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Results for “categorical quantum mechanics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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13 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Non-commutative disintegrations: Existence and uniqueness in finite dimensions

Motivated by advances in categorical probability, we introduce non-commutative almost everywhere (a.e.) equivalence and disintegrations in the setting of C*-algebras. We show that C*-algebras (resp. W*-algebras) and a.e. equivalence classes of 2-positive (resp. positive) unital maps form a category. We prove non-commutative disintegrations are a.e. unique whenever they exist. We provide an explicit characterization for when disintegrations exist in the setting of finite-dimensional C*-algebras, and we give formulas for the associated disintegrations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Predicting Energetics Materials’ Crystalline Density from Chemical Structure by Machine Learning

To expedite new molecular compound development, a long-sought goal within the chemistry community has been to predict molecules’ bulk properties of interest a priori to synthesis from a chemical structure alone. In this work, we demonstrate that machine learning methods can indeed be used to directly learn the relationship between chemical structures and bulk crystalline properties of molecules, even in the absence of any crystal structure information or quantum mechanical calculations. We focus specifically on a class of organic compounds categorized as energetic materials called high explosives (HE) and predicting their crystalline density. An ongoing challenge within the chemistry machine learning community is deciding how best to featurize molecules as inputs into machine learning models—whether expert handcrafted features or learned molecular representations via graph-based neural network models—yield better results and why. We evaluate both types of representations in combination with a number of machine learning models to predict the crystalline densities of HE-like molecules curated from the Cambridge Structural Database, and we report the performance and pros and cons of our methods. Our message passing neural network (MPNN) based models with learned molecular representations generally perform best, outperforming current state-of-the-art methods at predicting crystalline density and performing well even when testing on a data set not representative of the training data. However, these models are traditionally considered black boxes and less easily interpretable. Here, to address this common challenge, we also provide a comparison analysis between our MPNN-based model and models with fixed feature representations that provides insights as to what features are learned by the MPNN to accurately predict density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Chemical transformations and transport phenomena at interfaces

Abstract Interfaces, the boundary that separates two or more chemical compositions and/or phases of matter, alters basic chemical and physical properties including the thermodynamics of selectivity, transition states, and pathways of chemical reactions, nucleation events and phase growth, and kinetic barriers and mechanisms for mass transport and heat transport. While progress has been made in advancing more interface‐sensitive experimental approaches, their interpretation requires new theoretical methods and models that in turn can further elaborate on the microscopic physics that make interfacial chemistry so unique compared to the bulk phase. In this review, we describe some of the most recent theoretical efforts in modeling interfaces, and what has been learned about the transport and chemical transformations that occur at the air–liquid and solid–liquid interfaces. This article is categorized under: Structure and Mechanism > Reaction Mechanisms and Catalysis Structure and Mechanism > Computational Materials Science Software > Quantum Chemistry Software > Simulation Methods

Hao, Hongxia↗
DOE OSTI2020

Spatially resolved characterization of optical and recombination losses for different industrial silicon solar cell architectures

In this work, spatially resolved characterization methods are used to identify loss mechanisms for common p -type silicon solar cell architectures, including multicrystalline aluminum back surface field (Al-BSF), monocrystalline Al-BSF, monocrystalline passivated emitter and rear cells (PERC), and bifacial monocrystalline PERC. The characterization methods used in this work include suns-V OC , photoluminescence imaging, and spatially resolved external quantum efficiency and reflectance measurements. The optical and recombination losses are driven by the material properties, cell processing conditions, and device architecture. These losses are quantified and categorized in terms of underlying mechanisms (e.g., front reflectance, escape reflectance, front recombination, and parasitic optical absorption and recombination in the bulk and rear). The ability to create images of these loss parameters can be used to gain more insight into the materials and manufacturing processes used to produce solar cells, and examples are given in this work to illustrate how these images can help reveal the origin of defects.

14 SOLAR ENERGY↗
DOE OSTI2023

Chapman–Jouguet deflagration criteria and compressibility dynamics of turbulent fast flames for turbulence-induced deflagration-to-detonation transition

This work characterizes the compressibility dynamics in turbulent fast flames for a range of turbulent flame speeds. These turbulent fast flames experience increased effects of compressibility through the formation of strong shocks and may develop a runaway acceleration combined with a pressure buildup that leads to turbulence induced deflagration-to-detonation transition (tDDT). Simultaneous high-speed particle image velocimetry, OH* chemiluminescence, schlieren, and pressure measurements are used to examine the reacting flow field and flame dynamics. We examine flames with turbulent flame speeds ranging from 100 to 600 m/s. At lower turbulent flame speeds, the flame is not able to produce favorable background conditions for deflagration-to-detonation transition (DDT) onset, and thus flame compressibility and turbulence amplification are less dominant, resulting in a weaker acoustic coupling between the flame and compressed region. As the turbulent burning velocities exceed the Chapman–Jouguet deflagration speed, favorable background conditions are produced, as we observe flame-generated shocks and flame-generated turbulence with higher turbulent velocities and larger turbulent scales. At this regime, the flame is categorized to be at the runaway transition regime that leads to tDDT.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Quantum Simulations of Radiation Damage in a Molecular Polyethylene Analog

Abstract An atomic‐level understanding of radiation‐induced damage in simple polymers like polyethylene is essential for determining how these chemical changes can alter the physical and mechanical properties of important technological materials such as plastics. Ensembles of quantum simulations of radiation damage in a polyethylene analog are performed using the Density Functional Tight Binding method to help bind its radiolysis and subsequent degradation as a function of radiation dose. Chemical degradation products are categorized with a graph theory approach, and occurrence rates of unsaturated carbon bond formation, crosslinking, cycle formation, chain scission reactions, and out‐gassing products are computed. Statistical correlations between product pairs show significant correlations between chain scission reactions, unsaturated carbon bond formation, and out‐gassing products, though these correlations decrease with increasing atom recoil energy. The results present relatively simple chemical descriptors as possible indications of network rearrangements in the middle range of excitation energies. Ultimately, the work provides a computational framework for determining the coupling between nonequilibrium chemistry in polymers and potential changes to macro‐scale properties that can aid in the interpretation of future radiation damage experiments on plastic materials.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Enabling Efficient and Accurate Computational Studies of MOF Reactivity via QM/MM and QM/QM Methods

Electronic structure calculations can provide unique insight into metal–organic framework (MOF) reactivity and defect formation. Such calculations can be broadly categorized as utilizing either periodic or cluster models, each with their respective advantages and disadvantages. In the present study, we demonstrate how multiscale methods can leverage the advantages of both approaches to enable high levels of accuracy and computational efficiency in studies of MOF reactivity. Using defect formation in a zeolitic imidazolate framework (ZIF) as a prototypical example, we benchmark a quantum mechanics/molecular mechanics (QM/MM) scheme that enables highly efficient cluster-based calculations on MOFs. We demonstrate the importance of correctly accounting for the influence of both dative bond cleavage in the QM cluster and long-range mechanical coupling to the bulk to achieving accurate QM/MM studies of MOFs. We subsequently leverage these cluster models in a QM/QM scheme that goes beyond standard DFT to yield “gold-standard” correlated wave function results on MOFs at modest computational cost. Crucially, we find several cases in which the incorporation of these correlated corrections yields qualitatively important corrections over conventional DFT values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Understanding flavin electronic structure and spectra

Abstract Flavins have emerged as central to electron bifurcation, signaling, and countless enzymatic reactions. In bifurcation, two electrons acquired as a pair are separated in coupled transfers wherein the energy of both is concentrated on one of the two. This enables organisms to drive demanding reactions based on abundant low‐grade chemical fuel. To enable incorporation of this and other flavin capabilities into designed materials and devices, it is essential to understand fundamental principles of flavin electronic structure that make flavins so reactive and tunable by interactions with protein. Emerging computational tools can now replicate spectra of flavins and are gaining capacity to explain reactivity at atomistic resolution, based on electronic structures. Such fundamental understanding can moreover be transferrable to other chemical systems. A variety of computational innovations have been critical in reproducing experimental properties of flavins including their electronic spectra, vibrational signatures, and nuclear magnetic resonance (NMR) chemical shifts. A computational toolbox for understanding flavin reactivity moreover must be able to treat all five oxidation and protonation states, in addition to excited states that participate in flavoprotein's light‐driven reactions. Therefore, we compare emerging hybrid strategies and their successes in replicating effects of hydrogen bonding, the surrounding dielectric, and local electrostatics. These contribute to the protein's ability to modulate flavin reactivity, so we conclude with a survey of methods for incorporating the effects of the protein residues explicitly, as well as local dynamics. Computation is poised to elucidate the factors that affect a bound flavin's ability to mediate stunningly diverse reactions, and make life possible. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics Electronic Structure Theory > Combined QM/MM Methods Theoretical and Physical Chemistry > Spectroscopy

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The nature of the chemical bond

The nature of the chemical bond has long been a topic of much interest, beginning with the speculations of Isaac Newton about the “forces” that hold atoms together to the famous book by Linus Pauling with this title. For chemists, the existence of bonds between the atoms in a molecule is without question, but what are they, how can they be categorized, and what accounts for their existence? Furthermore, early theories focused on the attraction of electrical charges of opposite sign, which could account for the binding in many inorganic molecules. But what would account for the binding in electrically neutral organic molecules? Slightly more than a century ago, G. N. Lewis noted that the chemical bond appeared to be associated with electron pairs. Shortly after the discovery of the wave equation by Irwin Schrödinger in 1925-6, Heitler and London showed that quantum mechanics, in the form of what would eventually be called valence bond (VB) theory, accounted for the binding in that most improbable of molecules, the simple H 2 molecule.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Diffusion Monte Carlo approaches for studying nuclear quantum effects in fluxional molecules

Abstract Diffusion quantum Monte Carlo (DMC) provides a powerful approach for obtaining the ground state energy and wave function of molecules, ions, and molecular clusters. The approach is uniquely well suited for studies of fluxional molecules, which undergo large amplitude vibrational motions even in their ground state. In contrast to the electronic structure problem, where the wave function must be antisymmetric with respect to exchange of any pair of electrons, the wave function for the ground vibrational state is nodeless. This greatly simplifies the application of DMC for vibrational problems. Because there is not a single potential function that can be used to describe the intramolecular and intermolecular interactions in all molecular systems, most methods that are used to describe nuclear quantum effects rely on a carefully chosen zero‐order description of the molecular vibrations. In contrast, DMC calculations can be performed in Cartesian coordinates, making the DMC algorithm easily transferable between different chemical systems. In this contribution, the theory that underlies DMC will be discussed along with important considerations for performing DMC calculations. Extensions for evaluating vibrationally excited states and molecular properties are also discussed. Insights that can be obtained from DMC calculations are illustrated in the context of the protonated water clusters. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Theoretical and Physical Chemistry > Spectroscopy

Chemistry↗
DOE OSTI2021

ThickBrick: optimal event selection and categorization in high energy physics. Part I. Signal discovery

We provide a prescription called ThickBrick to train optimal machine-learning-based event selectors and categorizers that maximize the statistical significance of a potential signal excess in high energy physics (HEP) experiments, as quantified by any of six different performance measures. For analyses where the signal search is performed in the distribution of some event variables, our prescription ensures that only the information complementary to those event variables is used in event selection and categorization. This eliminates a major misalignment with the physics goals of the analysis (maximizing the significance of an excess) that exists in the training of typical ML-based event selectors and categorizers. In addition, this decorrelation of event selectors from the relevant event variables prevents the background distribution from becoming peaked in the signal region as a result of event selection, thereby ameliorating the challenges imposed on signal searches by systematic uncertainties. Our event selectors (categorizers) use the output of machine-learning-based classifiers as input and apply optimal selection cutoffs (categorization thresholds) that are functions of the event variables being analyzed, as opposed to flat cutoffs (thresholds). These optimal cutoffs and thresholds are learned iteratively, using a novel approach with connections to Lloyd’s k-means clustering algorithm. We provide a public, Python implementation of our prescription, also called ThickBrick, along with usage examples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Pointer States and Quantum Darwinism with Two-Body Interactions

Quantum Darwinism explains the emergence of classical objectivity within a quantum universe. However, to date, most research on quantum Darwinism has focused on specific models and their stationary properties. To further our understanding of the quantum-to-classical transition, it appears desirable to identify the general criteria a Hamiltonian has to fulfill to support classical reality. To this end, we categorize all N-qubit models with two-body interactions, and show that only those with separable interaction of the system and environment can support a pointer basis. We further demonstrate that “perfect” quantum Darwinism can only emerge if there are no intra-environmental interactions. Our analysis is complemented by solving the ensuing dynamics. We find that in systems exhibiting information scrambling, the dynamical emergence of classical objectivity directly competes with the non-local spread of quantum correlations. Our rigorous findings are illustrated through the numerical analysis of four representative models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Frustrated Kondo impurity triangle: A simple model of deconfinement

We report that the concepts of deconfinement and topological order are of great current interest for quantum information science and for our understanding of quantum materials. Here, we introduce a simple model of three antiferromagnetically coupled Kondo impurities, a Kondo triangle, which can be used to further extend the application of these concepts to electronic systems. We show that, by tuning the magnetic frustration, the Kondo triangle undergoes a quantum phase transition between two phases of unbroken symmetry, signaling a phase transition beyond the Landau paradigm. We demonstrate that the frustrated spin liquid phase is described by a three-channel Kondo (3CK) fixed point and thus displays an irrational ground state degeneracy. Using an Abrikosov pseudofermion representation, this quantum state is categorized by an emergent U(1) gauge field and its projective symmetry group. The gauge theory is deconfining in the sense that a miniature Wilson loop orders and topological defects (instantons in the gauge field) are expelled. This phase persists in the presence of moderate Kondo screening until proliferation of topological defects leads to a quantum phase transition to an unfrustrated Fermi liquid phase. Based on this evidence, we propose that the 3CK phase displays topological order in a similar sense as gapless spin liquids.

36 MATERIALS SCIENCE↗