Results 111 to 120 of about 337,499 (266)
Self‐Cleaning Sensor Surfaces for Long‐Term Environmental Monitoring
Long‐term use of unattended outdoor sensors without soiling or biofouling is achieved through generation of a micro‐ and nanorough cuvette surface by combing hydrophobic nanoparticles with fluorinated polymers, crosslinked and surface‐attached through CHic chemistry. The coating demonstrates self‐cleaning behavior and prolonged outdoor stability, which
Sanam Kumari Rajak +4 more
wiley +1 more source
Entropy‐Driven Design of Low‐Melting‐Point Alloys via Compositionally Complex Strategy
Conventional low‐melting‐point alloys (LMPAs) are limited by a narrow compositional space and inherent property trade‐offs. This review presents an entropy‐driven design strategy that overcomes these limitations, ushering in a new class of low‐melting‐point compositionally complex alloys (LMCCAs).
Yinghui Shang +6 more
wiley +1 more source
Design of a Multistable Finger Prosthesis with Programmable Metamaterials
This research article shows the development of a multistable programmble metamaterial for the use as a finger prosthesis. The material was designed on different hierarchical levels where the influence of geometrical parameters and combination of mechanical elements was explored.
Franziska Wenz +5 more
wiley +1 more source
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source
Feasibility and Limitations of the Advanced Replica Process for Bioactive Glasses
Periodic 3D‐printed Kelvin‐cell templates enable a controlled advanced replica process for fabricating highly porous glass lattices. Across P45K9, 45S5, and 13–93, material‐dependent differences in coating, burnout, and shrinkage lead to distinct strut morphologies, while comparable final porosities of 83%–88% are retained.
Swantje Funk +4 more
wiley +1 more source
Toward Full Interoperability in Materials Science: Integrating Workflows With Knowledge Graphs
The connection of conceptual workflow design, portable execution, and ontology‐based semantics leading to provenance‐rich knowledge graphs are main contributors to interoperability in materials science and a prerequisite to AI‐assisted orchestration and for interoperable Materials Acceleration Platforms.
Jan Janssen +14 more
wiley +1 more source
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source
Additively manufactured AlCrFe2Ni2 with contrasting BCC/B2‐dominant and lamellar FCC + BCC/B2 microstructures exhibits the same pressure‐induced BCC/B2 → HCP transformation. Under laser heating at high pressure, HCP is destabilized, and a cubic BCC/B2 + FCC assemblage is recovered, while the lower‐scan‐speed microstructure transforms at a lower ...
Raimundas Sereika +5 more
wiley +1 more source
Biomass Native Structure Into Functional Carbon‐Based Catalysts for Fenton‐Like Reactions
This study indicates that eight biomasses with 2D flaky and 1D acicular structures influence surface O types, morphology, defects, N doping, sp2 C, and Co nanoparticles loading in three series of carbon, N‐doped carbon, and cobalt/graphitic carbon. This work identifies how these structural factors impact catalytic pathways, enhancing selective electron
Wenjie Tian +7 more
wiley +1 more source

