arXiv subjects

Mark A. Miller

Publications and source records attributed to Mark A. Miller.

At least 19 recordsLinked to original sources

arXiv2026

LinkML: An Open Data Modeling Framework

Scientific research relies on well-structured, standardized data; however, much of it is stored in formats such as free-text lab notebooks, non-standardized spreadsheets, or data repositories. This lack of structure challenges interoperability, making data integration, validation, and reuse difficult. LinkML (Linked Data Modeling Language) is an open framework that simplifies the process of authoring, validating, and sharing data. LinkML can describe a range of data structures, from flat, list-based models to complex, interrelated, and normalized models that utilize polymorphism and compound inheritance. It offers an approachable syntax that is not tied to any one technical architecture and can be integrated seamlessly with many existing frameworks. The LinkML syntax provides a standard way to describe schemas, classes, and relationships, allowing modelers to build well-defined, stable, and optionally ontology-aligned data structures. Once defined, LinkML schemas may be imported into other LinkML schemas. These key features make LinkML an accessible platform for interdisciplinary collaboration and a reliable way to define and share data semantics. LinkML helps reduce heterogeneity, complexity, and the proliferation of single-use data models while simultaneously enabling compliance with FAIR data standards. LinkML has seen increasing adoption in various fields, including biology, chemistry, biomedicine, microbiome research, finance, electrical engineering, transportation, and commercial software development. In short, LinkML makes implicit models explicitly computable and allows data to be standardized at its origin. LinkML documentation and code are available at linkml.io.

cs.DB↗

arXiv2025

Numerical methods for unraveling inter-particle potentials in colloidal suspensions: A comparative study for two-dimensional suspensions

We compare three model-free numerical methods for inverting structural data to obtain interaction potentials, namely iterative Boltzmann inversion (IBI), test-particle insertion (TPI), and a machine-learning (ML) approach called ActiveNet. Three archetypal models of two-dimensional colloidal systems are used as test cases: Weeks--Chandler--Anderson short-ranged repulsion, the Lennard-Jones potential, and a repulsive shoulder interaction with two length scales. Additionally, data on an experimental suspension of colloidal spheres are acquired by optical microscopy and used to test the inversion methods. The methods have different merits. IBI is the only choice when the radial distribution function is known but particle coordinates are unavailable. TPI requires snapshots with particle positions and can extract both pair- and higher-body potentials without the need for simulation. The ML approach can only be used when particles can be tracked in time and it returns the force rather than the potential. However, it can unravel pair interactions from any one-body forces (such as drag or propulsion) and does not rely on equilibrium distributions for its derivation. Our results may serve as a guide when a numerical method is needed for application to experimental data, and as a reference for further development of the methodology itself.

cond-mat.soft↗

arXiv2024

Re-entrant percolation in active Brownian hard disks

Non-equilibrium clustering and percolation are investigated in an archetypal model of two-dimensional active matter using dynamic simulations of self-propelled Brownian repulsive particles. We concentrate on the single-phase region up to moderate levels of activity, before motility-induced phase separation (MIPS) sets in. Weak activity promotes cluster formation and lowers the percolation threshold. However, driving the system further out of equilibrium partly reverses this effect, resulting in a minimum in the critical density for the formation of system-spanning clusters and introducing re-entrant percolation as a function of activity in the pre-MIPS regime. This non-monotonic behaviour arises from competition between activity-induced effective attraction (which eventually leads to MIPS) and activity-driven cluster breakup. Using an adapted iterative Boltzmann inversion method, we derive effective potentials to map weakly active cases onto a passive (equilibrium) model with conservative attraction, which can be characterised by Monte Carlo simulations. While the active and passive systems have practically identical radial distribution functions, we find decisive differences in higher-order structural correlations, to which the percolation threshold is highly sensitive. For sufficiently strong activity, no passive pairwise potential can reproduce the radial distribution function of the active system.

cond-mat.stat-mech↗

arXiv2024

Understanding the effects of rotation on the wake of a wind turbine at high Reynolds number

The wake of a horizontal-axis wind turbine was studied at $Re_D=4\times10^6$ with the aim of revealing the effects of the tip speed ratio, $λ$, on the wake. Tip speed ratios of $4<λ<7$ were investigated and measurements were acquired up to 6.5 diameters downstream of the turbine. Through an investigation of the turbulent statistics, it is shown that the wake recovery was accelerated due to the higher turbulence levels associated with lower tip speed ratios. The energy spectra indicate that larger broadband turbulence levels at lower tip speed ratios contributes to a more rapidly recovering wake. Wake meandering and a coherent core structure were also studied, and it is shown that these flow features are tip speed ratio invariant, when considering their Strouhal numbers. This finding contradicts some previous studies regarding the core structure, indicating that the structure was formed by a bulk rotor geometric feature, rather than by the rotating blades. Finally, the core structure was shown to persist farther into the near wake with decreasing tip speed ratio. The structure's lifetime is hypothesized to be related to its strength relative to the turbulence in the core, which decreases with increasing tip speed ratio.

physics.flu-dyn↗

arXiv2024

The Artificial Intelligence Ontology: LLM-assisted construction of AI concept hierarchies

The Artificial Intelligence Ontology (AIO) is a systematization of artificial intelligence (AI) concepts, methodologies, and their interrelations. Developed via manual curation, with the additional assistance of large language models (LLMs), AIO aims to address the rapidly evolving landscape of AI by providing a comprehensive framework that encompasses both technical and ethical aspects of AI technologies. The primary audience for AIO includes AI researchers, developers, and educators seeking standardized terminology and concepts within the AI domain. The ontology is structured around six top-level branches: Networks, Layers, Functions, LLMs, Preprocessing, and Bias, each designed to support the modular composition of AI methods and facilitate a deeper understanding of deep learning architectures and ethical considerations in AI. AIO's development utilized the Ontology Development Kit (ODK) for its creation and maintenance, with its content being dynamically updated through AI-driven curation support. This approach not only ensures the ontology's relevance amidst the fast-paced advancements in AI but also significantly enhances its utility for researchers, developers, and educators by simplifying the integration of new AI concepts and methodologies. The ontology's utility is demonstrated through the annotation of AI methods data in a catalog of AI research publications and the integration into the BioPortal ontology resource, highlighting its potential for cross-disciplinary research. The AIO ontology is open source and is available on GitHub (https://github.com/berkeleybop/artificial-intelligence-ontology) and BioPortal (https://bioportal.bioontology.org/ontologies/AIO).

cs.LG↗

arXiv2021

Nearest-neighbor connectedness theory: A general approach to continuum percolation

We introduce a method to estimate continuum percolation thresholds and illustrate its usefulness by investigating geometric percolation of non-interacting line segments and disks in two spatial dimensions. These examples serve as models for electrical percolation of elongated and flat nanofillers in thin film composites. While the standard contact volume argument and extensions thereof in connectedness percolation theory yield accurate predictions for slender nanofillers in three dimensions, they fail to do so in two dimensions, making our test a stringent one. In fact, neither a systematic order-by-order correction to the standard argument nor invoking the connectedness version of the Percus-Yevick approximation yield significant improvements for either type of particle. Making use of simple geometric considerations, our new method predicts a percolation threshold of $ρ_c l^2 \approx 5.83$ for segments of length $l$, which is close to the $ρ_c l^2 \approx 5.64$ found in Monte Carlo simulations. For disks of area $a$ we find $ρ_c a \approx 1.00$, close to the Monte Carlo result of $ρ_c a \approx 1.13$. We discuss the shortcomings of the conventional approaches and explain how usage of the nearest-neighbor distribution in our new method bypasses those complications.

cond-mat.stat-mech↗

arXiv2020

Control of superselectivity by crowding in three-dimensional hosts

Motivated by the fine compositional control observed in membraneless droplet organelles in cells, we investigate how a sharp binding-unbinding transition can occur between multivalent client molecules and receptors embedded in a porous three-dimensional structure. In contrast to similar superselective binding previously observed at surfaces, we have identified that a key effect in a three-dimensional environment is that the presence of inert crowding agents can significantly enhance or even introduce superselectivity. In essence, molecular crowding initially suppresses binding via an entropic penalty, but the clients can then more easily form many bonds simultaneously. We demonstrate the robustness of the superselective behavior with respect to client valency, linker length and binding interactions in Monte Carlo simulations of an archetypal lattice polymer model.

cond-mat.soft↗

arXiv2020

Phase transitions on non-uniformly curved surfaces: Coupling between phase and location

For particles confined to two dimensions, any curvature of the surface affects the structural, kinetic and thermodynamic properties of the system. If the curvature is non-uniform, an even richer range of behaviours can emerge. Using a combination of bespoke Monte Carlo, molecular dynamics and basin-hopping methods, we show that the stable states of attractive colloids confined to non-uniformly curved surfaces are distinguished not only by the phase of matter but also by their location on the surface. Consequently, the transitions between these states involve cooperative migration of the entire colloidal assembly. We demonstrate these phenomena on toroidal and sinusoidal surfaces for model colloids with different ranges of interactions as described by the Morse potential. In all cases, the behaviour can be rationalised in terms of three universal considerations: cluster perimeter, stress, and the packing of next-nearest neighbours.

cond-mat.soft↗

arXiv2019

Controlling Fragment Competition on Pathways to Addressable Self-Assembly

Addressable self-assembly is the formation of a target structure from a set of unique molecular or colloidal building-blocks, each of which occupies a defined location in the target. The requirement that each type of building-block appears exactly once in each copy of the target introduces severe restrictions on the combinations of particles and on the pathways that lead to successful self-assembly. These restrictions can limit the efficiency of self-assembly and the final yield of the product. In particular, partially formed fragments may compete with each other if their compositions overlap, since they cannot be combined. Here, we introduce a "completability" algorithm to quantify competition between self-assembling fragments and use it to deduce general principles for suppressing the effects of fragment incompatibility in the self-assembly of small addressable clusters. Competition originates from loops in the bonding network of the target structure, but loops may be needed to provide structural rigidity and thermodynamic stability. An optimal compromise can be achieved by careful choice of bonding networks and by promoting semi-hierarchical pathways that rule out competition between early fragments. These concepts are illustrated in simulations of self-assembly in two contrasting addressable targets of 20 unique components each.

cond-mat.soft↗

arXiv2018

Nucleation on a sphere: the roles of curvature, confinement and ensemble

By combining Monte Carlo simulations and analytical models, we demonstrate and explain how the gas-to-liquid phase transition of colloidal systems confined to a spherical surface depends on the curvature and size of the surface, and on the choice of thermodynamic ensemble. We find that the geometry of the surface affects the shape of the free energy profile and the size of the critical nucleus by altering the perimeter-area ratio of isotropic clusters. Confinement to a smaller spherical surface results in both a lower nucleation barrier and a smaller critical nucleus size. Furthermore, the liquid domain does not grow indefinitely on a sphere. Saturation of the liquid density in the grand canonical ensemble and the depletion of the gas phase in the canonical ensemble lead to a minimum in the free energy profile, with a sharp increase in free energy for additional growth beyond this minimum.

physics.comp-ph↗

arXiv2018

Continuum Percolation of Polydisperse Rods in Quadrupole Fields: Theory and Simulations

We investigate percolation in mixtures of nanorods in the presence of external fields that align or disalign the particles with the field axis. Such conditions are found in the formulation and processing of nanocomposites, where the field may be electric, magnetic, or due to elongational flow. Our focus is on the effect of length polydispersity, which -- in the absence of a field -- is known to produce a percolation threshold that scales with the inverse weight average of the particle length. Using a model of non-interacting spherocylinders in conjunction with connectedness percolation theory, we show that a quadrupolar field always increases the percolation threshold and that the universal scaling with the inverse weight average no longer holds if the field couples to the particle length. Instead, the percolation threshold becomes a function of higher moments of the length distribution, where the order of the relevant moments crucially depends on the strength and type of field applied. The theoretical predictions compare well with the results of our Monte Carlo simulations, which eliminate finite size effects by exploiting the fact that the universal scaling of the wrapping probability function holds even in anisotropic systems. Theory and simulation demonstrate that the percolation threshold of a polydisperse mixture can be lower than that of the individual components, confirming recent work based on a mapping onto a Bethe lattice as well as earlier computer simulations involving dipole fields. Our work shows how the formulation of nanocomposites may be used to compensate for the adverse effects of aligning fields that are inevitable under practical manufacturing conditions.

cond-mat.soft↗

arXiv2016

Report on the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3)

This report records and discusses the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3). The report includes a description of the keynote presentation of the workshop, which served as an overview of sustainable scientific software. It also summarizes a set of lightning talks in which speakers highlighted to-the-point lessons and challenges pertaining to sustaining scientific software. The final and main contribution of the report is a summary of the discussions, future steps, and future organization for a set of self-organized working groups on topics including developing pathways to funding scientific software; constructing useful common metrics for crediting software stakeholders; identifying principles for sustainable software engineering design; reaching out to research software organizations around the world; and building communities for software sustainability. For each group, we include a point of contact and a landing page that can be used by those who want to join that group's future activities. The main challenge left by the workshop is to see if the groups will execute these activities that they have scheduled, and how the WSSSPE community can encourage this to happen.

cs.SE↗

arXiv2015

Design Strategies for Self-Assembly of Discrete Targets

Both biological and artificial self-assembly processes can take place by a range of different schemes, from the successive addition of identical building blocks, to hierarchical sequences of intermediates, all the way to the fully addressable limit in which each component is unique. In this paper we introduce an idealized model of cubic particles with patterned faces that allows self-assembly strategies to be compared and tested. We consider a simple octameric target, starting with the minimal requirements for successful self-assembly and comparing the benefits and limitations of more sophisticated hierarchical and addressable schemes. Simulations are performed using a hybrid dynamical Monte Carlo protocol that allows self-assembling clusters to rearrange internally while still providing Stokes-Einstein-like diffusion of aggregates of different sizes. Our simulations explicitly capture the thermodynamic, dynamic and steric challenges typically faced by self-assembly processes, including competition between multiple partially-completed structures. Self-assembly pathways are extracted from the simulation trajectories by a fully extendable scheme for identifying structural fragments, which are then assembled into history diagrams for successfully completed target structures. For the simple target, a one-component assembly scheme is most efficient and robust overall, but hierarchical and addressable strategies can have an advantage under some conditions if high yield is a priority.

cond-mat.soft↗

arXiv2015

Dynamics and thermodynamics of decay in charged clusters

We propose a method for quantifying charge-driven instabilities in clusters, based on equilibrium simulations under confinement at constant external pressure. This approach makes no assumptions about the mode of decay and allows different clusters to be compared on an equal footing. A comprehensive survey of stability in model clusters of 309 Lennard-Jones particles augmented with Coulomb interactions is presented. We proceed to examine dynamic signatures of instability, finding that rate constants for ejection of charged particles increase smoothly as a function of total charge with no sudden changes. For clusters where many particles carry charge, ejection of individual charges competes with a fission process that leads to more symmetric division of the cluster into large fragments. The rate constants for fission depend much more sensitively on total charge than those for ejection of individual particles.

physics.atm-clus↗

arXiv2013

Energy landscapes, structural topologies and rearrangement mechanisms in clusters of dipolar particles

Clusters of spherical particles with isotropic attraction favour compact structures that maximise the number of energetically optimal nearest-neighbour interactions. In contrast, dipolar interactions lead to the formation of chains with a low coordination number. When both isotropic and dipolar interactions are present, the competition between them can lead to intricate knot, link and coil structures. Here, we investigate how these structures may self-organise and interconvert in clusters bound by the Stockmayer potential (Lennard-Jones plus point dipole). We map out the low-lying region of the energy landscape using disconnectivity graphs to follow how it evolves as the strength of the dipolar interactions increases. From comprehensive surveys of isomerisation pathways, we identify a number of rearrangement mechanisms that allow the topology of chain-like structures to interconvert.

cond-mat.soft↗

arXiv2012

Structure and stability of charged clusters

When a cluster or nanodroplet bears charge, its structure and thermodynamics are altered and, if the charge exceeds a certain limit, the system becomes unstable with respect to fragmentation. Some of the key results in this area were derived by Rayleigh in the nineteenth century using a continuum model of liquid droplets. Here we revisit the topic using a simple particle-based description, presenting a systematic case study of how charge affects the physical properties of a Lennard-Jones cluster composed of 309 particles. We find that the ability of the cluster to sustain charge depends on the number of particles over which the charge is distributed---a parameter not included in Rayleigh's analysis. Furthermore, the cluster may fragment before the charge is strong enough to drive all charged particles to the surface. The charged particles in stable clusters are therefore likely to reside in the cluster's interior even without considering solvation effects.

cond-mat.soft↗

arXiv2012

Controlling the folding and substrate-binding of proteins using polymer brushes

The extent of coupling between the folding of a protein and its binding to a substrate varies from protein to protein. Some proteins have highly structured native states in solution, while others are natively disordered and only fold fully upon binding. In this Letter, we use Monte Carlo simulations to investigate how disordered polymer chains grafted around a binding site affect the folding and binding of three model proteins. The protein that approaches the substrate fully folded is more hindered during the binding process than those whose folding and binding are cooperative. The polymer chains act as localized crowding agents and can select correctly folded and bound configurations in favor of non-specifically adsorbed states. The free energy change for forming all intra-protein and protein-substrate contacts can depend non-monotonically on the polymer length.

cond-mat.soft↗

arXiv2011

Density functional theory for Baxter's sticky hard spheres in confinement

It has recently been shown that a free energy for Baxter's sticky hard sphere fluid is uniquely defined within the framework of fundamental measure theory (FMT) for the inhomogeneous hard sphere fluid, provided that it obeys scaled-particle theory and the Percus-Yevick (PY) result for the direct correlation function [Hansen-Goos and Wettlaufer, J. Chem. Phys. {\bf 134}, 014506 (2011)]. Here, combining weighted densities from common versions of FMT with a new vectorial weighted density, we derive a regularization of the divergences of the associated strongly confined limit. Moreover, the simple free energy that emerges is exact in the zero-dimensional limit, leaves the underlying equation of state unaffected, and yields a direct correlation function distinct from the PY expression. Comparison with simulation data for both the bulk pair correlation function and the density profiles in confinement shows that the new theory is significantly more accurate than the PY-based results. Finally, the resulting free energy is applicable to a glass of adhesive hard spheres.

cond-mat.soft↗