Results 41 to 50 of about 2,070 (169)
Tandem Takeoff: Powering Tomorrow with Industrial‐Grade Perovskite/Silicon Solar Cells
Perovskite/silicon tandem solar cells have recently achieved certified power conversion efficiencies of 34.85%, far exceeding the Shockley‐Queisser limit for single‐junction silicon and standalone perovskite cells. This review highlights the latest advances in the design, integration, and optimization of perovskite top cells for monolithic tandem ...
Maria Vasilopoulou +19 more
wiley +1 more source
This study introduces a multidimensional framework integrating electrical performance, cost, and life cycle assessment for 140 real and virtual battery cells. Results show that LFP offers low emissions and costs, sodium‐ion excels in resource efficiency, and pouch housings and higher energy densities effectively reduce environmental burdens.
Nicolas Peter Kaiser +7 more
wiley +1 more source
ABSTRACT The present study uses an agroeconomic supply model to assess the impacts of 2023–2027 CAP on Italian specialized dairy cattle farms. The model considers the voluntary choice of Eco‐Scheme 1, specifically addressed to livestock farms, through the implementation of binary variables.
Davide Dell'Unto, Raffaele Cortignani
wiley +1 more source
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia +3 more
wiley +1 more source
The Necessity of Dynamic Workflow Managers for Advancing Self‐Driving Labs and Optimizers
We assess the maturity and integration readiness of key methodologies for Materials Acceleration Platforms, highlighting the need for dynamic workflow managers. Demonstrating this, we integrate PerQueue into a color‐mixing robot, showing how flexible orchestration improves coordination and optimization.
Simon K. Steensen +6 more
wiley +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker +2 more
wiley +1 more source
It is a fact that slippage causes tracking errors in both longitudinal and lateral directions which results to have less travel distance in tracking a reference trajectory. Less travel distance means having energy loss of the battery and carrying loads less than planned.
Gokhan Bayar +2 more
wiley +1 more source
Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian +37 more
wiley +1 more source

