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Flexoelectricity is characterised by the coupling of the gradient of the deformation and the electrical polarization in a dielectric material. A novel micromorphic approach is presented to accommodate the resulting higher-order gradient…

Classical Physics · Physics 2023-07-19 Andrew McBride , Denis Davydov , Paul Steinmann

A machine learning approach is presented to accelerate the computation of block polymer morphology evolution for large domains over long timescales. The strategy exploits the separation of characteristic times between coarse-grained…

Chemical Physics · Physics 2023-09-01 Hyun Park , Boyuan Yu , Juhae Park , Ge Sun , Emad Tajkhorshid , Juan J. de Pablo , Ludwig Schneider

Recent technological advances have enabled the recording of neurons in intact circuits with a high spatial and temporal resolution, creating the need for modeling with the same precision. In particular, the development of ultra-fast…

Neurons and Cognition · Quantitative Biology 2023-11-30 Claire Guerrier , Tristan Dellazizzo Toth , Nicolas Galtier , Kurt Haas

Electrospraying is a widely-used technique for generating microspherical droplets in biomedical and chemical applications and considered as an effective approach for the deposition on substrate. However, studies on effects of controllable…

Applied Physics · Physics 2018-09-27 Zhuoying Jiang , Xiong Yu

Active forces occurring within cells can drive crucial biological processes that involve spontaneous organization and shape change, such as cell division. Motivated by recent in vitro experiments of nematic droplets of cytoskeletal…

Soft Condensed Matter · Physics 2021-02-16 Fabian Jan Schwarzendahl , Pierre Ronceray , Kimberly L. Weirich , Kinjal Dasbiswas

Ordering nanoparticles into a desired super-structure is often crucial for their technological applications. We use molecular dynamics simulations to study the assembly of nanoparticles in a polymer brush randomly grafted to a planar…

Soft Condensed Matter · Physics 2017-12-11 Shengfeng Cheng , Mark J. Stevens , Gary S. Grest

Enzymes are nano-scale machines that have evolved to drive chemical reactions out of equilibrium in the right place at the right time. Given the complexity and specificity of enzymatic function, bottom-up design of enzymes presents a…

Soft Condensed Matter · Physics 2025-05-28 Michalis Chatzittofi , Jaime Agudo-Canalejo , Ramin Golestanian

Brain-inspired learning mechanisms, e.g. spike timing dependent plasticity (STDP), enable agile and fast on-the-fly adaptation capability in a spiking neural network. When incorporating emerging nanoscale resistive non-volatile memory (NVM)…

Neural and Evolutionary Computing · Computer Science 2020-02-19 Xinyu Wu , Vishal Saxena

We develop an analytical theory to explain the experimentally-observed morphological transitions of giant vesicles induced by AC electric fields (1). The model treats the inner and suspending media as lossy dielectrics, while the membrane…

Biological Physics · Physics 2015-05-13 Petia Vlahovska , Ruben Serral Gracia , Said Aranda , Rumiana Dimova

We have theoretically studied how the azimuthal phase structure of an electron vortex beam excites surface plasmons on metal particles of different geometries as observed in electron energy loss spectroscopy. To do so, we have developed a…

Materials Science · Physics 2016-05-25 Daniel Ugarte , Caterina Ducati

Neuromorphic engineering is essentially the development of artificial systems, such as electronic analog circuits that employ information representations found in biological nervous systems. Despite being faster and more accurate than the…

Neural and Evolutionary Computing · Computer Science 2022-09-07 Arvind Subramaniam

In this paper, the effectiveness of electromagnetic forces on controlling the motion of a sedimenting elliptical particle is investigated using the immersed interface-lattice Boltzmann method (II-LBM), in which a signed distance function is…

Fluid Dynamics · Physics 2021-03-08 Jianhua Qin , Guodan Dong , Hui Zhang

A fundamental function of cortical circuits is the integration of information from different sources to form a reliable basis for behavior. While animals behave as if they optimally integrate information according to Bayesian probability…

Neurons and Cognition · Quantitative Biology 2023-09-22 Jakob Jordan , João Sacramento , Willem A. M. Wybo , Mihai A. Petrovici , Walter Senn

In this letter, we experimentally investigate the directional characteristics of propagating, finite-amplitude wave packets in lattice materials, with an emphasis on the functionality enhancement due to the nonlinearly-generated higher…

Pattern Formation and Solitons · Physics 2017-06-27 R. Ganesh , Stefano Gonella

Much of the information processing performed by a neuron occurs in the dendritic tree. For neural systems using light for communication, it is advantageous to convert signals to the electronic domain at synaptic terminals so dendritic…

Neural and Evolutionary Computing · Computer Science 2019-04-08 Jeffrey M. Shainline

A single neuron receives an extensive array of synaptic inputs through its dendrites, raising the fundamental question of how these inputs undergo integration and summation, culminating in the initiation of spikes in the soma. Experimental…

Neurons and Cognition · Quantitative Biology 2025-04-30 Yuanhong Tang , Shanshan Jia , Tiejun Huang , Zhaofei Yu , Jian K. Liu

Active dendrites are the basis for biologically plausible neural networks possessing many desirable features of the biological brain including flexibility, dynamic adaptability, and energy efficiency. A formulation for active dendrites…

Neural and Evolutionary Computing · Computer Science 2025-06-17 James E. Smith

Understanding the rules underlying organismal development is a major unsolved problem in biology. Each cell in a developing organism responds to signals in its local environment by dividing, excreting, consuming, or reorganizing, yet how…

Cell Behavior · Quantitative Biology 2025-08-20 Ramya Deshpande , Francesco Mottes , Ariana-Dalia Vlad , Michael P. Brenner , Alma dal Co

This paper presents a spike-based model which employs neurons with functionally distinct dendritic compartments for classifying high dimensional binary patterns. The synaptic inputs arriving on each dendritic subunit are nonlinearly…

Neural and Evolutionary Computing · Computer Science 2014-11-26 Shaista Hussain , Shih-Chii Liu , Arindam Basu

Self-assembly is a phenomenon observed in nature at all scales where autonomous entities build complex structures, without external influences nor centralised master plan. Modelling such entities and programming correct interactions among…

Computational Complexity · Computer Science 2013-09-26 German Terrazas , Hector Zenil , Natalio Krasnogor
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