Results 231 to 240 of about 111,464 (290)

Machine Learning‐Assisted Design and Performance Prediction of a Compact Dual‐Band Polarization‐Insensitive THz Metamaterial Absorber for Skin‐Cancer‐Related Refractive‐Index Sensing

open access: yesAdvanced Electronic Materials, EarlyView.
A compact QASRR‐based THz metamaterial absorber enables polarization‐insensitive dual‐band absorption and skin‐cancer‐related refractive‐index sensing through measurable resonance shifts. Field, surface‐current, and circuit analyses clarify the dual‐resonance mechanism, while StackNet‐assisted prediction accurately estimates the simulated absorption ...
Md. Murad Kabir Nipun   +5 more
wiley   +1 more source

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

open access: yesAdvanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin   +7 more
wiley   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

open access: yesAdvanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu   +6 more
wiley   +1 more source

Microneedling Versus Chemical Peels for Atrophic Acne Scars: A Systematic Review and Meta-Analysis. [PDF]

open access: yesCureus
Agu-Jefferson I   +4 more
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

open access: yesAdvanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen   +4 more
wiley   +1 more source

Biological use of molybdenum and tungsten stems back to 3.4 billion years ago. [PDF]

open access: yesNat Commun
Klos AS   +6 more
europepmc   +1 more source

Beyond Descriptor‐Based AI Design: Sp2‐Hybridized Branched Side Chains Enable Pre‐Aggregation–Driven Seeding Effects in Green‐Solvent‐Processed Organic Solar Cells

open access: yesAdvanced Energy Materials, EarlyView.
sp2‐hybridized branched side chains are introduced as a new molecular design for NFAs, YBOV, inducing strong solution‐state pre‐aggregation. This pre‐aggregation enables universal seeding motifs, highly ordered film growth, and overcoming the intrinsic current–voltage trade‐off, achieving 19.67% efficiency via green‐solvent processing beyond descriptor‐
Seokhwan Jeong   +14 more
wiley   +1 more source

Home - About - Disclaimer - Privacy