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David Quigley

Publications and source records attributed to David Quigley.

16 recordsLinked to original sources

Formation of $\mathrm{L}1_2$-ordered $\gamma'$-$\mathrm{Ni}_3\mathrm{Al}$ precipitates in ternary Cu-Ni-Al alloys modelled using an ab initio concentration wave theory and atomistic simulations

Precipitation-strengthened Cu-Ni-Al alloys are of interest for technological applications because coherent, $\mathrm{L}1_2$-ordered $\gamma'$-$\mathrm{Ni}_3\mathrm{Al}$ precipitates can confer high mechanical strength while allowing the material to retain many of the good transport properties characteristic of elemental Cu. In this work, we study the thermodynamics and phase stability of the pseudobinary $\textrm{Cu}_x (\textrm{Ni}_{3/4} \textrm{Al}_{1/4})_{1-x}$ system, $0 \leq x \leq 1$. We use a computational modelling framework combining first-principles electronic structure calculations with a concentration wave analysis from which atom-atom effective pair interactions are extracted for use in atomistic Monte Carlo simulations. Our modelling reveals three distinct, composition-dependent regimes of phase behaviour, in qualitative agreement with the experimentally determined phase diagram. At low Cu content, Cu is soluble in the $\mathrm{L}1_2$-ordered $\mathrm{Ni}_3\mathrm{Al}$ phase, with a single identifiable phase transition corresponding to chemical ordering between Ni and Al. At intermediate compositions, this high-temperature ordering is followed at lower temperatures by phase separation of Cu and $\mathrm{L}1_2$-ordered $\mathrm{Ni}_3\mathrm{Al}$. Finally, at high Cu content, $\mathrm{L}1_2$-ordered $\mathrm{Ni}_3\mathrm{Al}$ precipitates directly from the solid solution, with no clearly identifiable secondary transition. We relate these phase transformations to features of the underlying electronic structures of the considered alloys. Overall, this work demonstrates a computationally efficient workflow capturing both chemical ordering and coherent precipitation in multicomponent substitutional alloys, with relevance to the study of phenomena such as precipitation strengthening.

cond-mat.mtrl-sci

Learned Committors as Reaction Coordinates for Nucleation Rates

A central challenge in the analysis of first-order phase transitions is the identification of optimal reaction coordinates. In principle, the committor is the ideal choice; however, its computational cost has historically made it intractable. Here, we train a convolutional neural network ($p_B$-NN) as a proxy for the committor on brute-force committor labels and use it directly as the coordinate of a Markov state model. Applied to magnetisation reversal in the two-dimensional Ising model, $p_B$-NN reproduces brute-force nucleation rates across a range of thermodynamic conditions. The largest geometric cluster size also recovers accurate rates despite providing a poor pointwise predictor of the committor. These results demonstrate that an effective reaction coordinate for nucleation rate calculation must reliably separate the metastable and stable basins, but need not preserve the committor pointwise for every microstate. We stress that this distinction has direct implications for the choice of collective variable in rare-event simulations of nucleation more broadly.

physics.comp-ph

Revisiting the Phase Diagram of Hard Sphere Dumbbells with Nested Sampling: Known Phases and New Packing Variants

We explore the use of the nested sampling technique to sample the configuration space of non-spherical hard particles. We employ the technique on the hard dumbbell system consisting of two hard spheres connected by a rigid bond, and investigate the phase stability across a wide pressure range and for bond lengths from completely overlapping to tangential hard spheres. Nested sampling recovers all previously identified features of the phase diagram and identifies a family of new packing variants. The fluid phase, plastic crystal, close packed solid phases and aperiodic crystal are all sampled, and the transition points between these are mapped. Our results show good agreement with predictions made by existing equations of state, and former Monte Carlo simulations. Nested sampling also identified a close packed structure with Pnma symmetry which has not previously been considered.

cond-mat.soft

Optimal parallelisation strategies for flat histogram Monte Carlo sampling

Flat histogram methods, such as Wang--Landau sampling, provide a means for high-throughput calculation of phase diagrams of atomistic/lattice model systems. Many parallelisation schemes with varying degrees of complexity have been proposed to accelerate such sampling simulations. In this study, several widely used schemes are benchmarked -- both in isolation and in combination -- to establish best practice. The schemes studied include energy domain decomposition with both static sizing of energy sub-domains, as well as a dynamic sub-domain sizing scheme which we propose. We also assess the benefits both of replica exchange and of including multiple random walkers per sub-domain, to determine which factors have the largest impact on parallel efficiency. Additionally, the influence of energy sub-domain overlap regions is discussed. As illustrative test cases, we implement and apply the aforementioned strategies to a lattice-based model describing the internal energy of a substitutional alloy, studying the AlTiCrMo refractory high-entropy superalloy as well as the binary CuZn system, both of which crystallographically order into a B2 (CsCl) structure with decreasing temperature. We find that -- while all of the proposed strategies confer a non-negligible speedup -- parallelisation across energy domains which are non-uniform in size offers the most appreciable performance improvements. This work offers concrete recommendations for which parallelisation strategies should be prioritised to optimally accelerate flat-histogram Monte Carlo simulations.

physics.comp-ph

BraWl: Simulating the thermodynamics and phase stability of multicomponent alloys using conventional and enhanced sampling techniques

We present BraWl, a Fortran package implementing a range of conventional and enhanced sampling algorithms for exploration of the phase space of the Bragg-Williams model, facilitating study of diffusional solid-solid transformations in binary and multicomponent alloys. These sampling algorithms include Metropolis-Hastings Monte Carlo, Wang-Landau sampling, and Nested Sampling. We demonstrate the capabilities of the package by applying it to some prototypical binary and multicomponent alloys, including high-entropy alloys.

physics.comp-ph

Emergent B2 chemical orderings in the AlTiVNb and AlTiCrMo refractory high-entropy superalloys studied via first-principles theory and atomistic modelling

We study the thermodynamics and phase stability of the AlTiVNb and AlTiCrMo refractory high-entropy superalloys using a combination of \textit{ab initio} electronic structure theory -- namely a concentration wave analysis -- and atomistic Monte Carlo simulations. Our multiscale approach is suitable both for examining atomic short-range order in the solid solution, as well as for studying the emergence of long-range crystallographic order with decreasing temperature. In both alloys considered in this work, in alignment with experimental observations, we predict a B2 (CsCl) chemical ordering emerging at high temperatures, which is driven primarily by Al and Ti, with other elements expressing weaker site preferences. The predicted B2 ordering temperature for AlTiVNb is higher than that for AlTiCrMo. These chemical orderings are discussed in terms of the alloys' electronic structure, with hybridisation between the $sp$ states of Al and the $d$ states of the transition metals understood to play an important role. Within our modelling, the chemically ordered B2 phases for both alloys have an increased predicted residual resistivity compared to the A2 (disordered bcc) phases. These increased resistivity values are understood to originate in a reduction in the electronic density of states at the Fermi level, in conjunction with qualitative changes to the alloys' smeared-out Fermi surfaces. These results highlight the close connections between composition, structure, and physical properties in this technologically relevant class of materials.

cond-mat.mtrl-sci

Low temperature nucleation rate calculations using the N-Fold way

We present a numerical study to determine nucleation rates for magnetisation reversal within the Ising model (lattice gas model) in the low-temperature regime, a domain less explored in previous research. To achieve this, we implemented the N-Fold way algorithm, a well-established method for low-temperature simulations, alongside a novel, highly efficient cluster identification algorithm. Our method can access nucleation rates up to 50 orders of magnitude lower than previously reported results. We examine three cases: homogeneous pure system, system with static impurities, and system with mobile impurities, where impurities are defined as sites with zero interactions with neighbouring spins (spin value of impurities is set to 0). Classical nucleation theory holds across the entire temperature range studied in the paper, for both the homogeneous system and the static impurity case. However, in the case of mobile impurities, the umbrella sampling technique seems ineffective at low mobility values. These findings provide valuable insights into nucleation phenomena at low temperatures, contributing to theoretical and experimental understanding.

cond-mat.stat-mech

Mapping the influence of impurity interaction energy on nucleation in a lattice-gas model of solute precipitation

We study nucleation in the two dimensional Ising lattice-gas model of solute precipitation in the presence of randomly placed static and dynamic impurities. Impurity-solute and impurity-solvent interaction energies are varied whilst keeping other interaction energies fixed. In the case of static impurities, we observe a monotonic decrease in the nucleation rate when the difference between impurity-solute and impurity-solvent interaction energies is increased. The nucleation rate saturates to a minimum value with increasing interaction energy difference when the impurity density is low. However the nucleation rate does not saturate for high impurity densities. Similar behaviour is observed with dynamic impurities both at low and high densities. We explore a broad range of both symmetric and anti-symmetric interactions with impurities and map the regime for which the impurities act as a surfactant, decreasing the surface energy of the nucleating phase. We also characterise different nucleation regimes observed at different values of interaction energy. These include additional regimes where impurities play the role of inert-spectators, bulk-stabilizers or cluster together to create heterogeneous nucleation sites for solute clusters to form.

cond-mat.stat-mech

Kinetic control of competing nuclei in a dimer lattice-gas model

Nucleation is a key step in the synthesis of new material from solution. Well-established lattice-gas models can be used to gain insight into the basic physics of nucleation pathways involving a single nucleus type. In many situations a solution is supersaturated with respect to more than one precipitating phase. This can generate a population both stable and metastable nuclei on similar timescales and hence complex nucleation pathways involving competition between the two. In this study we introduce a lattice-gas model based on two types of interacting dimer representing particles in solution. Each type of dimer nucleates to a specific space-filling structure. Our model is tuned such that stable and metastable phases nucleate on a similar timescale. Either structure may nucleate first, with probability sensitive to dimer mobility. We calculate these nucleation rates via Forward-Flux Sampling and demonstrate how the resulting data can be used to infer the nucleation outcome and pathway. Possibilities include direct nucleation of the stable phase, domination of long-lived metastable crystallites, and pathways in which the stable phase nucleates only after multiple post-critical nuclei of the metastable phase have appeared.

cond-mat.stat-mech

Nucleation rate in the two dimensional Ising model in the presence of random impurities

Nucleation phenomena are ubiquitous in nature and the presence of impurities in every real and experimental system is unavoidable. Yet numerical studies of nucleation are nearly always conducted for entirely pure systems. We have studied the behaviour of the droplet free energy in two dimensional Ising model in the presence of randomly positioned static and dynamic impurities. We have shown that both the free energy barrier height and critical nucleus size monotonically decreases with increasing the impurity density for the static case. We have compared the nucleation rates obtained from Classical Nucleation Theory and the Forward Flux Sampling method for different densities of the static impurities. The results show good agreement. In the case of dynamic impurities, we observe preferential occupancy the impurities at the boundary positions of the nucleus when the temperature is low. This further boosts enhancement of the nucleation rate due to lowering of the effective interfacial free energy.

cond-mat.stat-mech

The Seven Deadly Sins: when computing crystal nucleation rates, the devil is in the details

The formation of crystals has proven to be one of the most challenging phase transformations to quantitatively model - let alone to actually understand - be it by means of the latest experimental technique or the full arsenal of enhanced sampling approaches at our disposal. One of the most crucial quantities involved with the crystallization process is the nucleation rate, a single, elusive number that is supposed to quantify the average probability for a nucleus of critical size to occur within a certain volume and time span. A substantial amount of effort has been devoted to attempt a connection between the crystal nucleation rates computed by means of atomistic simulations and their experimentally measured counterparts. Sadly, this endeavour almost invariably fails to some extent, with the venerable classical nucleation theory typically blamed as the main culprit. Here, we review some of the recent advances in the field, focusing on a number of perhaps more subtle details that are sometimes overlooked when computing nucleation rates. We believe it is important for the community to be aware of the full impact of aspects such as finite size effects and slow dynamics, that often introduce inconspicuous and yet non-negligible sources of uncertainty into our simulations. In fact, it is key to obtain robust and reproducible trends to be leveraged so as to shed new light on the kinetics of a process, that of crystal nucleation, which is involved into countless practical applications, from the formulation of pharmaceutical drugs to the manufacturing of nano-electronic devices.

cond-mat.mtrl-sci

Model-Independent Simulation Complexity of Complex Quantum Dynamics

We present a model-independent measure of dynamical complexity based on simulating complex quantum dynamics using stroboscopic Markovian dynamics. Tools from classical signal processing enable us to infer the Hilbert space dimension of a complex quantum system evolving under a time-independent Hamiltonian via pulsed interrogation. We evaluate our model-independent simulation complexity (MISC) for the spin-boson model and simulated third-order pump-probe spectroscopy data for exciton transport in coupled dimers with vibrational levels. The former provides insights into coherence and population dynamics in the two-level system while the latter reveals the dimension of the singly-excited manifold of the dimer. Finally, we probe the complexity of excitonic transport in light harvesting 2 (LH2) and Fenna-Matthews-Olson (FMO) complexes using data from two recent nonlinear ultrafast optical spectroscopy experiments. For the latter we make some model-independent inferences that are commensurate with model-specific ones. This includes estimating the fewest number of parameters needed to fit the experimental data and identifying the spatial extent, i.e., delocalization size, of quantum states occurring in this complex quantum dynamics.

quant-ph

Single-Atom Scale Structural Selectivity in Te Nanowires Encapsulated inside Ultra-Narrow, Single-Walled Carbon Nanotubes

Extreme nanowires (ENs) represent the ultimate class of crystals: They are the smallest possible periodic materials. With atom-wide motifs repeated in one dimension (1D), they offer a privileged perspective into the Physics and Chemistry of low-dimensional systems. Single-walled carbon nanotubes (SWCNTs) provide ideal environments for the creation of such materials. Here we present a comprehensive study of Te ENs encapsulated inside ultra- narrow SWCNTs with diameters between 0.7 nm and 1.1 nm. We combine state-of-the-art imaging techniques and 1D-adapted ab initio structure prediction to treat both confinement and periodicity effects. The studied Te ENs adopt a variety of structures, exhibiting a true 1D realisation of a Peierls structural distortion and transition from metallic to insulating behaviour as a function of encapsulating diameter. We analyse the mechanical stability of the encapsulated ENs and show that nanoconfinement is not only a useful means to produce ENs, but may actually be necessary, in some cases, to prevent them from disintegrating. The ability to control functional properties of these ENs with confinement has numerous applications in future device technologies, and we anticipate that our study will set the basic paradigm to be adopted in the characterisation and understanding of such systems.

cond-mat.mtrl-sci

Encapsulated Nanowires: Boosting Electronic Transport in Carbon Nanotubes

The electrical conductivity of metallic carbon nanotubes (CNTs) quickly saturates with respect to bias voltage due to scattering from a large population of optical phonons. Decay of these dominant scatterers in pristine CNTs is too slow to offset an increased generation rate at high voltage bias. We demonstrate from first principles that encapsulation of 1D atomic chains within a single-walled CNT can enhance decay of "hot" phonons by providing additional channels for thermalisation. Pacification of the phonon population growth reduces electrical resistivity of metallic CNTs by 51% for an example system with encapsulated beryllium.

cond-mat.mtrl-sci

Polyomino Models of Surface Supramolecular Assembly: Design Constraints and Structural Selectivity

We examine emergent properties of 2D supramolecular networks, using enumeration of configurations formed by interacting dominoes on square lattices as a simple model system. Possible ground states are identified using a convex hull construction in the interaction parameters for nearest-neighbour bonds. We demonstrate how this construction can be used to design interaction parameters which lead to networks with specific properties, including chirality and highly degenerate ground states. We then introduce kinetics as simple local rearrangements. By partitioning the configuration space into smaller sets which satisfy different topological constraints, we can design configurations which are kinetically trapped. By considering heat capacity curves along directions through the convex hull, we also demonstrate design of interacting domino configurations to create tilings robust against temperature induced phase transitions. We discuss extension of this design construction to more complex molecular shapes.

cond-mat.soft

Folding kinetics of a polymer [corrigendum]

In our original article (Phys. Chem. Chem. Phys., 2012, 14, 60446053) a convergence problem resulted in an averaging error in computing the entropy from a set of Wang-Landau Monte-Carlo simulations. Here we report corrected results for the freezing temperature of the homopolymer chain as a function of the range of the non-bonded interaction. We find that the previously reported forward-flux sampling (FFS) and brute-force (BF) simulation results are in agreement with the revised Wang-Landau (WL) calculations. This confirms the utility of FFS for computing crystallisation rates in systems of this kind.

cond-mat.soft