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We assess experimentally the ability of a simple flow-based sorting device, recently proposed numerically by [Zhu et al., Soft Matter, 2014, 10, 7705-7711], to separate capsules according to their stiffness. The device consists of a single…

Soft Condensed Matter · Physics 2021-01-01 Edgar Haner , Doriane Vesperini , Anne-Virginie Salsac , Anne Le Goff , Anne Juel

In recent years, mode-division multiplexing (MDM) has been proposed as a promising solution in order to increase the information capacity of optical networks both in free-space and in optical fiber transmission. Here we present the design,…

Object rearrangement, a fundamental challenge in robotics, demands versatile strategies to handle diverse objects, configurations, and functional needs. To achieve this, the AI robot needs to learn functional rearrangement priors in order…

Robotics · Computer Science 2024-03-11 Yiming Zeng , Mingdong Wu , Long Yang , Jiyao Zhang , Hao Ding , Hui Cheng , Hao Dong

Distance metric learning is successful in discovering intrinsic relations in data. However, most algorithms are computationally demanding when the problem size becomes large. In this paper, we propose a discriminative metric learning…

Machine Learning · Computer Science 2019-05-15 Jun Li , Xun Lin , Xiaoguang Rui , Yong Rui , Dacheng Tao

Non-intrusive displacement measurement technique has a distinct edge over displacement sensors working in contact mode. Laser Doppler Vibrometry based schemes (LDV) offer such an advantage. However, the measurements are limited up to…

Instrumentation and Detectors · Physics 2020-02-17 Nikhil Kumar Pachisia , Kajal Tiwari , Ritwick Das

An extended interference pattern close to surface may result in both a transmissive or evanescent surface fields for large area manipulation of trapped particles. The affinity of differing particle sizes to a moving standing wave light…

Inertial lift forces are exploited within inertial microfluidic devices to position, segregate, and sort particles or droplets. However the forces and their focusing positions can currently only be predicted by numerical simulations, making…

Fluid Dynamics · Physics 2016-07-21 Kaitlyn Hood , Sungyon Lee , Marcus Roper

Dynamic Mode Decomposition (DMD) is a data based modeling tool that identifies a matrix to map a quantity at some time instant to the same quantity in future. We design a new version which we call Adaptive Dynamic Mode Decomposition (ADMD)…

Signal Processing · Electrical Eng. & Systems 2020-12-16 Mohammad N. Murshed , M. Monir Uddin

Directional transport-dominated particle separation presents major challenges in many technological applications. The Feynman ratchet can convert the random perturbation into directional transport of particles, offering innovative…

Plasma Physics · Physics 2023-11-07 Zhi-min Cai , Zong-bo Ma , You-kai Zhao , Fu-cheng Liu , Ya-feng He

Dissipative particle dynamics (DPD) belongs to a class of models and computational algorithms developed to address mesoscale problems in complex fluids and soft matter in general. It is based on the notion of particles that represent…

Statistical Mechanics · Physics 2017-05-24 Pep Español , Patrick B Warren

This note proposes a simple and general framework of dynamic mode decomposition (DMD) and a mode selection for large datasets. The proposed framework explicitly introduces a preconditioning step using an incremental proper orthogonal…

Fluid Dynamics · Physics 2017-08-02 Yuya Ohmichi

We propose a new approach for reconstructing the 3D spatial distribution of small dislocation loops (DLs) from 2D TEM micrographs. This method is demonstrated for small DLs in tungsten, formed by low-dose ion-implantation, that appear as…

Materials Science · Physics 2018-04-04 Hongbing Yu , Xiaoou Yi , Felix Hofmann

The behavior of particles driven through a narrow constriction is investigated in experiment and simulation. The system of particles adapts to the confining potentials and the interaction energies by a self-consistent arrangement of the…

Soft Condensed Matter · Physics 2008-10-15 P. Henseler , A. Erbe , M. Köppl , P. Leiderer , P. Nielaba

Reduced-order models have long been used to understand the behavior of nonlinear partial differential equations (PDEs). Naturally, reduced-order modeling techniques come at the price of computational accuracy for a decrease in computation…

Numerical Analysis · Mathematics 2023-07-26 Jovan Žigić

Dynamic Mode Decomposition (DMD) yields a linear, approximate model of a system's dynamics that is built from data. We seek to reduce the order of this model by identifying a reduced set of modes that best fit the output. We adopt a model…

Machine Learning · Statistics 2020-01-20 John Graff , Xianzhang Xu , Francis D. Lagor , Tarunraj Singh

Within microcentrifuge devices, a microfluidic vortex separates larger particles from a heterogeneous suspension using inertial migration, a phenomenon that causes particles to migrate across streamlines. The ability to selectively capture…

Fluid Dynamics · Physics 2023-03-14 Samuel Christensen , Marcus Roper

We report on the translation and rotation of particle clusters made through the combination of spherical building blocks. These clusters present ideal model systems to study the motion of objects with complex shape. Because they could be…

Soft Condensed Matter · Physics 2009-11-02 Martin Hoffmann , Claudia S. Wagner , Ludger Harnau , Alexander Wittemann

Sedimentation and centrifugation can be used to sort particles by size, using a multistep (multicascade) method in which particles in the sediment are removed and the content of the supernatant is processed again, repeating the cycle…

Fluid Dynamics · Physics 2023-03-10 Heng Li , Lucas Beetsma , Suriya Prakash , Maurice Mikkers , Lorenzo Botto

There has been a recent revolution in the ability to manipulate micrometer-sized objects on surfaces patterned by traps or obstacles of controllable configurations and shapes. One application of this technology is to separate particles…

Soft Condensed Matter · Physics 2009-11-11 James P. Gleeson , J. M. Sancho , A. M. Lacasta , Katja Lindenberg

We give a simple, local process for nodes in an undirected graph to form non-adjacent clusters that (1) have at most a polylogarithmic diameter and (2) contain at least half of all vertices. Efficient deterministic distributed clustering…

Data Structures and Algorithms · Computer Science 2022-10-24 Václav Rozhoň , Bernhard Haeupler , Christoph Grunau