arXiv subjects

Arun Yethiraj

Publications and source records attributed to Arun Yethiraj.

5 recordsLinked to original sources

arXiv2024

Unsupervised machine learning for supercooled liquids

Unraveling the relation between structural information and the dynamic properties of supercooled liquids is one of the grand challenges of physics. Dynamic heterogeneity, characterized by the propensity of particles, is often used as a proxy for the dynamic slowing down. In this work, we introduce an unsupervised machine learning approach based on a time-lagged autoencoder (TAE) to elucidate the effect of structural features on the long-time dynamic heterogeneity of supercooled liquids. The TAE uses an autoencoder to reconstruct features at time $t + Δt$ from input features at time $t$ for individual particles, and the resulting latent space variables are considered as order parameters. In the Kob-Andersen system, with a $Δt$ about a thousand times smaller than the relaxation time, the TAE order parameter exhibits a remarkable correlation with the long-time propensity. We find that radial features on all length-scales are required to capture the long-time dynamics, consistent with recent simulations. This shows that fluctuations of structural features contain sufficient information about the long-time dynamic heterogeneity.

cond-mat.dis-nn↗

arXiv2021

Fast estimation of ion-pairing for screening electrolytes: A cluster can approximate a bulk liquid

The propensity for ion-pairing can often dictate the thermodynamic and kinetic properties of electrolyte solutions. Fast and accurate estimates of ion-pairing can thus be extremely valuable for supplementing design and screening efforts for novel electrolytes. Here, we introduce an efficient cluster model to estimate the local ion-pair potential-of-mean-force (PMF) between ionic solutes in electrolytes. The model incorporates an ion-pair and a few layers of explicit solvent in a gas-phase cluster and leverages an enhanced sampling approach to achieve high efficiency and accuracy. We employ harmonic restraints to prevent solvent escape from the cluster and restrict sampling of large inter ion distances. We develop a Cluster Ion-Pair Sampling (CLIPS) tool that implements our cluster model and demonstrate its potential utility for screening simple and poly-electrolyte systems.

cond-mat.soft↗

arXiv2020

Liquid-liquid Phase Separation as the Second Step of Complex Coacervation

Liquid liquid phase separation (LLPS) mediated by pi-cation bonds between tyrosine and arginine residues are of biological importance. To understand the interactions between proteins in the condensed phase in close analogy to complex coacervation, we run multiple umbrella calculations between oligomers containing tyrosine (pY) and arginine (pR). We find pR-pY complexation to be energetically driven. Metadynamics simulations reveal that this energy of complexation comes primarily from pi-cation bonds. On running free energy calculation for the second binding step of complex coacervation, we find striking similarities between this process and pi-mediated LLPS. These calculations lead us to believe that contrary to the common notion, complex coacervation as whole, which involves an entropic complexation followed by an energetic aggregation is not invoked by proteins containing arginine and tyrosine residues. Rather, the latter step in itself, in which neutral polyion pairs aggregate together is the correct mechanism for pi-cation mediated LLPS.

physics.bio-ph↗

arXiv2020

The Driving Force for the Complexation of Charged Polypeptides

The phase separation of oppositely-charged polyelectrolytes in solution is of current interest . In this work we study the driving force for polyelectrolyte complexation using molecular dynamics simulations. We calculate the potential of mean force between poly(lysine) and poly(glutamate) oligomers using three different forcefields, an atomistic force field and two coarse-grained force fields. There is qualitative agreement between all forcefields, i.e., the sign and magnitude of the free energy and the nature of the driving force are similar, which suggests that the molecular nature of water does not play a significant role. For fully charged peptides, we find that the driving force for association is entropic in all cases when small ions either neutralize the poly-ions, or are in excess. The removal of all counterions switches the driving force, making complexation energetic. This suggests that the entropy of complexation is dominated by the counterions. When only 6 residues of a 11-mer are charged, however, the driving force is enthalpic in salt-free conditions. The simulations shed insight into the mechanism of complex coacervation and the importance of realistic models for the polyions.

q-bio.BM↗

arXiv2004

Self-consistent mode-coupling theory for the viscosity of rod-like polyelectrolyte solutions

A self-consistent mode-coupling theory is presented for the viscosity of solutions of charged rod-like polymers. The static structure factor used in the theory is obtained from polymer integral equation theory; the Debye-Hückel approximation is inadequate even at low concentrations. The theory predicts a non-monotonic dependence of the reduced excess viscosity, $η_R$, on concentration from the behaviour of the static structure factor in polyelectrolyte solutions. The theory predicts that the peak in $η_R$ occurs at concentrations slightly lower than the overlap threshold concentration, $c^\ast$. The peak height increases dramatically with increasing molecular weight and decreases with increased concentrations of added salt. The position of the peak, as a function of concentration divided by $c^\ast$ is independent of salt concentration or molecular weight. The predictions can be tested experimentally.

cond-mat.soft↗