154 research outputs found
The first-principles phase diagram of monolayer nanoconfined water
No full textWater in nanoscale cavities is ubiquitous and of central importance to
everyday phenomena in geology and biology. However, the properties of nanoscale
water can be remarkably different from bulk, as shown e.g., by the anomalously
low dielectric constant of water in nanochannels [1], near frictionless water
flow [2], or the possible existence of a square ice phase [3]. Such properties
suggest that nanoconfined water could be engineered for technological
applications in nanouidics [4], electrolyte materials [5], and water
desalination [6]. Unfortunately, challenges in experimentally characterising
water on the nanoscale and the high cost of first-principles simulations have
prevented the molecular level understanding required to control the behavior of
water. Here we combine a range of computational approaches to enable a
first-principles level investigation of a single layer of water within a
graphene-like channel. We find that monolayer water exhibits surprisingly rich
and diverse phase behavior that is highly sensitive to temperature and the van
der Waals pressure acting within the nanochannel. In addition to multiple
molecular phases with melting temperatures varying non-monotonically by over
400 degrees with pressure, we predict a hexatic phase, which is an intermediate
between a solid and a liquid, and a superionic phase with a high electrical
conductivity exceeding that of battery materials. Notably, this suggests that
nanoconfinement could be a promising route towards superionic behavior at
easily accessible conditions.Comment: 33 pages, 8 figure
DFT torsiondrive data for: MACE-OFF23: Transferable Machine Learning Force Fields for Organic Molecules
No full text<p>MACE-OFF23: Transferable Machine Learning Force Fields for Organic Molecules</p>
<div><a href="https://arxiv.org/search/physics?searchtype=author&query=Kov%C3%A1cs,+D+P">Dávid Péter Kovács</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Moore,+J+H">J. Harry Moore</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Browning,+N+J">Nicholas J. Browning</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Batatia,+I">Ilyes Batatia</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Horton,+J+T">Joshua T. Horton</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Kapil,+V">Venkat Kapil</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Witt,+W+C">William C. Witt</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Magd%C4%83u,+I">Ioan-Bogdan Magdău</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Cole,+D+J">Daniel J. Cole</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Cs%C3%A1nyi,+G">Gábor Csányi </a><a href="https://doi.org/10.48550/arXiv.2312.15211">https://doi.org/10.48550/arXiv.2312.15211</a></div>
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<p>Supporting data including raw outputs from SPICE consistent torsion drives on the TorsionNet500 and OpenFF Biaryl datasets and HDF5 versions formated to be consistent with the rest of the SPICE dataset. See the <a href="../records/10975225">SPICE release</a> for more details. </p>
On the increase of the melting temperature of water confined in one-dimensional nano-cavities
No full textWater confined in nanoscale cavities plays a crucial role in everyday
phenomena in geology and biology, as well as technological applications at the
water-energy nexus. However, even understanding the basic properties of
nano-confined water is extremely challenging for theory, simulations, and
experiments. In particular, determining the melting temperature of
quasi-one-dimensional ice polymorphs confined in carbon nanotubes has proven to
be an exceptionally difficult task, with previous experimental and classical
simulations approaches report values ranging from up to
at ambient pressure. In this work, we use a machine
learning potential that delivers first principles accuracy to study the phase
diagram of water for confinement diameters . We
find that several distinct ice polymorphs melt in a surprisingly narrow range
between and , with a melting mechanism
that depends on the nanotube diameter. These results shed new light on the
melting of ice in one-dimension and have implications for the operating
conditions of carbon-based filtration and desalination devices
Accurate and efficient machine learning interatomic potentials for finite temperature modelling of molecular crystals
No full textAs with many parts of the natural sciences, machine learning interatomic potentials (MLIPs) are revolutionizing the modelling of molecular crystals. However, challenges remain for the accurate and efficient calculation of sublimation enthalpies - a key thermodynamic quantity measuring the stability of a molecular crystal. Specifically, two key stumbling blocks are: (i) the need for thousands of ab initio quality reference structures to generate training data; and (ii) the sometimes unreliable nature of density functional theory, the main technique for generating such data. Exploiting recent developments in foundation models for chemistry and materials science alongside accurate quantum diffusion Monte Carlo benchmarks, offers a promising path forward. Herein, we demonstrate the generation of MLIPs capable of describing molecular crystals at finite temperature and pressure with sub-chemical accuracy, using as few as ∼200 data structures; an order of magnitude improvement over the current state-of-the-art. We apply this framework to compute the sublimation enthalpies of the X23 dataset, accounting for anharmonicity and nuclear quantum effects, achieving sub-chemical accuracy with respect to experiment. Importantly, we show that our framework can be generalized to crystals of pharmaceutical relevance, including paracetamol and aspirin. Nuclear quantum effects are also accurately captured as shown for the case of squaric acid. By enabling accurate modelling at ambient conditions, this work paves the way for deeper insights into pharmaceutical and biological systems
Uncertainty estimation for molecular dynamics and sampling
No full textMachine-learning models have emerged as a very effective strategy to sidestep time-consuming electronic-structure calculations, enabling accurate simulations of greater size, time scale, and complexity. Given the interpolative nature of these models, the reliability of predictions depends on the position in phase space, and it is crucial to obtain an estimate of the error that derives from the finite number of reference structures included during model training. When using a machine-learning potential to sample a finite-temperature ensemble, the uncertainty on individual configurations translates into an error on thermodynamic averages and leads to a loss of accuracy when the simulation enters a previously unexplored region. Here, we discuss how uncertainty quantification can be used, together with a baseline energy model, or a more robust but less accurate interatomic potential, to obtain more resilient simulations and to support active-learning strategies. Furthermore, we introduce an on-the-fly reweighing scheme that makes it possible to estimate the uncertainty in thermodynamic averages extracted from long trajectories. We present examples covering different types of structural and thermodynamic properties and systems as diverse as water and liquid gallium
Embedding Approximately Low-Dimensional l_2^2 Metrics into l_1
No full textGoemans showed that any n points x_1,..., x_n in d-dimensions satisfying l_2^2 triangle inequalities can be embedded into l_{1}, with worst-case distortion at most sqrt{d}. We consider an extension of this theorem to the case when the points are approximately low-dimensional as opposed to exactly low-dimensional, and prove the following analogous theorem, albeit with average distortion guarantees: There exists an l_{2}^{2}-to-l_{1} embedding with average distortion at most the stable rank, sr(M), of the matrix M consisting of columns {x_i-x_j}_{i<j}. Average distortion embedding suffices for applications such as the SPARSEST CUT problem. Our embedding gives an approximation algorithm for the SPARSEST CUT problem on low threshold-rank graphs, where earlier work was inspired by Lasserre SDP hierarchy, and improves on a previous result of the first and third author [Deshpande and Venkat, in Proc. 17th APPROX, 2014]. Our ideas give a new perspective on l_{2}^{2} metric, an alternate proof of Goemans' theorem, and a simpler proof for average distortion sqrt{d}
Numerical modeling of microfluidic two-phase electrohydrodynamic instability:
No full textOrganic-aqueous liquid (phenol) extraction is one of many standard techniques to efficiently purify DNA directly from cells. Effective dispersion of one fluid phase in the other increases the surface area over which biological component partitioning may occur, and hence enhances DNA extraction efficiency. Electrohydrodynamic (EHD) instability can be harnessed to achieve this goal and has been experimentally demonstrated by Zahn and Reddy (2006). In this work, analysis and simulation are combined to study two-phase EHD instability. In the
problem configuration, the organic (phenol) phase flows into the microchannel in parallel with and sandwiched between two aqueous streams, creating a three-layer planar geometry; the two liquid phases are immiscible. An electric field is applied to induce instability and to break the organic stream into droplets. The Taylor-Melcher leaky-dielectric model is employed to investigate this phenomenon. A linear analysis is carried out with a Chebyshev pseudo-spectral method, whereas a fully nonlinear numerical simulation is implemented using a finite volume, immersed boundary method (IBM). The results from both models compare favorably with each other. The linear analysis reveals basic instability characteristics such as kink and sausage modes. On the other hand, the nonlinear simulation predicts surface deformation in the strongly nonlinear regime pertinent to droplet formation. These numerical tools will be used to investigate the effects of the applied electric field, geometry, and convective flow rate on mixing and dispersion. The eventual objective is to maximize surface area of the organic phase under given experimental conditions for optimized DNA extraction.M.S.Includes bibliographical references (p. 101-104)by Venkat raman Thenkarai Narayana
Development and evaluation of graphical user interface and benchmark creation for cache management on multi-core systems
No full textDSpace SAF Submission Ingestion Package generated from Vireo submission #11472 on 2017-09-29 at 11:19:27There is a constant need to improve processor performance on any system. It is vital to be able to visualize performance owing to a caching strategy and to use custom benchmarks to study the changes in performance. This thesis details the development and the evaluation of a graphical user interface to study the performance of a caching strategy detailed in [1]. Further, the process of creating synthetic benchmarks as well as integrating existing benchmarks to run with the tool are detailed. This thesis also proposes a synchronization mechanism which identifies the core carrying out 'prefetch and lock' of this framework and stalls other online and present cores temporarily during this phase of 'colored lockdown', to provide support on systems in which 'lockdown by master' is not available.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2019-08-01The student, Suraj Venkat, accepted the attached license on 2017-07-14 at 11:32.The student, Suraj Venkat, submitted this Thesis for approval on 2017-07-14 at 11:35.This Thesis was approved for publication on 2017-07-17 at 11:43.Made available in DSpace on 2017-09-29T17:52:23Z (GMT). No. of bitstreams: 2
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Recoding world literature : libraries, print culture, and Germany's pact with books /
No full textFrom the current vantage point of the transformation of books and libraries, B. Venkat Mani presents a historical account of world literature. By locating translation, publication, and circulation along routes of "bibliomigrancy"--The physical and virtual movement of books - Mani narrates how world literature is coded and recoded as literary works find new homes on faraway bookshelves. Mani argues that the proliferation of world literature in a society is the function of a nation's relationship with print culture - a Faustian pact with books. Moving from early Orientalist collections, to the Nazi magazine Weltliteratur, to the European Digital Library, Mani reveals the political foundations for a history of world literature that is at once a philosophical ideal, a process of exchange, a mode of reading, and a system of classification. Shifting current scholarship's focus from the academic to the general reader, from the university to the public sphere, 'Recoding World Literature' argues that world literature is culturally determined, historically conditioned, and politically charged.From the current vantage point of the transformation of books and libraries, B. Venkat Mani presents a historical account of world literature. By locating translation, publication, and circulation along routes of "bibliomigrancy"--The physical and virtual movement of books - Mani narrates how world literature is coded and recoded as literary works find new homes on faraway bookshelves. Mani argues that the proliferation of world literature in a society is the function of a nation's relationship with print culture - a Faustian pact with books. Moving from early Orientalist collections, to the Nazi magazine Weltliteratur, to the European Digital Library, Mani reveals the political foundations for a history of world literature that is at once a philosophical ideal, a process of exchange, a mode of reading, and a system of classification. Shifting current scholarship's focus from the academic to the general reader, from the university to the public sphere, 'Recoding World Literature' argues that world literature is culturally determined, historically conditioned, and politically charged.Introduction : world literature as a pact with books -- 1. Of masters and masterpieces : an empire of books, a mythic European library -- 2. Half epic, half drastic : from a parliament of letters to a national library -- 3. The shadow of empty shelves : two world wars and the rise and fall of world literature -- 4. Windows on the Berlin Wall : unfinished histories of world literature in a divided Germany -- 5. Libraries without walls? World literature in the digital century -- Epilogue.Includes bibliographical references (pages 309-336) and index.JSTO
Nuclear Quantum Effects: Fast and Accurate
No full textAtomistic simulations are a bottom up approach that predict properties of materials by modelling the quantum mechanical behaviour of all electrons and nuclei present in a system. These simulations, however, routinely assume nuclei to be classical particles, which leads to incorrect predictions for systems that exhibit significant quantum delocalization and zero-point effects, such as those containing light nuclei. The path integral approach, the state of the art approach that models the exact quantum thermodynamics of this class of systems, is much more computationally expensive and harder to implement than the classical methods that evolves the system using classical statistical mechanics. This has prevented widespread modelling of the quantum mechanics of nuclei in atomistic simulations, especially in combination with computationally expensive interatomic potentialsthat model interparticle interactions at a high level of theory. In this thesis, we present several new methods that dramatically reduce the computational cost of modelling the quantum nature of nuclei with respect to standard methods, and to existing cost reduction schemes. These methods are based on the realization that nuclear quantum effects can often be modelled using cheap short ranged interaction potential, or using high order splittings that decouple non-commuting potential and kinetic energy operators, or using generalized Langevin equations that can be used to mimic quantum fluctuations with correlated noise. We have also derived bespoke estimators of quantities such as the quantum heat capacity, the particle momentum distribution, and vibrational spectra that reduce the cost of calculating these properties, and allow direct comparisons with experiments. These methods have been implemented in the second release of an open source software i-PI, which allows them to be used in combination with widely used softwares that compute interatomic potentials. The availability of these methods has promoted routine incorporation of nuclear quantum effects in atomistic simulations. The relevance of these advances is underscored by the different properties and classes of materials to which we have applied these methods. For instance, we have computed PMD in different phases of water facilitating interpretation of Deep Inelastic Neutron Scattering experiments, and the understanding of the local environments of protons. Similarly, we have shown how the interplay of quantum effects and intermolecular interactions can be used to tune the heat capacity of methane loaded metal-organic frameworks, to increase, decrease or stay constant over a range of temperatures. We have also studied the impact of NQEs in affecting stabilities of pharmaceutically active molecular crystals using several computationally inexpensive methods that are routinely used to approximate quantum free energies. We have systematically studied their accuracy on a large set of solids, and concluded that free energy calculations that include the quantum nuclear motion exactly are the only reliable by way of predicting stabilities of molecular crystals.COSM
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