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Related Concept Videos

Passive Diffusion: Overview and Kinetics01:17

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Passive diffusion is a critical process that allows small lipophilic drugs to cross the cell membrane along a concentration gradient. This mechanism's efficiency depends on four primary factors: the membrane's surface area, the drug's lipid-water partition coefficient, the concentration gradient, and the membrane's thickness.
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Passive filters are utilized to shape the frequency spectrum of signals across a diverse array of applications. These filters, using only passive elements like resistors (R), inductors (L), and capacitors (C), are capable of selectively allowing or blocking certain frequency ranges without the need for external power sources.
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When an object is in equilibrium, it is either at rest or moving with a constant velocity. There are two types of equilibrium: static and dynamic. Static equilibrium occurs when an object is at rest, while dynamic equilibrium occurs when an object is moving with a constant velocity. In both cases, there must be a balance of forces acting on the object.
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In precipitation gravimetry, the precipitating agent should react specifically or selectively with the analyte. While a specific reagent reacts with the analyte alone, a selective reagent can react with a limited number of chemical species.
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Multipipe systems consist of complex configurations of interconnected pipes designed to transport fluids efficiently across intricate networks. They are essential in engineering applications requiring precise control over flow distribution, pressure, and head loss. They are categorized into series, parallel, loop, and network configurations, each distinguished by unique flow characteristics and applications.
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Updated: Jan 7, 2026

Bioprinting of Cartilage and Skin Tissue Analogs Utilizing a Novel Passive Mixing Unit Technique for Bioink Precellularization
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Mixing of a binary passive particle system using smart active particles.

Thomas Jacob1,2, Siddhant Mohapatra1, Rajalingam A1

  • 1Department of Mechanical Engineering, Indian Institute of Technology Madras, 600036, Chennai, India.

Scientific Reports
|December 20, 2025
PubMed
Summary
This summary is machine-generated.

Smart active particles, guided by artificial neural networks, achieve superior mixing of passive particles. Optimal strategies involve localized activity zones, enhancing system-level phenomena for applications in materials and drug delivery.

Keywords:
Active matterMixingReinforcement learning

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Area of Science:

  • Physics, Soft Matter and Materials Science
  • Computer Science, Artificial Intelligence and Machine Learning

Background:

  • Active matter systems exhibit emergent phenomena with applications in drug delivery, materials science, and microfluidics.
  • Controlled interactions between active and passive entities are key to harnessing these emergent properties.

Purpose of the Study:

  • To achieve optimal mixing of segregated passive particles using a small fraction of intelligent active particles.
  • To investigate the role of adaptive learning in active matter systems for enhanced performance.

Main Methods:

  • Introduction of active particles with adaptive behavior directed by a trained Artificial Neural Network (ANN) agent.
  • Comparison of mixing efficiency between conventional run-and-tumble particles and ANN-guided active particles.
  • Analysis of particle motion dynamics and spatial distribution for optimal mixing strategies.

Main Results:

  • ANN-guided active particles demonstrate significantly faster and more efficient mixing compared to conventional methods.
  • Optimal mixing is achieved not by uniform dispersion, but by concentrating active particle activity in an eccentric zone.
  • This localized activity induces global rotational motion in passive particles, with observed directional changes towards the center.

Conclusions:

  • Integrating machine learning, specifically ANNs, enhances the control and performance of active matter systems.
  • Adaptive active particles offer a powerful tool for optimizing mixing and other emergent phenomena in complex systems.
  • This research bridges active matter physics and AI, paving the way for novel applications in microfluidics and adaptive materials.