Results 241 to 250 of about 84,041 (333)

Numerical Modeling of Photothermal Self‐Excited Composite Oscillators

open access: yesAdvanced Robotics Research, EarlyView.
We present a numerical framework for simulating photothermal self‐excited oscillations. The driving mechanism is elucidated by highlighting the roles of inertia and overshoot, as well as the phase lag between the thermal moment and the oscillation angle, which together construct the feedback loop between the system state and the environmental stimulus.
Zixiao Liu   +6 more
wiley   +1 more source

Stimuli-responsive photoswitch-actinide binding: a match made in MOFs. [PDF]

open access: yesChem Sci
Park KC   +14 more
europepmc   +1 more source

Design and Utilization of Stable Hydrofluoroolefin‐Based Trifluoropropynyl Surrogate for Sonogashira Coupling

open access: yesAdvanced Synthesis &Catalysis, EarlyView.
A novel methodology for the construction of aromatic and heteroaromatic trifluoropropynyl derivatives has been developed. The new protocol is based on a tandem Sonogashira cross‐coupling reaction between a bench‐stable trifluoropropynyl carbinol reagent, generated from the commercially available and inexpensive hydrofluoroolefin‐1234yf gas, and (hetero)
Emma Bodnár   +3 more
wiley   +1 more source

Data‐Driven Multi‐Objective Optimization of Large‐Diameter Si Floating‐Zone Crystal Growth

open access: yesAdvanced Theory and Simulations, EarlyView.
This study presents a surrogate‐based Multi‐Objective Optimization framework for Floating Zone silicon crystal growth. An ensemble of Neural Networks is trained on simulation data and combined with Genetic Algorithms to explore trade‐offs in process parameters.
Lucas Vieira   +3 more
wiley   +1 more source

Comparison of Ce(iv)/Th(iv)-alkynyl complexes and observation of a <i>trans</i>-influence ligand series for Ce(iv). [PDF]

open access: yesChem Sci
Yang Q   +10 more
europepmc   +1 more source

Deep Learning Approach for Predicting Efficiency in Organic Photovoltaics from 2D Molecular Images of D/A Pairs

open access: yesAdvanced Theory and Simulations, EarlyView.
This study highlights the potential of deep learning, particularly Convolutional Neural Networks (CNNs), for predicting the photovoltaic performance of organic solar cells. By leveraging 2D images representing donor/acceptor molecular pairs, the model accurately estimates key performance indicators proving that this image‐based approach offers a fast ...
Khoukha Khoussa   +2 more
wiley   +1 more source

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