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 Membraneless organelles: phasing out of equilibrium

2020 ◽  
Vol 4 (3) ◽  
pp. 343-354 ◽  
Author(s):  
Maria Hondele ◽  
Stephanie Heinrich ◽  
Paolo De Los Rios ◽  
Karsten Weis
Keyword(s):  
Gene Expression ◽  
Phase Separation ◽  
Biological Processes ◽  
Cellular Organization ◽  
Multiple Strategies ◽  
The Past ◽  
Equilibrium Process ◽  
And Control ◽  
Liquid Liquid Phase Separation ◽  
Non Equilibrium

Over the past years, liquid–liquid phase separation (LLPS) has emerged as a ubiquitous principle of cellular organization implicated in many biological processes ranging from gene expression to cell division. The formation of biological condensates, like the nucleolus or stress granules, by LLPS is at its core a thermodynamic equilibrium process. However, life does not operate at equilibrium, and cells have evolved multiple strategies to keep condensates in a non-equilibrium state. In this review, we discuss how these non-equilibrium drivers counteract solidification and potentially detrimental aggregation, and at the same time enable biological condensates to perform work and control the flux of substrates and information in a spatial and temporal manner.

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 Matrix Product State Simulations of Non-Equilibrium Steady States and Transient Heat Flows in the Two-Bath Spin-Boson Model at Finite Temperatures

Entropy ◽  
2021 ◽  
Vol 23 (1) ◽  
pp. 77
Author(s):  
Angus J. Dunnett ◽  
Alex W. Chin
Keyword(s):  
Finite Temperature ◽  
Open Quantum Systems ◽  
Quantum Systems ◽  
Steady States ◽  
Matrix Product ◽  
Open Quantum ◽  
Matrix Product State ◽  
Wide Range ◽  
Boson Model ◽  
Non Equilibrium

Simulating the non-perturbative and non-Markovian dynamics of open quantum systems is a very challenging many body problem, due to the need to evolve both the system and its environments on an equal footing. Tensor network and matrix product states (MPS) have emerged as powerful tools for open system models, but the numerical resources required to treat finite-temperature environments grow extremely rapidly and limit their applications. In this study we use time-dependent variational evolution of MPS to explore the striking theory of Tamascelli et al. (Phys. Rev. Lett. 2019, 123, 090402.) that shows how finite-temperature open dynamics can be obtained from zero temperature, i.e., pure wave function, simulations. Using this approach, we produce a benchmark dataset for the dynamics of the Ohmic spin-boson model across a wide range of coupling strengths and temperatures, and also present a detailed analysis of the numerical costs of simulating non-equilibrium steady states, such as those emerging from the non-perturbative coupling of a qubit to baths at different temperatures. Despite ever-growing resource requirements, we find that converged non-perturbative results can be obtained, and we discuss a number of recent ideas and numerical techniques that should allow wide application of MPS to complex open quantum systems.

scholarly journals Intracellular Ionic Strength Sensing Using NanoLuc

2021 ◽  
Vol 22 (2) ◽  
pp. 677
Author(s):  
Tausif Altamash ◽  
Wesam Ahmed ◽  
Saad Rasool ◽  
Kabir H. Biswas
Keyword(s):  
Thermal Stability ◽  
Phase Separation ◽  
Drug Discovery ◽  
Ionic Strength ◽  
Cellular Signaling ◽  
Live Cells ◽  
Protein Activity ◽  
Cellular Survival ◽  
Cellular Processes ◽  
Wide Range

Intracellular ionic strength regulates myriad cellular processes that are fundamental to cellular survival and proliferation, including protein activity, aggregation, phase separation, and cell volume. It could be altered by changes in the activity of cellular signaling pathways, such as those that impact the activity of membrane-localized ion channels or by alterations in the microenvironmental osmolarity. Therefore, there is a demand for the development of sensitive tools for real-time monitoring of intracellular ionic strength. Here, we developed a bioluminescence-based intracellular ionic strength sensing strategy using the Nano Luciferase (NanoLuc) protein that has gained tremendous utility due to its high, long-lived bioluminescence output and thermal stability. Biochemical experiments using a recombinantly purified protein showed that NanoLuc bioluminescence is dependent on the ionic strength of the reaction buffer for a wide range of ionic strength conditions. Importantly, the decrease in the NanoLuc activity observed at higher ionic strengths could be reversed by decreasing the ionic strength of the reaction, thus making it suitable for sensing intracellular ionic strength alterations. Finally, we used an mNeonGreen–NanoLuc fusion protein to successfully monitor ionic strength alterations in a ratiometric manner through independent fluorescence and bioluminescence measurements in cell lysates and live cells. We envisage that the biosensing strategy developed here for detecting alterations in intracellular ionic strength will be applicable in a wide range of experiments, including high throughput cellular signaling, ion channel functional genomics, and drug discovery.

scholarly journals Simulating the interstellar medium of galaxies with radiative transfer, non-equilibrium thermochemistry, and dust

2020 ◽  
Vol 499 (4) ◽  
pp. 5732-5748 ◽  
Author(s):  
Rahul Kannan ◽  
Federico Marinacci ◽  
Mark Vogelsberger ◽  
Laura V Sales ◽  
Paul Torrey ◽  
...  
Keyword(s):  
Interstellar Medium ◽  
Galaxy Formation ◽  
State Of The Art ◽  
Complex Function ◽  
Ionization State ◽  
Radiation Fields ◽  
Stellar Feedback ◽  
Wide Range ◽  
Dust Distribution ◽  
Non Equilibrium

ABSTRACT We present a novel framework to self-consistently model the effects of radiation fields, dust physics, and molecular chemistry (H2) in the interstellar medium (ISM) of galaxies. The model combines a state-of-the-art radiation hydrodynamics module with a H  and He  non-equilibrium thermochemistry module that accounts for H2 coupled to an empirical dust formation and destruction model, all integrated into the new stellar feedback framework SMUGGLE. We test this model on high-resolution isolated Milky-Way (MW) simulations. We show that the effect of radiation feedback on galactic star formation rates is quite modest in low gas surface density galaxies like the MW. The multiphase structure of the ISM, however, is highly dependent on the strength of the interstellar radiation field. We are also able to predict the distribution of H2, that allow us to match the molecular Kennicutt–Schmidt (KS) relation, without calibrating for it. We show that the dust distribution is a complex function of density, temperature, and ionization state of the gas. Our model is also able to match the observed dust temperature distribution in the ISM. Our state-of-the-art model is well-suited for performing next-generation cosmological galaxy formation simulations, which will be able to predict a wide range of resolved (∼10 pc) properties of galaxies.

scholarly journals Towards a methodology for the characterisation of the fabric of wet clays using X-ray scattering

2019 ◽  
Vol 92 ◽  
pp. 01005
Author(s):  
Georgios Birmpilis ◽  
Reza Ahmadi-Naghadeh ◽  
Jelke Dijkstra
Keyword(s):  
Materials Science ◽  
Measurement Techniques ◽  
Invasive Technique ◽  
Colloidal Systems ◽  
Characteristic Distance ◽  
X Ray ◽  
Hydrophobic Coating ◽  
X Ray Scattering ◽  
Wide Range ◽  
Ray Scattering

X-ray scattering is a promising non-invasive technique to study evolving nano- and micromechanics in clays. This study discusses the experimental considerations and a successful method to enable X-ray scattering to study clay samples at two extreme stages of consolidation. It is shown that the proposed sample environment comprising flat capillaries with a hydrophobic coating can be used for a wide range of voids ratios ranging from a clay suspension to consolidated clay samples, that are cut from larger specimens of reconstituted or natural clay. The initial X-ray scattering results using a laboratory instrument indicate that valuable information on, in principal evolving, clay fabric can be measured. Features such as characteristic distance between structural units and particle orientations are obtained for a slurry and a consolidated sample of kaolinite. Combined with other promising measurement techniques from Materials Science the proposed method will help advance the contemporary understanding on the behaviour of dense colloidal systems of clay, as it does not require detrimental sample preparation

Theories of Phase Separation in Colloidal Systems. Controversies and a Possible Resolution?

Langmuir ◽  
2002 ◽  
Vol 18 (5) ◽  
pp. 1457-1459 ◽  
Author(s):  
Kenneth S. Schmitz ◽  
Lutful Bari Bhuiyan
Keyword(s):  
Phase Separation ◽  
Colloidal Systems
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