Results 111 to 120 of about 10,907,159 (259)
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
Meeting NCATE Standards Through Service-Learning: Diversity [PDF]
Over the past several years, college campuses across North America have seen an increase in the variety of service-learning projects integrated with academic course goals.
National Service-Learning in Teacher Education Partnership
core
The OntOMat ontology establishes a structured framework for polymer matrix fiber reinforced composite materials, integrating manufacturing processes, characterization methods, and multiscale design through the VDI/VDE 3682 formalized process description standard.
Nicolas Christ +19 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
Development education and international service-learning are approaches to education that have the potential to offer students an opportunity to develop their understanding and appreciation of global issues such as poverty and inequality. In this regard,
Ciaran O'Leary, Claire M McDonnell
doaj +1 more source
HEA interlayers offer a versatile route for joining high‐performance structural materials. Their compositional and structural design regulates interfacial reactions, suppresses brittle IMCs, and improves metallurgical bonding. Sandwich interlayers further integrate defect healing with precipitation strengthening, enabling improved strength–ductility ...
Lin Yuan +4 more
wiley +1 more source
Supporting AI Readiness Through Digital Workflows in Materials Science
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns +67 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
Service-Learning: International Teachers' Perspectives [PDF]
In this study, we explored the knowledge and perceptions of service-learning held by a diverse group of international teachers. Through focus group interviews, we found that the majority of participants desired to implement service-learning in their ...
Feinberg, Joseph R., O'Keefe, Jean
core
This dataset shows the original validation and standardization of the Questionnaire for the Self-Assessment of Service-Learning Experiences in Higher Education (QaSLu).
Roberto Sánchez-Cabrero +3 more
doaj +1 more source

