Results 131 to 140 of about 3,170,729 (273)
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
The documentation of component manufacture has become an essential part of today's production processes, especially for the analysis and optimization of production or component design with regard to structural performance, economic efficiency, and sustainability.
Björn Denker +4 more
wiley +1 more source
What Do Large Language Models Know About Materials?
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 +2 more
wiley +1 more source
A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source
PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science
Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley +1 more source
Optimization of regulatory DNA with active learning. [PDF]
Shen Y, Kudla G, Oyarzún DA.
europepmc +2 more sources
A Topology Optimization Framework for the Inverse Design of Nonlinear Mechanical Metamaterials
This work uses topology optimization to design unit cells for mechanical metamaterials with a prescribed nonlinear stress–strain response. The framework adds contact and postbuckling modeling to synthesize microstructures for three highly nonlinear responses, including pseudoductile behavior, monostable with snap‐through buckling, and bistable ...
Charlie Aveline +2 more
wiley +1 more source
The layer‐by‐layer (LbL) assembly of coordination solids, enabled by the surface‐mounted metal‐organic framework (SURMOF) platform, is on the cusp of generating the organic counterpart of the epitaxy of inorganics. The programmable and sequential SURMOF protocol, optimized by machine learning (ML), is suited for accessing high‐quality thin films of ...
Zhengtao Xu +2 more
wiley +1 more source
Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana +2 more
wiley +1 more source
Selective Benzene Capture by Metal‐Organic Frameworks
Metal‐organic frameworks (MOFs) hold significant potential for capturing benzene from air emissions and hydrocarbon mixtures in liquid phases. This capability stems from their precisely engineered structures, versatile chemistries, and diverse binding interactions.
Zongsu Han +4 more
wiley +1 more source

