Results 151 to 160 of about 64,270 (302)
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
ABSTRACT The penetration of information and communication technologies (ICTs) in farming communities is increasing the use of smartphone‐based instant messaging apps. Despite this, the reasons behind participation and the impact on farm productivity in developing countries remain unexplored.
Zafar Kurbanov +4 more
wiley +1 more source
A time for everything: reviewing an institution's virtual learning environment [PDF]
Roger Cook, Regina Obexer
openalex
ABSTRACT The origin of a product, if associated with good quality, can contribute to building a positive collective reputation, leading to a potential price premium. However, it is conceivable that a producer markets a product by evoking symbols, images, words, and values typical of places other than where it was designed or produced, creating a ...
Annalisa Caloffi +2 more
wiley +1 more source
ABSTRACT This study analyzes the effects of value co‐creation and creation of shared value in agricultural input marketing. This study used a sample of 178 agricultural companies in Costa Rica. The data were analyzed using partial least squares structural equation modeling (PLS‐SEM) with SMART PLS software. Our findings reveal the significant influence
Luis Ricardo Solís‐Rivera +1 more
wiley +1 more source
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang +5 more
wiley +1 more source
Virtual Reality: Applications in Veterinary Science. [PDF]
Daungsupawong H, Wiwanitkit V.
europepmc +1 more source
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob +2 more
wiley +1 more source
Software-defined self-learning control system for industrial robots by using reinforcement learning. [PDF]
Moon J, Kim M, Lee T, Um J.
europepmc +1 more source
Predictors for the Adoption of Virtual Learning Environments - a Case Study from Bhutan.
Sonam Penjor, Pär‐Ola Zander
openalex +1 more source

