavior has been the focus of many works in computational …
understanding of materials behavior has been the focus of many works in computational …
Guiding the design of heterogeneous electrode microstructures for Li‐ion batteries: microscopic imaging, predictive modeling, and machine learning
Electrochemical and mechanical properties of lithium‐ion battery materials are heavily
dependent on their 3D microstructure characteristics. A quantitative understanding of the …
dependent on their 3D microstructure characteristics. A quantitative understanding of the …
Bayesian optimization for materials design with mixed quantitative and qualitative variables
Abstract Although Bayesian Optimization (BO) has been employed for accelerating materials
design in computational materials engineering, existing works are restricted to problems …
design in computational materials engineering, existing works are restricted to problems …
Machine-learning-assisted de novo design of organic molecules and polymers: opportunities and challenges
Organic molecules and polymers have a broad range of applications in biomedical,
chemical, and materials science fields. Traditional design approaches for organic molecules …
chemical, and materials science fields. Traditional design approaches for organic molecules …
Photonics for photovoltaics: Advances and opportunities
Photovoltaic systems have reached impressive efficiencies, with records in the range of 20–
30% for single-junction cells based on many different materials, yet the fundamental …
30% for single-junction cells based on many different materials, yet the fundamental …
Harnessing structural stochasticity in the computational discovery and design of microstructures
This paper presents a deep generative model-based design methodology for tailoring the
structural stochasticity of microstructures. Although numerous methods have been …
structural stochasticity of microstructures. Although numerous methods have been …
Self-assembly of Au nano-islands with tuneable organized disorder for highly sensitive SERS
Aggregates of disordered metallic nano-clusters exhibiting long-range organized fractal
properties are amongst the most efficient scattering enhancers, and they are promising as …
properties are amongst the most efficient scattering enhancers, and they are promising as …
Efficient light-trapping in ultrathin GaAs solar cells using quasi-random photonic crystals
J Buencuerpo, TE Saenz, M Steger, M Young… - Nano Energy, 2022 - Elsevier
Ultrathin solar cells reduce material usage and allow the use of lower-quality materials
thanks to their one order of magnitude smaller thickness than their conventional …
thanks to their one order of magnitude smaller thickness than their conventional …
Transparent quasi-random structures for multimodal light trapping in ultrathin solar cells with broad engineering tolerance
Waveguide modes are well-known to be a valuable light-trapping resource for absorption
enhancement in solar cells. However, their scarcity in the thinnest device stacks …
enhancement in solar cells. However, their scarcity in the thinnest device stacks …
Over 65% sunlight absorption in a 1 μm Si slab with hyperuniform texture
N Tavakoli, R Spalding, A Lambertz, P Koppejan… - ACS …, 2022 - ACS Publications
Thin, flexible, and invisible solar cells will be a ubiquitous technology in the near future.
Ultrathin crystalline silicon (c-Si) cells capitalize on the success of bulk silicon cells while …
Ultrathin crystalline silicon (c-Si) cells capitalize on the success of bulk silicon cells while …