Results 101 to 110 of about 5,821,170 (252)

On Unbiased Estimation of Positive Integral Powers of the Natural Parameter in Exponential Families

open access: yes
We explore the structure of one-parameter exponential families admitting an unbiased estimator for a positive integral power of the natural parameter. It is seen that only exponential families dominated by Lebesgue measure can have this property.
Ludwig Baringhaus
core   +1 more source

Comparative Insights and Overlooked Factors of Interphase Chemistry in Alkali Metal‐Ion Batteries

open access: yesAdvanced Energy Materials, EarlyView.
This review presents a comparative analysis of Li‐, Na‐, and K‐ion batteries, focusing on the critical role of electrode–electrolyte interphases. It especially highlights overlooked aspects such as SEI/CEI misconceptions, binder effects, and self‐discharge relevance, emphasizing the limitations of current understanding and offering strategies for ...
Changhee Lee   +3 more
wiley   +1 more source

Emerging Materials and Future Strategies for Solid Oxide Electrochemical Cells

open access: yesAdvanced Energy Materials, EarlyView.
Solid oxide electrochemical cells operate under strongly coupled electrochemical and thermodynamic conditions, where performance is constrained by interactions among crystal structure, defect chemistry, and interfacial evolution. This review, based on a structure‐defect‐property‐durability framework, reveals the roles of lattice symmetry and defect ...
Qiuchun Lu   +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

A Descriptor for Non‐Arrhenius Ion Transport Enables Design of Sulfide Superionic Conductors

open access: yesAngewandte Chemie, EarlyView.
A curated database of sulfide electrolytes reveals widespread non‐Arrhenius ion transport. Meyer–Neldel deviation (MND) quantifies this behavior, distinguishes low‐conductivity and superionic regimes, and guides composition screening. An experimentally validated candidate exhibits room‐temperature conductivity of 7.21 mS cm−1, an apparent activation ...
Han Zhou   +6 more
wiley   +2 more sources

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Ionic Liquid Electrolytes for Extreme Temperature Conditions: Challenges and Perspective

open access: yesAngewandte Chemie, EarlyView.
Ionic liquids (ILs) have gained great attention as safe electrolyte components in recent years. This review elucidates the temperature effects on IL‐based electrolytes from molecular configurations, physicochemical properties, and interfacial chemistry, raises the challenges and design strategies operating at low‐ and HT, providing valuable guidance ...
En Xie   +11 more
wiley   +2 more sources

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

open access: yesAdvanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez   +4 more
wiley   +1 more source

Large Language Model‐Based Chatbots in Higher Education

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci   +4 more
wiley   +1 more source

Self‐Assembled Pt(II) Complexes Boost Up Stem Cell Proliferation and Accelerate Metamorphosis in Living Organisms

open access: yesAngewandte Chemie, EarlyView.
Pt1, an organometallic platinum‐based complex, act as a modulator of redox homeostasis in cnidarians, regulating cellular functions and life‐cycle dynamics. In Nematostella vectensis, it mitigates oxidative stress, strengthens detox systems and accelerates development.
Giuseppina Tommasini   +13 more
wiley   +2 more sources

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