arXiv subjects

Jaehun Chun

Publications and source records attributed to Jaehun Chun.

9 recordsLinked to original sources

arXiv2026

Effect of cations on van der Waals interactions between particles in aqueous alkali nitrate electrolytes

The van der Waals interaction has been extensively studied for colloidal forces and resultant emergent phenomena such as colloidal stability, aggregation, and suspension rheology, but the effect of electrolytes on this interaction, especially at intermediate and high electrolyte concentrations, remains incompletely understood. We have extended the Lifshitz theory for van der Waals interactions in pure water to alkali nitrate solutions at arbitrary concentrations by developing a dielectric response model for alkali nitrate solutions that is based on electronic structure calculations of the molecular constituents. Due to their importance in catalysis, ceramics, and coating technologies, the Hamaker constants for rutile, boehmite, and alumina nanoparticles suspended in alkali nitrate solutions are calculated as a function of salt concentration. Contrary to prevailing assumptions, increasing the concentration of sodium (Na), potassium (K), and rubidium (Rb) nitrate solutions causes appreciable increases of the Hamaker constants relative to pure water instead of decreases, whereas cesium nitrate (CsNO3) has almost no effect on the Hamaker constant. We discussed the influence of the solution molar volume, the polarizability of the dissolved ions, and optical properties of the interacting particles in the context of previously published work. Our study indicates a non-vanishing role of van der Waals interactions on colloidal stability at intermediate and high electrolyte concentrations, leading to physical insights on emergent phenomena associated with nanoparticles.

cond-mat.soft↗

arXiv2025

Energy-Conserving Contact Dynamics of Nonspherical Rigid-Body Particles

Understanding the contact dynamics of nonspherical particles beyond the microscale is crucial for accurately modeling colloidal and granular systems, where shape anisotropy dictates structural organization and transport properties. In this paper, we introduce an energy-conserving contact dynamics framework for arbitrary convex rigid-body particles, integrating vertex-boundary interactions in 2D with vertex-surface and edge-edge detection in 3D. This formulation enables continuous force evaluation and strictly prevents particle overlap while conserving total energy during translational and rotational motion. Simulations of polygonal and polyhedral particles confirm the framework's stability and demonstrate its capability to capture packing behavior, anisotropic diffusion, and equations of state. The framework establishes a robust and extensible foundation for investigating the nonequilibrium dynamics of complex nonspherical particle systems, with potential applications in colloidal self-assembly, granular flow, and hydrodynamics.

cond-mat.soft↗

arXiv2025

Quantum Algorithm for Subcellular Multiscale Reaction-Diffusion Systems

Computational modeling of cellular systems, where reactants are governed by biochemical equations and physical representations, requires extensive classical computing resources. These limitations significantly constrain the system size and spatiotemporal scales of simulations. A key challenge lies in the "curse of dimensionality", where the number of possible reaction terms grows exponentially with the number of species, and the computation of reaction rates involving many-body interactions becomes intractable in polynomial time on classical computers. In this work, we introduce a quantum algorithmic framework designed to overcome these challenges, leveraging the architecture of quantum computing to simultaneously compute reaction rates and track the spatiotemporal dynamical evolutions of subcellular systems. We generalize the reaction-diffusion equation (RDE) for multiscale systems with arbitrary species count, encompassing higher-order interactions. Our approach achieves two principal quantum advantages: (i) an exponential quantum speedup in reaction-rate computation, contingent on the efficient preparation of polynomially accurate ground states on a quantum computer, and (ii)) a quadratic scaling in spatial grid points and polynomial scaling in the number of species for solving nonlinear RDEs, contrasting sharply with classical methods that scale exponentially with the system's degrees of freedom. To our knowledge, this represents the first efficient quantum algorithm for solving multiscale reaction-diffusion systems. This framework opens the door to simulations of biologically relevant subcellular processes across previously inaccessible spatial and temporal scales, with profound implications for computational biology, soft matter physics, and biophysical modeling.

quant-ph↗

arXiv2025

Magnetic Interactions between Nanoscale Domains in Correlated Liquids

The formation of nanoscale domains (NDs) in correlated liquids and the emerging collective magnetic properties have been suggested as key mechanisms governing ion transport under external magnetic fields (eMFs). However, the molecular-level understanding of these magnetic field-driven phenomena and the interaction between these domains remain elusive. To this end, we introduce a simplified model of a solvated nanoparticle (NP) that consists of localized magnetic domains at their surfaces to represent groups of paramagnetic ions, forming NDs, whose effective magnetic dipole moments are at least one order of magnitude greater than the individual ions. We use classical density functional theory (cDFT) to estimate the effective interactions between these localized magnetic NPs (LMNPs). Our findings indicate that, unlike individual ions, magnetic dipole interactions of NDs in the LMNP model can indeed compete with the electrostatic, van der Waals, and hydration interactions. Depending on the direction of eMF, the cDFT effective interactions between two LMNPs turn out to become more attractive or repulsive, which may play a critical role in ion separation and nucleation processes. This indicates that the cDFT interaction barrier heights can be significantly affected by the magnetic dipole interactions and the barrier heights tend to increase as the size of LMNPs increases.

cond-mat.soft↗

arXiv2023

Optical assembly of nanostructures mediated by surface roughness

Rigorous understanding of the self-assembly of colloidal nanocrystals is crucial to the development of tailored nanostructured materials. Despite extensive studies, a mechanistic understanding of self-assembly under non-equilibrium driven by an external field remains an ongoing challenge. We demonstrate self-assembly by optical tweezers imposing an external attractive field for cubic-phase sodium yttrium fluoride nanocrystals. We show that surface roughness of the nanocrystals is a decisive factor for contact leading to assembly between the nanocrystals, manifested by the roughness-dependent hydrodynamic resistivity. This provides direct evidence that dynamics are equally important to energetics in understanding self-assembly. These results have implications in a wide variety of different fields, such as in understanding the factors that mediate oriented attachment-based crystal growth or in interpreting the structure of binding sites on viruses.

cond-mat.mtrl-sci↗

arXiv2023

Potential quantum advantage for simulation of fluid dynamics

Numerical simulation of turbulent fluid dynamics needs to either parameterize turbulence-which introduces large uncertainties-or explicitly resolve the smallest scales-which is prohibitively expensive. Here we provide evidence through analytic bounds and numerical studies that a potential quantum exponential speedup can be achieved to simulate the Navier-Stokes equations governing turbulence using quantum computing. Specifically, we provide a formulation of the lattice Boltzmann equation for which we give evidence that low-order Carleman linearization is much more accurate than previously believed for these systems and that for computationally interesting examples. This is achieved via a combination of reformulating the nonlinearity and accurately linearizing the dynamical equations, effectively trading nonlinearity for additional degrees of freedom that add negligible expense in the quantum solver. Based on this we apply a quantum algorithm for simulating the Carleman-linearized lattice Boltzmann equation and provide evidence that its cost scales logarithmically with system size, compared to polynomial scaling in the best known classical algorithms. This work suggests that an exponential quantum advantage may exist for simulating fluid dynamics, paving the way for simulating nonlinear multiscale transport phenomena in a wide range of disciplines using quantum computing.

quant-ph↗

arXiv2018

From yielding to shear jamming in a cohesive frictional suspension

Simulations are used to study the steady shear rheology of dense suspensions of frictional particles exhibiting discontinuous shear thickening and shear jamming, in which finite-range cohesive interactions result in a yield stress. We develop a constitutive model that combines yielding behavior and shear thinning at low stress with the frictional shear thickening at high stresses, in good agreement with the simulation results. This work shows that there is a distinct difference between solids below the yield stress and in the shear-jammed state, as the two occur at widely separated stress levels, separated by a region of stress in which the material is flowable.

cond-mat.soft↗

arXiv2018

Global topology of contact force networks: new insight into shear thickening suspensions

Highly concentrated or 'dense" particle suspensions can undergo a sharp increase in viscosity, or shear thickening, under applies stress. Understanding the fundamental features leading to such rheological changes in dense suspensions is crucial to optimize flow conditions or to design flow modifiers for slurry processing. While local changes to the particle environment under an applied shear can be related to changes in viscosity, there is a broader need to connect the shear thickening transition to the fundamental organization of particle-interaction forces which lead to long-range organization. In particular, at a high volume fraction of particles, recent evidence indicates frictional forces between contacting particles is of importance. Herein, the network of frictional contact forces is analyzed within simulated two-dimensional shear thickening suspensions. Two topological metrics are studied to characterize the response of the contact force network (CFN) under varying applied shear stress. The metrics, geodesic index and the void parameter, reflect complementary aspects of the CFN: one is the connectedness of the contact network and the second is the distribution of spatial areas devoid of particle-particle contacts. Considered in relation to the variation of the viscosity, the topological metrics show that the network grows homogeneously at large scales but with many local regions devoid of contacts, indicating clearly the role of stress chain growth in causing the large change in the rheological response at the shear thickening transition.

cond-mat.soft↗

arXiv2017

Bidisperse and polydisperse suspension rheology at large solid fraction

At the same solid volume fraction, bidisperse and polydisperse suspensions display lower viscosities, and weaker normal stress response, compared to monodisperse suspensions. The reduction of viscosity associated with size distribution can be explained by an increase of the maximum flowable, or jamming, solid fraction $ϕ_m$. In this work, dense suspensions are simulated under strong shearing, where thermal motion and repulsive forces are negligible, but we allow for particle contact with a mild frictional interaction with interparticle friction coefficient of $μ = 0.2$. Aspects of bidisperse suspension rheology are first revisited to establish that the approach reproduces established trends; the study of bidisperse suspensions at size ratios of large to small particle radii of $δ= 2$ to 4 shows that a minimum in the viscosity occurs for $ζ$ slightly above 0.5, where $ζ= ϕ_l/ϕ$ is the fraction of the total solid volume occupied by the large particles. The simple shear flows of polydisperse suspensions with truncated normal and log normal size distributions, and bidisperse suspensions which are statistically equivalent with these polydisperse cases up to third moment of the size distribution, are simulated and the rheologies are extracted. Prior work shows that such distributions with equivalent low-order moments have similar $ϕ_m$, and the rheological behaviors of normal, log normal and bidisperse cases are shown to be in close agreement for a wide range of standard deviation in particle size, with standard correlations which are functionally dependent on $ϕ/ϕ_m$ providing excellent agreement with the rheology found in simulation. The close agreement of both viscosity and normal stress response between bi- and polydisperse suspensions demonstrates the controlling influence of the maximum packing fraction in noncolloidal suspensions

cond-mat.soft↗