Results 151 to 160 of about 1,111,226 (344)

GRAIN SIZE CHARACTERISTICS OF NATIVE AND NOURISHED BEACHES IN TERNATE, CAVITE, PHILIPPINES

, 2019
Christian Heco Senen SANCHEZ, Mario de Leon, Ryuichiro NISHI, Yoshihisa TSURUNARI   +3 more
openalex   +1 more source

Decoupling Size and Electronic Effects in Doped SrTiO3 Photocatalysts Through Surface Area–Normalized CO2 Hydrogenation Rates

Advanced Functional Materials, EarlyView.
Exploring the photocatalytic reverse water–gas shift (RWGS) reaction on doped SrTiO3 nanoparticle films, reveals that normalizing catalytic rates by the catalyst's specific surface area (SSA) disentangled surface area effects from the catalyst's intrinsic material properties.
Dikshita Bhattacharyya, Baliana Shani, Isaac Holmes‐Gentle, Gerardo T Martinez, Martyn McLachlan, Nicola Seriani, Ludmilla Steier   +6 more
wiley   +1 more source

Effect of Grain Size Distribution on Shear Strength Characteristic of Random Fill Material at Keureuto Dam, Indonesia

, 2023
Abi Maulana Hakim, Samira Albati Kamaruddin, Andhika Sahadewa, Рамли Назир, Haris Eko Setyawan   +4 more
openalex   +1 more source

MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance

Advanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley   +1 more source

Grain size composition of Barents Sea bottom sediments, Core PL-96-108 sampled from R/V Professor Logachev in 1996

, 2007
Б.Г. Ванштейн
openalex   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Influence of grain size on the solid-state direct reduction of polycrystalline iron oxide. [PDF]

Commun Mater
Ratzker B, Ruffino M, Shankar S, Ma Y, Raabe D.   +4 more
europepmc   +1 more source

Effects of Grain Size Distributions on Mechanical, Corrosion, Osteogenic, and Antibacterial Properties of Zn-Mg Alloys

Tao Wang, Weiran Ye, Weihua Zhao, Guanghui Zhu, Qian Tan, Ge Yang   +5 more
openalex   +1 more source

Magnetic and Structural Response Tuned by Coexisting Mn Concentration‐Dependent Phases in MnBi2Te4 Thin Film Grown on GaAs(001) by Molecular Beam Epitaxy

Advanced Functional Materials, EarlyView.
The study explores structural and magnetic properties of one of the most recent topological quantum materials (MnBi2Te4). The Mn‐poor structure leads to stacking faults (quintuple layer ‐ QL of Bi2Te3 formation instead of a septuple layer ‐ SL of MnBi2Te4), resulting in a coexistence between weak antiferromagnetism and ferromagnetism.
Wesley F. Inoch, Sergio L. A. Mello, Gilberto Rodrigues‐Junior, Sukarno O. Ferreira, Marcelo M. Sant'Anna, Benjamin R. Salles, Mateus T. Souza, Sérgio L. Morelhão, Maybi F. Sampaio, Bráulio S. Archanjo, Leonarde N. Rodrigues   +10 more
wiley   +1 more source

Strigolactones coordinate barley tillering and grain size. [PDF]

J Exp Bot
Kelly JH, Gilmore AJ, Situmorang A, Porker KD, Marzec M, Tucker MR, Brewer PB.   +6 more
europepmc   +1 more source