Results 81 to 90 of about 49,660 (224)

Ultrafast Electron Transfer Coupled with a Proton Relay in an Anisotropic Dual S‐Scheme Heterojunction for Overcoming Kinetics Mismatch in H2O2 Photosynthesis

Advanced Science, EarlyView.
An anisotropic dual S‐scheme heterojunction (C3N4/SubPc‐1/C3N5) is constructed to overcome the electron–proton kinetics mismatch in photocatalytic H2O2 production. The imide bridge serves as a dual channel for ultrafast electron transfer and proton relay, synergistically enabling efficient dual‐pathway oxygen reduction and achieving a high H2O2 ...
Bing Wang, XiangBo Feng, Yao Liu, XinYi Wang, EnZhou Liu, YuZhen Zhao, ZongCheng Miao, Zhuo Li   +7 more
wiley   +1 more source

A Study of Some New Hermite–Hadamard Inequalities via Specific Convex Functions with Applications

Mathematics
Convexity plays a crucial role in the development of fractional integral inequalities. Many fractional integral inequalities are derived based on convexity properties and techniques.
Moin-ud-Din Junjua, Ather Qayyum, Arslan Munir, Hüseyin Budak, Muhammad Mohsen Saleem, Siti Suzlin Supadi   +5 more
doaj   +1 more source

High‐Throughput Screening and Characterization of Non‐Flammable Na‐Cl Solid Electrolytes

Advanced Electronic Materials, EarlyView.
A Na‐Cl solid electrolyte with high ionic conductivity is screened from a structural database using force‐field molecular dynamics (MD) simulations and density functional theory (DFT)‐MD calculations. Na3La5Cl18 is identified, synthesized, and characterized.
Naoto Tanibata, Naoki Nonaka, Daisuke Urushihara, Hayami Takeda, Ryo Kobayashi, Naoaki Kuwata, Masanobu Nakayama   +6 more
wiley   +1 more source

Exponentially $ E $-convex vector optimization problems

Journal of Industrial and Management Optimization
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Approximations and inequalities for the exponential beta function

Journal of Inequalities and Applications, 2019
In this paper, motivated by interest in simulating the expenditure patterns of construction projects, we introduce the mathematical concept of Exponential-Beta function by F(α,β):=∫01exp[xα(1−x)β]dx, $$ F ( \alpha ,\beta ) := \int _{0}^{1}\exp \bigl[ x^{\
Silvestru Sever Dragomir, Farzad Khosrowshahi   +1 more
doaj   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

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

Advanced 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

On the refinements of Jensen Mercer's inequality

Journal of Numerical Analysis and Approximation Theory, 2012
In this paper we give refinements of Jensen-Mercer's inequality and its generalizations and give applications for means. We prove \(n\)-exponential convexity of the functions constructed from these refinements. At the end we discuss some examples.
M. Adil Khan, Asif R. Khan, J. Pečarić
doaj   +2 more sources

n–polynomial exponential type p–convex function with some related inequalities and their applications

Heliyon, 2020
In this paper, the idea and its algebraic properties of n–polynomial exponential type p–convex function have been investigated. Authors prove new trapezium type inequality for this new class of functions.
Saad Ihsan Butt, Artion Kashuri, Muhammad Tariq, Jamshed Nasir, Adnan Aslam, Wei Gao   +5 more
doaj   +1 more source