Results 91 to 100 of about 18,424,037 (238)

Polymeric Sorbents as Energy‐Efficient Alternative to Cryogenic Distillation for Light Hydrocarbon Purification

open access: yesAdvanced Materials, EarlyView.
The transition from cryogenic distillation to polymeric sorbents for light hydrocarbon purification is crucial for energy and environmental sustainability. The polymeric sorbents are engineered to separate gas mixtures based on their specific properties.
Kelechi Festus   +9 more
wiley   +1 more source

Tight Bounds for Joint Distribution Functions of Order Statistics Under k-Independence

open access: yes
The present study investigates the problem of determining sharp bounds for key reliability and distributional characteristics associated with order statistics.
Okolewski, Andrzej   +3 more
core   +1 more source

Data‐Driven Materials Science for Energy‐Sustainable Applications

open access: yesAdvanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

Testing the martingale difference hypothesis using integrated regression functions. [PDF]

open access: yes
An omnibus test for testing a generalized version of the martingale difference hypothesis (MDH) is proposed. This generalized hypothesis includes the usual MDH, testing for conditional moments constancy such as conditional homoscedasticity (ARCH effects)
Velasco, Carlos, Escanciano, Juan Carlos
core  

Exact goodness-of-fit tests for censored dats [PDF]

open access: yes, 2009
The statistic introduced in Fortiana and Grané (2003) is modified so that it can be used to test the goodness-of-fit of a censored sample, when the distribution function is fully specified.
Grané Chávez, Aurea
core   +1 more source

S‐Nitrosothiols as Thiol‐Protecting Groups for Controlled Thiol‐Maleimide Crosslinking of Homogeneous Soft Hydrogels

open access: yesAdvanced Materials, EarlyView.
Rapid thiol‐maleimide addition frequently outpaces mixing, resulting in heterogeneous hydrogels. S‐nitrosothiols act as thiol‐protecting groups, allowing uniform mixing with maleimide‐functionalized polymers before gelation. Sodium thiosulfate or sodium ascorbate then regenerates thiols on demand, triggering controlled thiol‐maleimide crosslinking ...
Julian A. Serna   +7 more
wiley   +1 more source

Percolation‐Driven β‐Relaxation Enables Resonant Acceleration of Crystallization in Amorphous Phase‐Change Materials

open access: yesAdvanced Materials, EarlyView.
Mobile‐atom percolation underlying β‐relaxations fundamentally dictates the crystallization pathways of phase‐change materials. High‐frequency ultrasonic excitation dynamically modulates this critical mobility percolation network, substantially accelerating the crystallization process.
Yu‐Yao Liu   +11 more
wiley   +1 more source

1T‐to‐2H Phase Evolution During Epitaxial Growth of Transition Metal Dichalcogenides

open access: yesAdvanced Materials, EarlyView.
During MOCVD growth of MoS2 and WSe2, a transient metallic 1T phase emerges in early, edge‐rich, chalcogen‐deficient domains and declines as the films ultimately coalesce as 2H material. Together, experiments and ReaxFF simulations link domain size, edge stoichiometry, and vacancies to this evolution.
Andrew R. Graves   +8 more
wiley   +1 more source

Empirical likelihood estimators for the error distribution in nonparametric regression models [PDF]

open access: yes
The aim of this paper is to show that existing estimators for the error distribution in nonparametric regression models can be improved when additional information about the distribution is included by the empirical likelihood method.
Kiwitt, Sebastian   +2 more
core  

Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models

open access: yesAdvanced Materials, EarlyView.
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng   +24 more
wiley   +1 more source

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