Results 181 to 190 of about 8,666,177 (367)

Differential grain quality responses of rice varieties under combined salt, cadmium and arsenic stresses. [PDF]

open access: yesSci Rep
Rifasa S   +7 more
europepmc   +1 more source

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

open access: yesAdvanced 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

Genetic Diversity of Prolamin Loci Related to Grain Quality in Durum Wheat (<i>Triticum durum</i> Desf.) in Kazakhstan. [PDF]

open access: yesLife (Basel)
Utebayev M   +11 more
europepmc   +1 more source

Impact of tillage on yield and quality traits of grains of spring wheat cultivars

open access: bronze, 2019
Alicja Sułek   +2 more
openalex   +1 more source

Universal In Situ Isotope Exchange Raman Spectroscopy (IERS) Methodology for Measuring Oxygen Surface Exchange Dynamics Using a Probe Layer

open access: yesAdvanced Functional Materials, EarlyView.
A bespoke multilayer thin film configuration has been designed, which overcomes the material dependency of conventional isotope exchange Raman spectroscopy (IERS). This universal IERS methodology is efficient, non‐destructive and provides additional structural information and time resolution, which can be further extended to various isotopic elements ...
Zonghao Shen   +7 more
wiley   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced 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   +7 more
wiley   +1 more source

CRISPR/Cas9-mediated inactivation of the soybean agglutinin <i>Le1</i> gene to improve grain quality. [PDF]

open access: yesFront Plant Sci
Kafer JM   +8 more
europepmc   +1 more source

Home - About - Disclaimer - Privacy