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Maximum-Power Stirling-like Heat Engine with a Harmonically Confined Brownian Particle.
Entropy (Basel)
January 2025
Física Teórica, Universidad de Sevilla, Apartado de Correos 1065, E-41080 Sevilla, Spain.
Heat engines transform thermal energy into useful work, operating in a cyclic manner. For centuries, they have played a key role in industrial and technological development. Historically, only gases and liquids have been used as working substances, but the technical advances achieved in recent decades allow for expanding the experimental possibilities and designing engines operating with a single particle.
View Article and Find Full Text PDFBernoulli trial under subsystem restarts: Two competing searchers looking for a target.
Chaos
January 2025
Research Center for Computer Science and Information Technologies, Macedonian Academy of Sciences and Arts, Bul. Krste Misirkov 2, 1000 Skopje, Macedonia.
We study a pair of independent searchers competing for a target under restarts and find that introduction of restarts tends to enhance the search efficiency of an already efficient searcher. As a result, the difference between the search probabilities of the individual searchers increases when the system is subject to restarts. This result holds true independent of the identity of individual searchers or the specific details of the distribution of restart times.
View Article and Find Full Text PDFInference of Onsager coefficient from microscopic simulations by machine learning.
J Chem Phys
January 2025
School of Chemistry, Beihang University, Beijing 100191, China.
Dynamic density functional theory (DDFT) is a fruitful approach for modeling polymer dynamics, benefiting from its multiscale and hybrid nature. However, the Onsager coefficient, the only free parameter in DDFT, is primarily derived empirically, limiting the accuracy and broad application of DDFT. Herein, we propose a machine learning-based, bottom-up workflow to directly extract the Onsager coefficient from molecular simulations, circumventing partly heuristic assumptions in traditional approaches.
View Article and Find Full Text PDFUsing space-filling curves and fractals to reveal spatial and temporal patterns in neuroimaging data.
J Neural Eng
January 2025
Center for Complex Systems & Brain Sciences (CEMSC3), Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, Buenos Aires, Argentina.
. Magnetic resonance imaging (MRI), functional MRI (fMRI) and other neuroimaging techniques are routinely used in medical diagnosis, cognitive neuroscience or recently in brain decoding. They produce three- or four-dimensional scans reflecting the geometry of brain tissue or activity, which is highly correlated temporally and spatially.
View Article and Find Full Text PDFMicroscale Electrical Resistivity Measurements to Investigate Particle Distribution.
Langmuir
January 2025
Materials Science and Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, Pennsylvania 19104, United States.
The functional performance of a particulate thin film depends greatly on the particle distribution that forms during drying. In situ methods for monitoring the impact of different processing parameters on the distribution of particles currently require expensive and specialized equipment. This work addresses this gap by miniaturizing a geophysical prospecting method to thin-film applications.
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