Data‐Driven Materials Science for Energy‐Sustainable Applications
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
A multiplatform chromatography-mass spectrometry dataset for targeted and suspect screening of pollutants. [PDF]
Zhou H +6 more
europepmc +1 more source
Closed‐Loop Solid‐State Synthesis Planning for Materials Discovery With Large Language Models
Leveraging literature data, we build a large‐language‐model‐driven workflow that extracts synthesis steps from 4407 papers, retrieves similar precedents, and generates candidate solid‐state synthesis recipes. The system benchmarks against ground‐truth and then operates in a closed loop with experiments to synthesize oxy‐selenide electrolyte materials ...
Dong Won Jeon +9 more
wiley +1 more source
Is Prospective Memory Monitoring Governed by Dual Processes of Initiating a Retrieval Mode and Checking for Targets? A Conceptual Replication and Extension of Guynn (2003). [PDF]
Valdez MR, Bugg JM.
europepmc +1 more source
Fact-Checking Large Language Model Responses to a Health Care Prompt: Comparative Study. [PDF]
Ryan P, Davoren O, Elwyn G.
europepmc +1 more source
Applying the Rules of Evidence to Expert Testimony About Risk. [PDF]
Slobogin C.
europepmc +1 more source
Crack/cocaine use to manage xylazine exposure in fentanyl in Connecticut: findings from a convergent mixed methods study. [PDF]
Hill K +10 more
europepmc +1 more source
Comparing the Accuracy of Patient-Perceived Fever, Manual Fever Checking, and Non-Contact Frontal Infrared Thermometer; A Cross-sectional Study. [PDF]
Shabani-Kakroudi M +8 more
europepmc +1 more source

