Results 111 to 120 of about 1,016,972 (289)
This study establishes an interpretable machine learning framework that disentangles the intrinsic molecular efficacy of passivators from experimental platform effects—enabling unbiased, high‐throughput discovery of effective perovskite surface modifiers.
Jing Zhang +5 more
wiley +1 more source
A ballean is a set endowed with some family of subsets which are called the balls. The properties of the family of balls are postulated in such a way that the balleans can be considered as a natural asymptotic counterparts of the uniform topological ...
Ivan V. Protasov
doaj +1 more source
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai +3 more
wiley +1 more source
Impedance of Nonelectroneutral Solid Electrolyte Interphases With Nanopores: A Theoretical Model
Physical modeling reveals that often‐neglected non‐electroneutrality and nanopores in the solid‐electrolyte interphase (SEI) govern the impedance behavior. Under nonreactive conditions, the low‐frequency constant‐phase element (CPE) phenomenon can be attributed to the nonelectroneutral local conditions in the SEI.
Chenkun Li, Jun Huang
wiley +1 more source
Low‐Power Control Of Resistance Switching Transitions in First‐Order Memristors
Joule losses are a serious concern in modern integrated circuit design. In this regard, minimizing the energy necessary for programming memristors should be handled with care. This manuscript presents an optimal control framework, allowing to derive energy‐efficient programming voltage protocols for resistance switching devices. Following this approach,
Valeriy A. Slipko +3 more
wiley +1 more source
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
Sustainable Productivity Growth in Agriculture: The Role of Shifts in R&D Investments and Technology
ABSTRACT The objective of the paper is to evaluate the long‐term prospects of sustainable productivity growth linked to plausible assumptions on public agricultural R&D investments as the key productivity driver. Second, it investigates the role of changing R&D focus from yield maximization to input saving technologies (fertilizers and pesticides). The
Zuzana Smeets Křístková +4 more
wiley +1 more source
Double asymptotic inequalities for the generalized Wallis ratio
Asymptotic estimates for the generalized Wallis ratio \(W^*(x):=\frac{1}{\sqrt{\pi}}\cdot\frac{\Gamma(x+\frac{1}{2})}{\Gamma(x+1)}\) are presented for \(x\in\mathbb{R}^+\) on the basis of Stirling's approximation formula for the \(\Gamma\) function.
Vito Lampret
doaj +1 more source
ABSTRACT In recent decades, agriculture has become increasingly concentrated through horizontal mergers and acquisitions via corporate entities, and policy makers are concerned this will be exacerbated by the aging population of farm operators. To reduce market concentration in agriculture, many states have enacted policies to entice new prospective ...
Justin M. Ross +2 more
wiley +1 more source
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openaire +2 more sources

