Results 131 to 140 of about 80,670 (263)

Silicon Nitride Resistive Memories

open access: yesAdvanced Electronic Materials, EarlyView.
Amorphous SiNx is an attractive resistance switching material for ReRAM applications due to its physicochemical properties, such as humidity resistance, low oxygen diffusivity, and is used as a metal diffusion blocker. By modifying the ratio between N and Si atoms, the microstructure of the SiNx is affected, rendering it possible to change the ...
Alexandros‐Eleftherios Mavropoulis   +7 more
wiley   +1 more source

Assessing the feasibility of machine learning for ancient DNA age prediction: Limitations and insights. [PDF]

open access: yesBiol Methods Protoc
Kazanskii M   +5 more
europepmc   +1 more source

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

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

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

open access: yesAdvanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park   +19 more
wiley   +1 more source

Understanding Egg Price Volatility and Policy Implications in the U.S. With Machine Learning

open access: yesApplied Economic Perspectives and Policy, EarlyView.
ABSTRACT Eggs are an inexpensive and sustainable source of proteins, but volatility in the U.S. egg prices has intensified in recent years, raising concerns over food affordability and market stability. This study examines the drivers of U.S. egg price dynamics over 2004–2025 using a two‐stage framework that combines LASSO‐based variable selection with
Xuemei Zhao   +3 more
wiley   +1 more source

Rural Labor Supply and Economic Opportunities: Commuting, Migration, Tariffs, and Immigration

open access: yesApplied Economic Perspectives and Policy, EarlyView.
ABSTRACT Some rural counties remain dependent on agricultural or manufacturing jobs, but an increasing proportion have diversified economics. Rural counties also differ in their abilities to commute to an urban market characterized by higher wages and labor productivity.
Peter F. Orazem, Mary C. Ahearn
wiley   +1 more source

Solid–liquid equilibria in the LiOH–ethanol–water system: Solubility measurements and thermodynamic modeling

open access: yesAIChE Journal, EarlyView.
Abstract The demand for LiOH is driven by the growth of the electric vehicle industry. Evaporative crystallization of LiOH·H2O is energy intensive, whereas ethanol‐based antisolvent crystallization has emerged as a more sustainable alternative. From a process design perspective, the crystallization yield depends on the ethanol dosage, and thermodynamic
Xiaoqi Xu   +3 more
wiley   +1 more source

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