Results 81 to 90 of about 39,022 (281)

Polymorph‐Specific Electronic Transduction in WO3 during Molecular Sensing

Advanced Materials, EarlyView.
Metal‐oxide polymorphs with similar surface chemistry can nevertheless exhibit distinct sensing properties. In γ‐ and ε‐WO3, analyte adsorption appears comparable; yet, only ε‐WO3 induces a pronounced lattice electronic perturbation that accommodates charge in sub‐conduction band minimum states.
Matteo D'Andria, Meng Yin, Stefan Neuhauser, Vlasis G. Mavrantzas, Ying Chen, Ken Suzuki, Andreas T. Güntner   +6 more
wiley   +1 more source

A New Three-Parameter Flexible Unit Distribution and Its Quantile Regression Model

IEEE Access
This paper introduces a novel Poisson-unit-Weibull (PUW) distribution, which is defined on a unit domain and characterized by three parameters. The PUW distribution is capable of accommodating diverse non-monotone failure rates.
Mustapha Muhammad, Badamasi Abba, Jinsen Xiao, Najwan Alsadat, Farrukh Jamal, Mohammed Elgarhy   +5 more
doaj   +1 more source

Bottom‐Up Programming of Cell States in Cancer Organoids with Defined Synthetic Adhesion Cues

Advanced Materials, EarlyView.
A bottom‐up biomaterial platform is developed to program transcriptomic states in pancreatic cancer organoids by tuning adhesion cues within synthetic matrices. By combining a Design of Experiments framework with multiobjective optimization, matrix compositions are identified that enrich specific cellular programs like EMT.
Ali Nadernezhad, Verena J. Kast, Dagmar Pette, Franziska Baenke, Daniel E. Stange, Carsten Werner, Daniela Loessner   +6 more
wiley   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Semiparametric distribution regression with instruments and monotonicity

Labour Economics, 2022
This paper proposes IV-based estimators for the semiparametric distribution regression model in the presence of an endogenous regressor, which are based on an extension of IV probit estimators. We discuss the causal interpretation of the estimators and two methods (monotone rearrangement and isotonic regression) to ensure a monotonically increasing ...
openaire   +2 more sources

Influence of Carbon Nanoparticles on Electrically Induced Wear of Grease‐Lubricated Steels

Advanced Materials Interfaces, EarlyView.
When an electric current enters a pair of rubbing surfaces, enormous damage takes place. In this research, how such damage occurs in the presence of protective grease and the mitigation with added carbon nanoparticles, were investigated. It was discovered that those particles regulate transport and interfacial electrical stability of the grease ...
Mohammad Humaun Kabir, Darrius Dias, Jacob Bons, MD Wasek Foysal, Evan Johnson, Joe Kosmoski, Hong Liang   +6 more
wiley   +1 more source

Testing strict monotonicity in nonparametric regression [PDF]

A new test for strict monotonicity of the regression function is proposed which is based on a composition of an estimate of the inverse of the regression function with a common regression estimate. This composition is equal to the identity if and only if
Birke, Melanie, Dette, Holger
core  

Ductility Tuning via Cluster Network Characteristics of Porous Components

Advanced Materials Technologies, EarlyView.
Network optimization via cluster characteristics induced by interaction of stress concentration is proposed, demonstrating increased cluster size and dispersion in non‐uniform porous components. The optimized structures exhibit, for the first time, that enhanced ductility and damage progression is controllable through zigzag cluster network designed by
Ryota Toyoba, Yuichi Otsuka, Ian J Davies, Naritoshi Aoyagi, Yukio Miyashita   +4 more
wiley   +1 more source

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

Advanced Materials Technologies, EarlyView.
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding, Danny E. P. Vanpoucke, Yunus T. Aksoy, Tobias Corthouts, Maria R. Vetrano, Wim Deferme   +5 more
wiley   +1 more source

A comparative study of monotone nonparametric kernel estimates [PDF]

In this paper we present a detailed numerical comparison of three monotone nonparametric kernel regression estimates, which isotonize a nonparametric curve estimator. The first estimate is the classical smoothed isotone estimate of Brunk (1958).
Dette, Holger, Pilz, Kay F.
core