Physics
We investigate the random close packing density, $\phi_\textrm{RCP}$, of polydisperse hard sphere systems using a theoretical framework based on the equilibrium model of crowding. We derive a closed-form solution for $\phi_\textrm{RCP}$ in…
Tailoring microscopic details to tune bulk rheology is a key paradigm in soft matter physics, yet the vast parameter space associated with constituent interactions precludes a fully systematic approach. To address this, we have designed a…
Grain piles embody the complex mechanics and kinematics of disordered granular materials, including solid-like and fluid-like behaviours, complex kinematics, and preparation history-dependent stress variation. It is widely believed that the…
Microfluidic channels have emerged as useful tools to control dynamic forcing on transported microscale objects, as encountered in emulsions, biological flows, and other soft matter systems. Tailored channel designs enable precise…
Electrostatic interactions are key to the recognition processes of proteins and DNA and have been previously documented for the action of repair enzymes. Uracil-DNA glycosylase (UDG) is the first in a sequence of enzymes that act in the…
We present an exact solution of the discrete wormlike chain (DWLC) model describing a single semiflexible polymer under arbitrary external force. Through exact closure relations between pair angular correlations and single-site angular…
We present a comprehensive benchmarking dataset and empirical scaling law analysis for neural network wavefunctions by matching them to a wide spectrum of famous many body target wavefunctions. The dataset, WF-Bench, spans multiple distinct…
Spontaneous demixing in active matter is a ubiquitous phenomenon that is crucial for numerous living processes ranging from bacterial swarming to sorting of cells in dense tissues. Here, we systematically investigate the effect of spatially…
Arranging multiple arches in a circular pattern and fusing them at their midpoint yields a three-dimensional configuration that we refer to as midpoint-fused arches (MFA). This study investigates the structural bistability of MFA, i.e.,…
Many active systems move in complex environments whose mechanical response is slow and history dependent. To address this regime, we study the collective dynamics of self-sustained active particles in non-Markovian media within a…
The self-assembly of photonic nanostructures in insects involves chitin, proteins, and lipids. While synthetic photonic systems have been extensively studied, current lipid-based self-assembly systems are limited in periodicity to…
Stiff and dense fibrin networks in chronic blood clots impede drug penetration and distribution into the clot core, limiting the efficacy of thrombolytic therapies. Acoustic cavitation of microbubbles is a promising strategy to enhance drug…
We present MARUT, a scalable multi-GPU computational fluid dynamics (CFD) framework designed for high-fidelity simulations of compressible flows spanning subsonic to hypersonic regimes, including chemically reacting nonequilibrium flows…
Responsive, adaptive and intelligent are widely used but inconsistently defined descriptors of soft matter. A conceptual framework is proposed in which the three classes are information channels of increasing architectural complexity: a…
We investigate photo-responsive structure formation in a minimal model of dry active nematics. Combining microscopic simulations with the analysis of the corresponding hydrodynamic theory, we show that the system generically self-assembles…
We perform molecular dynamics simulations to investigate hydration structures and dynamics in seven water-containing polymers: PVA, PHEA, PHEMA, PBA, PMEMA, PEG, and PMEA. The analysis integrates four perspectives: the water-content…
Measuring the mechanical response of liquid interfaces without direct contact remains a major experimental challenge, particularly in liquid-liquid systems where no solid reference exists. Here, we develop a frequency-modulation atomic…
This paper presents a deep learning strategy to simultaneously solve Partial Differential Equations (PDEs) and back-calculate their parameters in the context of deep tunnel excavation. A Physics-Informed Neural Network (PINN) model is…
The GW plus Bethe-Salpeter equation (GW-BSE) formalism is a well-established approach for calculating excitation energies and optical spectra of molecules, nanostructures, and crystalline materials. We implement GW-BSE in the CP2K code and…
Understanding and controlling the dynamic interactions between fluid flows and solid materials and structures-a field known as fluid-structure interaction -is central not only to established disciplines such as aerospace and naval…