Search NASA⌕ Search

SEARCH · Search NASA

Results for “quantum mechanical simulations”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Power spectrum and form factor in random diagonal matrices and integrable billiards

Triggered by a controversy surrounding a universal behavior of the power spectrum in quantum systems exhibiting regular classical dynamics, we focus on a model of random diagonal matrices (RDM), often associated with the Poisson spectral universality class, and examine how the power spectrum and the form factor get affected by two-sided truncations of RDM spectra. Having developed a nonperturbative description of both statistics, we perform their detailed asymptotic analysis to demonstrate explicitly how a traditional assumption (lying at the heart of the controversy) – that the power spectrum is merely determined by the spectral form factor – breaks down for truncated spectra. This observation has important consequences as we further argue that bounded quantum systems with integrable classical dynamics are described by heavily truncated rather than complete RDM spectra. High-precision numerical simulations of semicircular and irrational rectangular billiards lend independent support to these conclusions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Structure- and Interaction-Based Design of Anti-SARS-CoV-2 Aptamers

Aptamer selection against novel infections is a complicated and time-consuming approach. Synergy can be achieved by using computational methods together with experimental procedures. In this study, we aim to develop a reliable methodology for a rational aptamer in silico et vitro design. The new approach combines multiple steps: (1) Molecular design, based on screening in a DNA aptamer library and directed mutagenesis to fit the protein tertiary structure; (2) 3D molecular modeling of the target; (3) Molecular docking of an aptamer with the protein; (4) Molecular dynamics (MD) simulations of the complexes; (5) Quantum-mechanical (QM) evaluation of the interactions between aptamer and target with further analysis; (6) Experimental verification at each cycle for structure and binding affinity by using small-angle X-ray scattering, cytometry, and fluorescence polarization. By using a new iterative design procedure, structure- and interaction-based drug design (SIBDD), a highly specific aptamer to the receptor-binding domain of the SARS-CoV-2 spike protein, was developed and validated. The SIBDD approach enhances speed of the high-affinity aptamers development from scratch, using a target protein structure. The method could be used to improve existing aptamers for stronger binding. This approach brings to an advanced level the development of novel affinity probes, functional nucleic acids. It offers a blueprint for the straightforward design of targeting molecules for new pathogen agents and emerging variants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Consistency-Enhanced Evolution for Variable Selection Can Identify Key Chemical Information from Spectroscopic Data

In the last few decades, spectroscopic techniques such as near-infrared (NIR) spectroscopy have gained wide applications in several industries, such as the pharmaceutical, agricultural, oil, and gas industries. As a result, various soft sensors have been developed to predict sample properties from spectroscopic readings. Because the spectroscopic readings at different wavelengths, especially at the adjacent wavelengths, are highly correlated, it has been shown that variable selection could significantly improve a soft sensor’s prediction performance while reducing the model complexity. To improve the prediction performance, most variable selection methods focus on identifying the variables (i.e., wavelengths or wavelength segments) that are strongly correlated with the dependent variable. Although many successful applications have been reported, these variable selection methods do have their limitations. Specifically, the selected wavelengths sometimes show little connection to the chemical bounds or functional groups presenting in the sample. In addition, the selected variables can be quite sensitive to the choice of the training samples. In this work, we address these limitations from a different perspective: if a variable selection algorithm can identify the truly relevant input variables, it should consistently identify the same subset of variables regardless of the choice of the training samples. Therefore, we propose a variable selection method that aims to improve the consistency of variable selection resulting from different training samples. Furthermore, the new algorithm is termed consistency-enhanced evolution for variable selection (CEEVS). To demonstrate the performance and robustness of CEEVS, we compare the proposed method with three representative variable selection methods using five published NIR data sets. These case studies clearly demonstrate that by improving the variable selection consistency, we can not only achieve improved prediction performance, but also identify key chemical information from spectroscopic data.

42 ENGINEERING↗
DOE OSTI2026

Characterizing Defect Dynamics in Silicon Carbide Using Symmetry-Adapted Collective Variables and Machine Learning Interatomic Potentials

Silicon carbide (SiC) divacancies are attractive candidates for spin-defect qubits possessing long coherence times and optical addressability. The high activation barriers associated with SiC defect formation and motion pose challenges for their study by first-principles molecular dynamics. In this work, we develop and deploy machine learning interatomic potentials (MLIPs) to accelerate defect dynamics simulations while retaining ab initio accuracy. We employ an active learning strategy comprising symmetry-adapted collective variable discovery and enhanced sampling to compile configurationally diverse training data, calculation of energies and forces using density functional theory (DFT), and training of an E(3)-equivariant MLIP based on the Allegro model. Here, the trained MLIP reproduces DFT-level accuracy in defect transition activation free energy barriers, enables the efficient and stable simulation of multidefect 216-atom supercells, and permits an analysis of the temperature dependence of defect thermodynamic stability and formation/annihilation kinetics to propose an optimal annealing temperature to maximally stabilize VV divacancies.

Computer simulations↗
DOE OSTI2022

Computational Insights into Malononitrile-Based Carbanions for CO 2 Capture

Although anionic N and O sites have been widely used in chemisorption of CO 2 , carbanions are much less explored for CO 2 capture. Here, in this study, we employ ab initio calculations and quantum mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) simulations to examine the interaction between CO 2 and the malononitrile carbanion, [CH(CN) 2 ] – . We have explored the potential energy surface of CO 2 binding by scanning the C–C distance between CO 2 and the central C site of the carbanion. We find that CO 2 prefers to bind to the nitrile group physically rather than to form a C–C bond via the carboxylation reaction at the sp 2 C site. Moreover, the two –CN groups can attract two CO 2 molecules at equal strength. The presence of an alkali metal ion enhances both physical and chemical interactions of CO 2 with the malononitrile carbanion. QM/MM MD simulations further confirm the preference of physical interaction in the condensed ionic liquid phase with a phosphonium cation. Our findings suggest that ionic liquids based on the malononitrile carbanion may have a high CO 2 solubility for carbon capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Photoluminescence, photophysics, and photochemistry of the V B - defect in hexagonal boron nitride

Extensive photochemical and spectroscopic properties of the V B - defect in hexagonal boron nitride are calculated, concluding that the observed photoemission associated with recently observed optically detected magnetic resonance is most likely of (1) 3 E'' → (1) 3 A' 2 origin. Rapid intersystem crossing from the defect's triplet to singlet manifolds explains the observed short excited-state lifetime and very low quantum yield. New experimental results reveal smaller intrinsic spectral bandwidths than previously recognized, interpreted in terms of spectral narrowing and zero-phonon-line shifting induced by the Jahn-Teller effect. Different types of computational methods are applied to map out the complex triplet and singlet defect manifolds, including the doubly ionized formulation of the equation-of-motion coupled-cluster theory that is designed to deal with the open-shell nature of defect states, and mixed quantum-mechanics/molecular-mechanics schemes enabling 5763-atom simulations. Finally, two other energetically feasible spectral assignments from among the singlet and triplet manifolds are considered, but ruled out based on inappropriate photochemical properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Studying Open Quantum Systems Relevant to Chemistry on a Trapped-Ion Quantum Simulator (Final Technical Report)

This project advances the trapped-ion quantum simulator as a versatile platform for studying open quantum system phenomena. We aim to contribute to the emerging quantum simulation toolkits and enable simulation of nanoscale energy processes. Trapped-ion platforms offer unique capabilities: their vibrational motion can be precisely manipulated, measured, and coherently coupled to auxiliary qubits. The vibrational mode can function both as a highly sensitive quantum sensor and a programmable environment bath. Using this platform, we achieved three major outcomes. First, we demonstrated using the vibrational mode as an ultrasensitive probe for testing fundamental physics, including possible nonlinear quantum mechanics effects. Second, we established that these modes can act as controllable baths in which tunable noise and loss can enhance or modify energy-transfer dynamics, providing the experimental preparation toward studying mechanisms relevant to chemical reactions and light-harvesting systems. Third, by introducing controllable nonlinear gain and loss, we showed theoretically how simulations using trapped ions can model vibrationally-assisted energy transport in a non‐Hermitian quantum system comprising a chromophore dimer weakly coupled to a vibrational mode. Exploring the non‐Hermitian dynamics of the whole system including vibrations, we found that energy transfer accompanied by absorption of phonons from a vibrational mode can be significantly enhanced near an exceptional point. This theoretical work on simulation of energy transfer processes in driven non‐Hermitian quantum systems revealed an interesting novel path to study open quantum systems dynamics under conditions of gain and loss. We then further explored the benefits of controllable gain and loss with an experimental realization of quantum analogs of nonlinear oscillators, namely, the van der Pol oscillator. Here we observed mutual synchronization mediated by collective dissipation between two oscillators. In parallel, we explored related quantum networking protocols using the same trapped-ion platform, developing fast, high-fidelity schemes for distributing entanglement. Together, these achievements show that trapped-ion vibrational modes provide a highly programmable and high-fidelity platform for investigating complex dissipative quantum behavior, while enabling new approaches to remote quantum sensing, energy science, and nonlinear quantum dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Deconvolving the components of the sign problem

Auxiliary field quantum Monte Carlo simulations of interacting fermions require sampling over a Hubbard-Stratonovich field h introduced to decouple the interactions. The weight for a given configuration involves the products of the determinant of matrices $M_σ(h)$ where σ labels the species, and hence is typically not positive definite. Indeed, the average sign $\langle \mathscr {L} \rangle$ of the determinants goes to zero exponentially with increasing spatial size and decreasing temperature for most Hamiltonians of interest. This statement, however, does not explicitly separate two possible origins for the vanishing of $\langle \mathscr {L} \rangle$. Does $\langle \mathscr {L} \rangle$ → 0 because randomly chosen field configurations have det[M(h)] < 0, or does the sign problem arise because the specific subset of configurations chosen by the weighting function have a greater preponderance of negative values? In the latter case, the process of weighting the configurations with |det[M(h)]| might steer the simulation to a region of configuration space of h where positive and negative determinants are equally likely, even though randomly chosen h would preferentially have determinants with a single dominant sign. Here in this paper, we address the relative importance of these two mechanisms for the vanishing of $\langle \mathscr {L} \rangle$ in quantum simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A graphene edge-mediated quantum gate

We propose a quantum gate architecture that allows for the systematic control of the effective exchange interactions between magnetic impurities embedded in nanoscale graphene flakes connected by a gated bridge. The entanglement between the magnetic moment and the edge states of the fragments is used to electrostatically tune the exchange interaction from ferro to antiferromagnetic by merely changing the bridge's carrier density. By characterizing the effects of size and coupling parameters, we explore different operation regimes of this device by means of exact calculations with the density matrix renormalization group. We analyze the results utilizing a simplified model that accounts for the main many-body mechanisms. Finally, we discuss how to use arrays of these devices to build quantum simulators for quantum many-body Hamiltonians.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Digital quantum simulation of non-equilibrium quantum many-body systems

Digital quantum simulation uses the capabilities of quantum computers to determine the dynamics of quantum systems, which are beyond the computability of modern classical computers. A notoriously challenging task in this field is the description of non-equilibrium dynamics in quantum many-body systems. In this study, we used the IBM quantum computers to simulate the non-equilibrium dynamics of few spin and fermionic systems. Our results reveal that with a combination of error mitigation, noise extrapolation and optimized initial state preparation, one can tackle the most important drawbacks of modern quantum devices. The systems we simulate demonstrate the potential for large-scale quantum simulations of light–matter interactions in the near future.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1999

Development of a Computational Chemical Vapor Deposition Model: Applications to Indium Nitride and Dicyanovinylaniline

A computational chemical vapor deposition (CVD) model is presented, that couples chemical reaction mechanisms with fluid dynamic simulations for vapor deposition experiments. The chemical properties of the systems under investigation are evaluated using quantum, molecular and statistical mechanics models. The fluid dynamic computations are performed using the CFD-ACE program, which can simulate multispecies transport, heat and mass transfer, gas phase chemistry, chemistry of adsorbed species, pulsed reactant flow and variable gravity conditions. Two experimental setups are being studied, in order to fabricate films of: (a) indium nitride (InN) from the gas or surface phase reaction of trimethylindium and ammonia; and (b) 4-(1,1)dicyanovinyl-dimethylaminoaniline (DCVA) by vapor deposition. Modeling of these setups requires knowledge of three groups of properties: thermodynamic properties (heat capacity), transport properties (diffusion, viscosity, and thermal conductivity), and kinetic properties (rate constants for all possible elementary chemical reactions). These properties are evaluated using computational methods whenever experimental data is not available for the species or for the elementary reactions. The chemical vapor deposition model is applied to InN and DCVA. Several possible InN mechanisms are proposed and analyzed. The CVD model simulations of InN show that the deposition rate of InN is more efficient when pulsing chemistry is used under conditions of high pressure and microgravity. An analysis of the chemical properties of DCVA show that DCVA dimers may form under certain conditions of physical vapor transport. CVD simulations of the DCVA system suggest that deposition of the DCVA dimer may play a small role in the film and crystal growth processes.

Cardelino, Carlos↗
NASA NTRS2002

Research in Computational Astrobiology

We present results from several projects in the new field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. We have developed a procedure for calculating long-range effects in molecular dynamics using a plane wave expansion of the electrostatic potential. This method is expected to be highly efficient for simulating biological systems on massively parallel supercomputers. We have perform genomics analysis on a family of actin binding proteins. We have performed quantum mechanical calculations on carbon nanotubes and nucleic acids, which simulations will allow us to investigate possible sources of organic material on the early earth. Finally, we have developed a model of protobiological chemistry using neural networks.

Chaban, Galina↗
NASA NTRS1998

Predictive Models for Semiconductor Device Design and Processing

The device feature size continues to be on a downward trend with a simultaneous upward trend in wafer size to 300 mm. Predictive models are needed more than ever before for this reason. At NASA Ames, a Device and Process Modeling effort has been initiated recently with a view to address these issues. Our activities cover sub-micron device physics, process and equipment modeling, computational chemistry and material science. This talk would outline these efforts and emphasize the interaction among various components. The device physics component is largely based on integrating quantum effects into device simulators. We have two parallel efforts, one based on a quantum mechanics approach and the second, a semiclassical hydrodynamics approach with quantum correction terms. Under the first approach, three different quantum simulators are being developed and compared: a nonequlibrium Green's function (NEGF) approach, Wigner function approach, and a density matrix approach. In this talk, results using various codes will be presented. Our process modeling work focuses primarily on epitaxy and etching using first-principles models coupling reactor level and wafer level features. For the latter, we are using a novel approach based on Level Set theory. Sample results from this effort will also be presented.

Meyyappan, Meyya↗
DOE OSTI2020

Imaging multiphoton ionization dynamics of CH 3 I at a high repetition rate XUV free-electron laser

XUV multiphoton ionization of molecules is commonly used in free-electron laser experiments to study charge transfer dynamics. However, molecular dissociation and electron dynamics, such as multiple photon absorption, Auger decay, and charge transfer, often happen on competing time scales, and the contributions of individual processes can be difficult to unravel. We experimentally investigate the Coulomb explosion dynamics of methyl iodide upon core–hole ionization of the shallow inner-shell of iodine (4d) and classically simulate the fragmentation by phenomenologically introducing ionization dynamics and charge transfer. Under our experimental conditions with medium fluence and relatively long XUV pulses (~75 fs), we find that fast Auger decay prior to charge transfer significantly contributes to the charging mechanism, leading to a yield enhancement of higher carbon charge states upon molecular dissociation. Furthermore, we argue for the existence of another charging mechanism for the weak fragmentation channels leading to triply charged carbon atoms. This study shows that classical simulations can be a useful tool to guide the quantum mechanical description of the femtosecond dynamics upon multiphoton absorption in molecular systems.

Optics↗
DOE OSTI2026

Mechanism of Tyrosine-Driven Deprotonation in Photosystem II Revealed by Multiscale Simulations

Photosystem II (PSII) drives light-induced water oxidation via stepwise redox transitions of its oxygen-evolving complex (OEC), a Mn 4 Ca cluster advancing through five intermediate S-states (S 0 –S 4 ). The S 2 → S 3 transition involves a redox event in which a Mn ion donates an electron to the redox-active tyrosine YZ, coupled to deprotonation of an OEC-bound water ligand─yet the underlying coupling mechanism remains unresolved. Time-resolved serial femtosecond crystallography (TR-SFX) has revealed transient electron density shifts near the redox-active tyrosine Y Z , interpreted as sequential oxidation and reduction, with reduction initiating ∼1 μs after excitation and substantially progressed by 30 μs. However, this interpretation conflicts with kinetics from photothermal beam deflection (PBD), time-resolved X-ray absorption spectroscopy (TR-XAS), and electron paramagnetic resonance (EPR), which place electron transfer at 190–400 μs and proton transfer around 30 μs. Here, we reconcile these discrepancies using quantum mechanics/molecular mechanics (QM/MM) and molecular dynamics (MD) simulations. We show that oxidation of P680 and Y Z breaks the symmetry of the nearby hydrogen bonds involving water molecule W4, displacing Y Z and replicating the TR-SFX features of Y Z and Q165 observed at 1 μs. This local perturbation propagates through a hydrogen-bond network, transmitting the electrostatic signal from Y Z to the E65-E312 dyad and triggering redox-coupled deprotonation via the Cl1 channel. By 30 μs, the hydrogen-bond symmetry is restored through deprotonation of W2 (or alternatively W1), reproducing the disappearance of TR-SFX density differences around Y Z and Q165 without requiring Y Z reduction. Our proposed mechanism also gives molecular insights into the O6* density, assigning it to water reorganization rather than a discrete Ca-bound hydroxide species. Here, our results reveal a detailed atomistic mechanism linking Y Z oxidation to long-range proton release and suggest a functional role for the nearby Cl – ion in proton transfer. More broadly, this study underscores the importance of hydrogen-bond dynamics in mediating redox-driven proton transport and demonstrates how integrative simulations can resolve mechanistic ambiguities.

Deprotonation↗
DOE OSTI2022

Spectral analysis of product formulas for quantum simulation

We consider the time-independent Hamiltonian simulation using the first order Lie–Trotter–Suzuki product formula under the assumption that the initial state is supported on a low-dimension subspace. By comparing the spectral decomposition of the original Hamiltonian and the effective Hamiltonian, we obtain better upper bounds for various conditions. Especially, we show that the Trotter step size needed to estimate an energy eigenvalue within precision ϵ using quantum phase estimation can be improved in scaling from ϵ to ϵ 1/2 for a large class of systems. Our results also depend on the gap condition of the simulated Hamiltonian.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Evolution of the marker distribution in gyrokinetic $δf$ particle-in-cell simulations

The evolution of the particle weight in a δf particle-in-cell simulation depends on the marker distribution that can evolve in a turbulent field due to turbulent diffusion. When Monte Carlo methods are used to implement the test particle collision operator, or when the particle motion is not strictly Hamiltonian in a collisionless simulation, the marker distribution will evolve along the particle trajectory and, in general, cannot be known exactly. A two-dimensional numerical marker distribution is proposed as an approximation. It is shown to be advantageous over other common methods for evaluating the marker distribution in long-time turbulence simulations. A generalized two-weight δf-method is proposed to mitigate the marker evolution problem.

, Monte Carlo methods↗