scholarly journals Controlling Organization and Forces in Active Matter Through Optically-Defined Boundaries

2018 ◽  
Author(s):  
Tyler D. Ross ◽  
Heun Jin Lee ◽  
Zijie Qu ◽  
Rachel A. Banks ◽  
Rob Phillips ◽  
...  
Keyword(s):  
Fluid Flows ◽  
Cellular Structures ◽  
Active Matter ◽  
Experimental Systems ◽  
Order Of Magnitude ◽  
Equilibrium Structures ◽  
Microtubule Networks ◽  
Spatiotemporal Control ◽  
Individual Motor ◽  
Non Equilibrium

AbstractLiving systems are capable of locomotion, reconfiguration, and replication. To perform these tasks, cells spatiotemporally coordinate the interactions of force-generating, “active” molecules that create and manipulate non-equilibrium structures and force fields that span up to millimeter length scales [1–3]. Experimental active matter systems of biological or synthetic molecules are capable of spontaneously organizing into structures [4, 5] and generating global flows [6–9]. However, these experimental systems lack the spatiotemporal control found in cells, limiting their utility for studying non-equilibrium phenomena and bioinspired engineering. Here, we uncover non-equilibrium phenomena and principles by optically controlling structures and fluid flow in an engineered system of active biomolecules. Our engineered system consists of purified microtubules and light-activatable motor proteins that crosslink and organize microtubules into distinct structures upon illumination. We develop basic operations, defined as sets of light patterns, to create, move, and merge microtubule structures. By composing these basic operations, we are able to create microtubule networks that span several hundred microns in length and contract at speeds up to an order of magnitude faster than the speed of an individual motor. We manipulate these contractile networks to generate and sculpt persistent fluid flows. The principles of boundary-mediated control we uncover may be used to study emergent cellular structures and forces and to develop programmable active matter devices.

scholarly journals Persistent fluid flows defined by active matter boundaries

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zijie Qu ◽  
Dominik Schildknecht ◽  
Shahriar Shadkhoo ◽  
Enrique Amaya ◽  
Jialong Jiang ◽  
...  
Keyword(s):  
Fluid Flow ◽  
Protein Structures ◽  
Fluid Flows ◽  
Flow Fields ◽  
Self Organization ◽  
Force Model ◽  
Active Matter ◽  
Cytoskeletal Networks ◽  
Microtubule Networks ◽  
Protein Components

AbstractBiological systems control ambient fluids through the self-organization of active protein structures, including flagella, cilia, and cytoskeletal networks. Self-organization of protein components enables the control and modulation of fluid flow fields on micron scales, however, the physical principles underlying the organization and control of active-matter-driven fluid flows are poorly understood. Here, we use an optically-controlled active-matter system composed of microtubule filaments and light-switchable kinesin motor proteins to analyze the emergence of persistent flow fields. Using light, we form contractile microtubule networks of varying size and shape, and demonstrate that the geometry of microtubule flux at the corners of contracting microtubule networks predicts the architecture of fluid flow fields across network geometries through a simple point force model. Our work provides a foundation for programming microscopic fluid flows with controllable active matter and could enable the engineering of versatile and dynamic microfluidic devices.

BAND NN: A Deep Learning Framework For Energy Prediction and Geometry Optimization of Organic Small Molecules

2019 ◽  
Author(s):  
Siddhartha Laghuvarapu ◽  
Yashaswi Pathak ◽  
U. Deva Priyakumar
Keyword(s):  
Machine Learning ◽  
Density Functional ◽  
Computational Cost ◽  
Geometry Optimization ◽  
Dft Methods ◽  
Energy Prediction ◽  
Machine Learning Model ◽  
Equilibrium Structures ◽  
High Level ◽  
Non Equilibrium

Recent advances in artificial intelligence along with development of large datasets of energies calculated using quantum mechanical (QM)/density functional theory (DFT) methods have enabled prediction of accurate molecular energies at reasonably low computational cost. However, machine learning models that have been reported so far requires the atomic positions obtained from geometry optimizations using high level QM/DFT methods as input in order to predict the energies, and do not allow for geometry optimization. In this paper, a transferable and molecule-size independent machine learning model (BAND NN) based on a chemically intuitive representation inspired by molecular mechanics force fields is presented. The model predicts the atomization energies of equilibrium and non-equilibrium structures as sum of energy contributions from bonds (B), angles (A), nonbonds (N) and dihedrals (D) at remarkable accuracy. The robustness of the proposed model is further validated by calculations that span over the conformational, configurational and reaction space. The transferability of this model on systems larger than the ones in the dataset is demonstrated by performing calculations on select large molecules. Importantly, employing the BAND NN model, it is possible to perform geometry optimizations starting from non-equilibrium structures along with predicting their energies.

scholarly journals Tunable thermo-reversible bicontinuous nanoparticle gel driven by the binary solvent segregation

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yuyin Xi ◽  
Ronald S. Lankone ◽  
Li-Piin Sung ◽  
Yun Liu
Keyword(s):  
Phase Separation ◽  
Domain Size ◽  
Binary Solvent ◽  
Colloidal Systems ◽  
Colloidal Assembly ◽  
Structures And Properties ◽  
Wide Range ◽  
Equilibrium Process ◽  
Equilibrium Structures ◽  
Non Equilibrium

AbstractBicontinuous porous structures through colloidal assembly realized by non-equilibrium process is crucial to various applications, including water treatment, catalysis and energy storage. However, as non-equilibrium structures are process-dependent, it is very challenging to simultaneously achieve reversibility, reproducibility, scalability, and tunability over material structures and properties. Here, a novel solvent segregation driven gel (SeedGel) is proposed and demonstrated to arrest bicontinuous structures with excellent thermal structural reversibility and reproducibility, tunable domain size, adjustable gel transition temperature, and amazing optical properties. It is achieved by trapping nanoparticles into one of the solvent domains upon the phase separation of the binary solvent. Due to the universality of the solvent driven particle phase separation, SeedGel is thus potentially a generic method for a wide range of colloidal systems.

scholarly journals Thermal processes in molecular gas

1991 ◽  
Vol 147 ◽  
pp. 197-204
Author(s):  
J.P. Chièze ◽  
C. de Boisanger
Keyword(s):  
Ultraviolet Radiation ◽  
Molecular Clouds ◽  
Radiation Flux ◽  
Molecular Gas ◽  
Heating And Cooling ◽  
Collective Motions ◽  
Thermochemical Processes ◽  
Order Of Magnitude ◽  
Short Time ◽  
Non Equilibrium

The dynamics of the cold atomic and molecular gas, on which we focus here, is strongly affected by non equilibrium heating and cooling processes. We give two different examples, in which the breaking of the thermal balance is due respectively to variations of the incident ultraviolet radiation flux, and non equilibrium abundances of H2 molecules in molecular clouds envelopes. Fluctuations of the ultraviolet radiation flux in clumpy molecular cloud envelopes result in the formation or the destruction of dense regions. Large density contrasts, greater than one order of magnitude, are easily achieved in cloud regions of moderate visual extinction. Condensation or expansion develop on quite short time scales, of the order of a few tenth of million year, and induce collective motions which can feed turbulence.Another example of the importance of out of equilibrium thermochemical processes is furnished by the study of the H — H2 transition layers in molecular clouds envelopes. They turn out to be unstable against convection-like motions, driven by the energy released by H2 photodestruction. The gas velocities involved in these motions are, again, typical of the observed turbulent velocity in clouds envelopes.

scholarly journals Distinguishing between Clausius, Boltzmann and Pauling Entropies of Frozen Non-Equilibrium States

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 799 ◽  
Author(s):  
Rainer Feistel
Keyword(s):  
Heat Capacity ◽  
Historical Review ◽  
Zero Point ◽  
Quantum States ◽  
Boltzmann Entropy ◽  
Nernst Theorem ◽  
Symbolic Information ◽  
Equilibrium Structures ◽  
Physical Quantities ◽  
Non Equilibrium

In conventional textbook thermodynamics, entropy is a quantity that may be calculated by different methods, for example experimentally from heat capacities (following Clausius) or statistically from numbers of microscopic quantum states (following Boltzmann and Planck). It had turned out that these methods do not necessarily provide mutually consistent results, and for equilibrium systems their difference was explained by introducing a residual zero-point entropy (following Pauling), apparently violating the Nernst theorem. At finite temperatures, associated statistical entropies which count microstates that do not contribute to a body’s heat capacity, differ systematically from Clausius entropy, and are of particular relevance as measures for metastable, frozen-in non-equilibrium structures and for symbolic information processing (following Shannon). In this paper, it is suggested to consider Clausius, Boltzmann, Pauling and Shannon entropies as distinct, though related, physical quantities with different key properties, in order to avoid confusion by loosely speaking about just “entropy” while actually referring to different kinds of it. For instance, zero-point entropy exclusively belongs to Boltzmann rather than Clausius entropy, while the Nernst theorem holds rigorously for Clausius rather than Boltzmann entropy. The discussion of those terms is underpinned by a brief historical review of the emergence of corresponding fundamental thermodynamic concepts.

scholarly journals Non-Equilibrium Acceptor Concentration in GaN:Mg Grown by Metalorganic Chemical Vapor Deposition

2003 ◽  
Vol 798 ◽  
Author(s):  
Y. Gong ◽  
Y. Gu ◽  
Igor L. Kuskovsky ◽  
G. F. Neumark ◽  
J. Li ◽  
...  
Keyword(s):  
Chemical Vapor Deposition ◽  
Vapor Deposition ◽  
Chemical Vapor ◽  
Solubility Limit ◽  
Organic Chemical ◽  
Original Sample ◽  
Acceptor Concentration ◽  
Order Of Magnitude ◽  
Hall Effect Measurements ◽  
Non Equilibrium

ABSTRACTIt is shown that the high p-type conductivity in GaN:Mg, grown by metal-organic chemical vapor deposition followed by post-growth annealing, is due to non-equilibrium acceptor concentrations. A series of samples cut from a single GaN:Mg wafer, which initially had undergone rapid thermal annealing (RTA) after growth, has been investigated. The samples were annealed at various temperatures in nitrogen ambient for over 12 hours, and temperature-dependent Hall effect measurements were performed. For samples annealed at temperatures higher than 850 °C, the hole concentrations decrease by at least an order of magnitude, compared with the original sample. This behavior is explained by an Mg acceptor concentration in excess of its equilibrium solubility limit in the original sample; thus, at high enough temperatures, in the absence of hydrogen, Mg acceptors diffuse either to form electrically inactive precipitates or are eliminated. It is worth noting that the acceptor activation energy remains the same for all samples.

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