Results 181 to 190 of about 3,621,297 (302)

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

A practice-oriented guide to statistical inference in linear modeling for non-normal or heteroskedastic error distributions. [PDF]

Behav Res Methods
Rajh-Weber H, Huber SE, Arendasy M.
europepmc   +1 more source

Hybrid Auxetic Architectures: Integrating Curvature‐Driven Design for Enhanced Mechanical Tunability and Structural Performance

Advanced Engineering Materials, EarlyView.
Curvature‐tuned auxetic lattices are designed, fabricated, and mechanically characterized to reveal how geometric curvature governs stretchability, stress redistribution, and Poisson's ratio evolution. Photoelastic experiments visualize stress pathways, while hyperelastic simulations quantify deformation mechanics.
Shuvodeep De, Giovanni Meli, Meysam Khaleghian, Anahita Emami   +3 more
wiley   +1 more source

Nonclassicality and Coherent Error Detection via Pseudo-Entropy. [PDF]

Entropy (Basel)
Katz A, Bloch S, Cohen E.
europepmc   +1 more source

Unique Performance Considerations for Printable Organic Semiconductor and Perovskite Radiation Detectors: Toward Consensus on Best Practice Evaluation

Advanced Functional Materials, EarlyView.
A lack of standard approaches for testing and reporting the performance of metal halide perovskites and organic semiconductor radiation detectors has resulted in inconsistent interpretation of performance parameters, impeding progress in the field. This Perspective recommends key metrics and experimental details, which are suggested for reporting in ...
Jessie A. Posar, Matthew Large, Andrea Ciavatti, Laura Basiricò, Beatrice Fraboni, Paul J. Sellin, Attila J. Mozer, Marco Petasecca, Matthew J. Griffith   +8 more
wiley   +1 more source

A new automatic forecasting method based on explainable deep dendritic artificial neural network. [PDF]

Sci Rep
Bas E, Egrioglu E.
europepmc   +1 more source

Lipid Nanoparticles for the Delivery of CRISPR/Cas9 Machinery to Enable Site‐Specific Integration of CFTR and Mutation‐Agnostic Disease Rescue

Advanced Functional Materials, EarlyView.
Lipid nanoparticles (LNPs) are optimized to co‐deliver Cas9‐encoding messenger RNA (mRNA), a single guide RNA (sgRNA) targeting the endogenous cystic fibrosis transmembrane conductance regulator (CFTR) gene, and homologous linear double‐stranded donor DNA (ldsDNA) templates encoding CFTR.
Ruth A. Foley, Paul G. Ayoub, Vrishti Sinha, Colin Juett, Alicia Sanoyca, Emily C. Duggan, Lindsay E. Lathrop, Priyanka Bhatt, Kevin Coote, Beate Illek, Brigitte N. Gomperts, Donald B. Kohn, Steven J. Jonas   +12 more
wiley   +1 more source

Simulation-based inference of cell migration dynamics in complex spatial environments. [PDF]

NPJ Syst Biol Appl
Arruda J, Alamoudi E, Mueller R, Vaisband M, Molkenbur R, Merrin J, Kiermaier E, Hasenauer J.   +7 more
europepmc   +1 more source

Patterning the Void: Combining L‐Systems with Archimedean Tessellations as a Perspective for Tissue Engineering Scaffolds

Advanced Functional Materials, EarlyView.
This study introduces a novel multi‐scale scaffold design using L‐fractals arranged in Archimedean tessellations for tissue regeneration. Despite similar porosity, tiles display vastly different tensile responses (1–100 MPa) and deformation modes. In vitro experiments with hMSCs show geometry‐dependent growth and activity. Over 55 000 tile combinations
Maria Kalogeropoulou, Kenny A. van Kampen, Pierpaolo Fucile, Carlos Mota, Lorenzo Moroni   +4 more
wiley   +1 more source

A new exponential family of distributions with applications to engineering and medical data. [PDF]

Sci Rep
Sapkota LP, Bam N, Kumar V.
europepmc   +1 more source