Results 171 to 180 of about 1,266,861 (312)

What Do Large Language Models Know About Materials?

open access: yesAdvanced 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   +2 more
wiley   +1 more source

Compliance in Environmental Governance Requires Eenvironmental Knowledge Management in Developing Countries: The Liberian Case Study

open access: yes, 2005
This paper will commence with the definition and or explanation of environmental governance and environmental knowledge management. It will continue with the reasons why environmental knowledge management is required in developing countries and ...
Eben, Moses
core  

Electrochemical Evaluation of Compressed Selective Laser Melted AlSi7Mg and AlSi10Mg Alloys in Chloride Environment

open access: yesAdvanced Engineering Materials, EarlyView.
The corrosion performance of AlSi7Mg and AlSi10Mg alloys produced through selective laser melting (SLM) was examined under compressive stress in a chloride environment. Electrochemical analyses, including open‐circuit potential (OCP), potentiodynamic polarization (CPP), and electrochemical impedance spectroscopy (EIS), were complemented by scanning ...
Femi John Akinfolarin   +2 more
wiley   +1 more source

NFDI MatWerk Ontology (MWO): A BFO‐Compliant Ontology for Research Data Management in Materials Science and Engineering

open access: yesAdvanced Engineering Materials, EarlyView.
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi   +4 more
wiley   +1 more source

Intelligent Information System for Environmental Management

open access: yes, 2006
The development of an environmental management system according with ISO 14000 requirements can be a complex process that can be finished with unsatisfying results.
Tanasescu, Ana   +3 more
core  

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

open access: yesAdvanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed   +6 more
wiley   +1 more source

Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows

open access: yesAdvanced Engineering Materials, EarlyView.
A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba   +5 more
wiley   +1 more source

Environmental Modelling with Uncertainty

open access: yes, 2006
The characteristic feature of current environmental modelling is the complexity and uncertainty of its mathematical representation (uncertainty of formula). Imprecision of its input data is another characteristic feature, where it is not possible to omit
Hejc, Michal, Hrebicek, Jiri
core  

A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data

open access: yesAdvanced Engineering Materials, EarlyView.
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

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