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Learning from nature's amazing molecular machines, globular proteins, we present a framework for the predictive design of nano-machines. We show that the crucial ingredients for a chain molecule to behave as a machine are its inherent…

Soft Condensed Matter · Physics 2015-05-13 Jayanth R. Banavar , Marek Cieplak , Trinh Xuan Hoang , Amos Maritan

We propose a two-dimensional model for a complete description of the dynamics of molecular motors, including both the processive movement along track filaments and the dissociation from the filaments. The theoretical results on the…

Biomolecules · Quantitative Biology 2009-11-10 Ping Xie , Shuo-Xing Dou , Peng-Ye Wang

We introduce a new approach to build microscopic engines on the atomic scale that move translationally or rotationally and can perform useful functions such as pulling of a cargo. Characteristic of these engines is the possibility to…

Condensed Matter · Physics 2009-10-31 Markus Porto , Michael Urbakh , Joseph Klafter

Effective locomotion in nature happens by transitioning across multiple modes (e.g., walk, run, climb). Despite this, far more mechanistic understanding of terrestrial locomotion has been on how to generate and stabilize around…

Biological Physics · Physics 2025-09-22 Ratan Othayoth , George Thoms , Chen Li

Legged robots are increasingly being adopted in industries such as oil, gas, mining, nuclear, and agriculture. However, new challenges exist when moving into natural, less-structured environments, such as forestry applications. This paper…

Active particles locally transduce energy into motion, leading to unusual and emergent behaviors. However, current synthetic particles lack sensing and adaptation mechanisms. Here, we demonstrate a novel regulation pathway, through the…

Many biological functions are executed by molecular machines, which consume energy and convert it into mechanical work. Biological machines have evolved to transport cargo, facilitate folding of proteins and RNA, remodel chromatin and…

Biological Physics · Physics 2020-04-15 Mauro L. Mugnai , Changbong Hyeon , Michael Hinczewski , D. Thirumalai

Unmanned vehicle technologies are an area of great interest in theory and practice today. These technologies have advanced considerably after the first applications have been implemented and cause a rapid change in human life. Autonomous…

Computer Vision and Pattern Recognition · Computer Science 2019-12-12 Sertap Kamçı , Dogukan Aksu , Muhammed Ali Aydin

Beyond providing accurate movements, achieving smooth motion trajectories is a long-standing goal of robotics control theory for arms aiming to replicate natural human movements. Drawing inspiration from biological agents, whose reaching…

Robotics · Computer Science 2023-03-09 Ioannis Polykretis , Lazar Supic , Andreea Danielescu

Directed evolution of proteins has been the most effective method for protein engineering. However, a new paradigm is emerging, fusing the library generation and screening approaches of traditional directed evolution with computation…

Biomolecules · Quantitative Biology 2023-05-29 Kadina E. Johnston , Clara Fannjiang , Bruce J. Wittmann , Brian L. Hie , Kevin K. Yang , Zachary Wu

The 21st century is presenting humankind with unprecedented environmental and medical challenges. The ability to design novel proteins tailored for specific purposes could transform our ability to respond timely to these issues. Recent…

Biomolecules · Quantitative Biology 2022-08-24 Noelia Ferruz , Birte Höcker

Generating natural and physically feasible motions for legged robots has been a challenging problem due to its complex dynamics. In this work, we introduce a novel learning-based framework of autoregressive motion planner (ARMP) for…

Robotics · Computer Science 2023-03-29 Jeonghwan Kim , Tianyu Li , Sehoon Ha

Legged locomotion on flowing ground ({\em e.g.} granular media) is unlike locomotion on hard ground because feet experience both solid- and fluid-like forces during surface penetration. Recent bio-inspired legged robots display speed…

Biological Physics · Physics 2021-05-20 Chen Li , Paul B. Umbanhowar , Haldun Komsuoglu , Daniel E. Koditschek , Daniel I. Goldman

We show that neural networks trained by evolutionary reinforcement learning can enact efficient molecular self-assembly protocols. Presented with molecular simulation trajectories, networks learn to change temperature and chemical potential…

Statistical Mechanics · Physics 2020-06-01 Stephen Whitelam , Isaac Tamblyn

Understanding the dynamic nature of protein structures is essential for comprehending their biological functions. While significant progress has been made in predicting static folded structures, modeling protein motions on microsecond to…

This paper describes a design of a molecular propagation system in molecular communication. Molecular communication is a new communication paradigm where biological and artificially-created nanomachines communicate over a short distance…

Biological Physics · Physics 2007-08-15 Satoshi Hiyama , Y. Isogawa , T. Suda , Y. Moritani , Kazuo Sutoh

Artificial neural networks for motor control usually adopt generic architectures like fully connected MLPs. While general, these tabula rasa architectures rely on large amounts of experience to learn, are not easily transferable to new…

Machine Learning · Computer Science 2022-11-29 Nikhil X. Bhattasali , Anthony M. Zador , Tatiana A. Engel

True microrobots, in contrast with externally controlled microparticles, must harvest or carry their own source of energy, as well as their own (preferably programmable) microcontroller of actuators for locomotion, using information…

Systems and Control · Electrical Eng. & Systems 2025-08-26 Vineeth K. Bandari , Yeji Lee , Pranathi Adluri , Daniil Karnaushenko , Dmitriy D. Karnaushenko , John S. McCaskill , Oliver G. Schmidt

This letter presents a new intelligent control scheme for the accurate trajectory tracking of flexible link manipulators. The proposed approach is mainly based on a sliding mode controller for underactuated systems with an embedded…

The folding pathway and rate coefficients of the folding of a knotted protein are calculated for a potential energy function with minimal energetic frustration. A kinetic transition network is constructed using the discrete path sampling…

Biomolecules · Quantitative Biology 2010-07-05 Michael C. Prentiss , David J. Wales , Peter G. Wolynes
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