Results 171 to 180 of about 4,787 (279)

Stability of Perovskite Indoor Photovoltaics: A Focused Review and a Call for Standardized Stability Reporting

Advanced Energy Materials, EarlyView.
While perovskite solar cells have been widely studied, including their stability, perovskite indoor photovoltaics (IPVs) have only recently emerged. Nevertheless, more studies are appearing in the literature. The systematic stability study of IPVs is crucial, particularly given the inconsistencies in reported methodologies and results, which call for ...
Ivy Mawusi Asuo, Arezo Mahdavi Varposhti, Cyril Chu Fubin Kumachang, Gopal Krishnamurthy Grandhi, Vincenzo Pecunia, Thomas Meredith Brown, Paola Vivo, Nutifafa Yao Doumon   +7 more
wiley   +1 more source

Comparative Insights and Overlooked Factors of Interphase Chemistry in Alkali Metal‐Ion Batteries

Advanced Energy Materials, EarlyView.
This review presents a comparative analysis of Li‐, Na‐, and K‐ion batteries, focusing on the critical role of electrode–electrolyte interphases. It especially highlights overlooked aspects such as SEI/CEI misconceptions, binder effects, and self‐discharge relevance, emphasizing the limitations of current understanding and offering strategies for ...
Changhee Lee, Zachary T. Gossage, Shinichi Kumakura, Shinichi Komaba   +3 more
wiley   +1 more source

Impact of Satellite Clock Corrections and Different Precise Products on GPS and Galileo Precise Point Positioning Performance. [PDF]

Sensors (Basel)
Kiliszek D, Korolczuk K.
europepmc   +1 more source

Accelerated Screening of Halide Double Perovskites via Hybrid Density Functional Theory and Machine Learning for Thermoelectric Energy Conversion

Advanced Energy and Sustainability Research, EarlyView.
This study integrates hybrid density functional theory, Boltzmann transport theory, and machine learning to accelerate the discovery of lead‐free halide double perovskites for thermoelectric energy conversion. By screening 102 compounds, the authors identify high‐performing candidates such as Rb2GeI6 and Cs2SnBr6, offering a sustainable pathway toward ...
Souraya Goumri‐Said, Ghouti Abdellaoui, Mohammed Benali Kanoun   +2 more
wiley   +1 more source

Picosecond synchronization of mode-locked lasers for metropolitan-scale quantum networks. [PDF]

Opt Express
Nunn C, Lal N, Burenkov I, Li-Baboud YS, Kuo PS, Gerrits T, Polyakov SV.   +6 more
europepmc   +1 more source

opXRD: Open Experimental Powder X‐Ray Diffraction Database

Advanced Intelligent Discovery, EarlyView.
We introduce the Open Experimental Powder X‐ray Diffraction Database, the largest openly accessible collection of experimental powder diffractograms, comprising over 92,000 patterns collected across diverse material classes and experimental setups. Our ongoing effort aims to guide machine learning research toward fully automated analysis of pXRD data ...
Daniel Hollarek, Henrik Schopmans, Jona Östreicher, Jonas Teufel, Bin Cao, Adie Alwen, Simon Schweidler, Mriganka Singh, Tim Kodalle, Hanlin Hu, Gregoire Heymans, Maged Abdelsamie, Arthur Hardiagon, Alexander Wieczorek, Siarhei Zhuk, Ruth Schwaiger, Sebastian Siol, François‐Xavier Coudert, Moritz Wolf, Carolin M. Sutter‐Fella, Ben Breitung, Andrea M. Hodge, Tong‐yi Zhang, Pascal Friederich   +23 more
wiley   +1 more source

Sub-Hz fundamental, sub-kHz integral linewidth self-injection locked 780 nm hybrid integrated laser. [PDF]

Sci Rep
Isichenko A, Hunter AS, Bose D, Chauhan N, Song M, Liu K, Harrington MW, Blumenthal DJ.   +7 more
europepmc   +1 more source

Accelerating Biosensor Discovery: A Computationally‐Driven Pipeline for Microplastics Monitoring

Advanced Intelligent Discovery, EarlyView.
A computationally guided pipeline unites molecular simulation, synthetic biology, electrochemical engineering, and machine learning to accelerate biosensor discovery. A Bacillus anthracis carbohydrate‐binding module is used to develop a high‐performance micro‐ and nanoplastics sensor with greatly reduced error and variability.
Gabriel X. Pereira, Marcos de C. Leite, Pedro H. M. Zanineli, Juliana N. Y. Costa, Débora M. Cunha, Sophia P. Serra, Pedro H. Sophia, Flávio M. Shimizu, Yasmin W. Moura, Célio C. Oliveira, Gabriel R. Schleder, Gabriela F. Persinoti, Leandro Merces, Renato S. Lima   +13 more
wiley   +1 more source

A comparative study on different machine learning approaches with periodic items for the forecasting of GPS satellites clock bias. [PDF]

Sci Rep
Song L, Liu J, Wang L, Wang Z, Yuan Y.
europepmc   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source