Results 41 to 50 of about 212,411 (244)
ExponentialFamilyManifolds.jl: Representing exponential families as Riemannian manifolds
ExponentialFamilyManifolds.jl implements exponential family natural parameter spaces as Riemannian manifolds, enabling geometric optimization over probability distributions.
Mykola Lukashchuk +4 more
semanticscholar +1 more source
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source
Determining the lifetime distribution using fractional moments with maximum entropy
Here we propose a model-free, non-parametric method to solve an ill-posed inverse problem arising in several fields. It consists of determining a probability density of the lifetime, or the probability of survival of an individual, from the knowledge of ...
Henryk Gzyl, Silvia Mayoral
doaj +1 more source
Limited chemical diversity of nucleic acid libraries has long been suspected to be a major constraining factor in the overall success of SELEX (Systematic Evolution of Ligands by EXponential enrichment).
John C Rohloff +6 more
doaj +1 more source
ABSTRACT The accelerating expansion of data‐centric technologies is sharply increasing the energy burden of information storage, placing unprecedented pressure on the efficiency of magnetic switching. Conventional field‐driven reversal, once the foundation of magnetic memory, has become impractical in modern architectures due to its high energy cost ...
Mohammad H. Badarneh +2 more
wiley +1 more source
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Magnetic particles are organized into layered architectures by combining shear flow and magnetic fields, with the resulting structures governed by appropriate Mason numbers. The programmed assemblies provide spatial guidance for cell placement, linking field‐controlled self‐assembly, flow‐induced structuring and biological organization.
Guillermo Camacho +5 more
wiley +1 more source
Recent Advances in Ferrite‐Based Materials for Biomedical Applications: A Comprehensive Review
Ferrite nanoplatforms are presented as tunable biomedical materials in which synthesis control, cation engineering, defect/morphology regulation, and surface functionalization govern structure–property–bioactivity relationships. These design strategies enable multifunctional applications including MRI contrast, magnetic hyperthermia, targeted drug ...
Pramod D. Mhase +6 more
wiley +1 more source
ABSTRACT Molybdenum disulfide (MoS2) has attracted attention as a promising material due to the growing demand for environmentally friendly, cost‐effective, and efficient water treatment techniques. With its physicochemical characteristics, this stratified bidimensional material allows it to be highly effective in adsorption and catalytic performance ...
Pariksha Bishnoi +4 more
wiley +1 more source

