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At least 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Towards atom-level understanding of metal oxide catalysts for the oxygen evolution reaction with machine learning

Abstract Green hydrogen production is crucial for a sustainable future, but current catalysts for the oxygen evolution reaction (OER) suffer from slow kinetics, despite many efforts to produce optimal designs, particularly through the calculation of descriptors for activity. In this study, we develop a dataset of density functional theory calculations of bulk and surface perovskite oxides, and adsorption energies of OER intermediates, which includes compositions up to quaternary and facets up to (555). We demonstrate that per-site properties of perovskite oxides such as Bader charge or band center can be tuned through element substitution and faceting, and develop a machine learning model that accurately predicts these properties directly from the local chemical environment. We leverage these per-site properties to identify promising perovskites with high theoretical OER activity. The identified design principles and promising materials provide a roadmap for closing the gap between current artificial catalysts and biological enzymes such as photosystem II.

Chemistry↗
DOE OSTI2024

Lithium inventory tracking as a non-destructive battery evaluation and monitoring method

Tracking the active lithium (Li) inventory in an electrode shows the true state of a Li battery, akin to a fuel gauge for an engine. However, non-destructive Li inventory tracking is currently unavailable. Here, in this work, we used the theoretical capacity of a transition metal oxide to convert capacity into a Li inventory analysis. The Li inventory in electrodes was tracked reliably to show how battery formulations and test methods affect performance. Contrary to capacity, Li inventory tracking reveals stoichiometric variations near the electrode–electrolyte interface. Verifiable results rationalized differences in measurements, clarifying and reducing interferences from cell formulations and experimental manipulations. By tracing four variables from formation to end-of-life, we characterize electrode and cell performance with a thermodynamic framework. Accurate rationalization of subtle differences in Li inventory utilization promises precise battery engineering, evaluation, failure analysis and risk mitigation. The method could be applicable from cell design optimization and fabrication to battery management, improving battery performance and reliability.

25 ENERGY STORAGE↗
DOE OSTI2022

Multi-fidelity information fusion with concatenated neural networks

Recently, computational modeling has shifted towards the use of statistical inference, deep learning, and other data-driven modeling frameworks. Although this shift in modeling holds promise in many applications like design optimization and real-time control by lowering the computational burden, training deep learning models needs a huge amount of data. This big data is not always available for scientific problems and leads to poorly generalizable data-driven models. This gap can be furnished by leveraging information from physics-based models. Exploiting prior knowledge about the problem at hand, this study puts forth a physics-guided machine learning (PGML) approach to build more tailored, effective, and efficient surrogate models. For our analysis, without losing its generalizability and modularity, we focus on the development of predictive models for laminar and turbulent boundary layer flows. In particular, we combine the self-similarity solution and power-law velocity profile (low-fidelity models) with the noisy data obtained either from experiments or computational fluid dynamics simulations (high-fidelity models) through a concatenated neural network. We illustrate how the knowledge from these simplified models results in reducing uncertainties associated with deep learning models applied to boundary layer flow prediction problems. The proposed multi-fidelity information fusion framework produces physically consistent models that attempt to achieve better generalization than data-driven models obtained purely based on data. While we demonstrate our framework for a problem relevant to fluid mechanics, its workflow and principles can be adopted for many scientific problems where empirical, analytical, or simplified models are prevalent. In line with grand demands in novel PGML principles, this work builds a bridge between extensive physics-based theories and data-driven modeling paradigms and paves the way for using hybrid physics and machine learning modeling approaches for next-generation digital twin technologies.

42 ENGINEERING↗
DOE OSTI2022

Quantum algorithm for electronic band structures with local tight-binding orbitals

While the main thrust of quantum computing research in materials science is to accurately measure the classically intractable electron correlation effects due to Coulomb repulsion, designing optimal quantum algorithms for simpler problems with well-understood solutions is a useful tactic to advance our quantum “toolbox”. With this in mind, we consider the quantum calculation of a periodic system’s single-electron band structure over a path through reciprocal space. Previous efforts have used the Variational Quantum Eigensolver algorithm to solve the energy of each band, which involves numerically optimizing the parameters of a variational quantum circuit to minimize a cost function, constructed as the expectation value of a Hamiltonian operator. Traditionally, a unique Hamiltonian operator is constructed for each k-point, so that many cost functions, each with their own parameter space, must be optimized to generate a single band. Similarly, calculating higher bands than the first has traditionally involved modifying the cost function with additional overlap terms to ensure higher-energy eigenstates are orthogonal to those of lower bands. In this paper, we adopt a direct space approach, using a novel hybrid first/second-quantized qubit mapping which allows us to construct a single Hamiltonian, and a single cost-function, suitable for solving the entire electronic band structure. In contrast to previous approaches, the k-point and the band index are selected by additional parameters in our quantum circuit, rather than through modifications to the cost function. The result is a technically and conceptually simpler approach to band structure calculations on a quantum computer. Moreover, we expect that the tools developed herein will motivate new strategies for tackling highly-correlated materials beyond the grasp of classical computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Ultrafast hole relaxation dynamics in quantum dots revealed by two-dimensional electronic spectroscopy

Elucidating the population dynamics of correlated electron-hole pairs (bound excitons) in semiconducting quantum dots (QDs) is key for developing our fundamental understanding of nanoscale photophysics as well as for the optimal design of devices, such as lasers. For decades, it was assumed that holes did not contribute to band edge bleach signals in QDs. Here, we employ two-dimensional electronic spectroscopy to monitor electron and hole dynamics in both CdSe and CdSe/CdS/ZnS QDs to probe electron and hole dynamics. Based on a combination of time and frequency resolution, we observe a previously unresolved bleaching signal in CdSe QDs on timescales faster than 30 fs due to hole cooling. Atomistic semiempirical pseudopotential calculations are used to rationalize the order of magnitude difference in the observed hole dynamics in CdSe and CdSe/CdS/ZnS QDs. This picture advances our understanding of QD excitonics past the prevailing continuum effective mass theories generally used to describe QD electronic structure and dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Light-trapping and recycling for extraordinary power conversion in ultra-thin gallium-arsenide solar cells

Here, we demonstrate nearly 30% power conversion efficiency in ultra-thin (~200 nm) gallium arsenide photonic crystal solar cells by numerical solution of the coupled electromagnetic Maxwell and semiconductor drift-diffusion equations. Our architecture enables wave-interference-induced solar light trapping in the wavelength range from 300-865 nm, leading to absorption of almost 90% of incoming sunlight. Our optimized design for 200 nm equivalent bulk thickness of GaAs, is a square-lattice, slanted conical-pore photonic crystal (lattice constant 550 nm, pore diameter 600 nm, and pore depth 290 nm), passivated with AlGaAs, deposited on a silver back-reflector, with ITO upper contact and encapsulated with SiO 2 . Our model includes both radiative and non-radiative recombination of photo-generated charge carriers. When all light from radiative recombination is assumed to escape the structure, a maximum achievable photocurrent density (MAPD) of 27.6 mA/cm 2 is obtained from normally incident AM 1.5 sunlight. For a surface non-radiative recombination velocity of 10 3 cm/s, this corresponds to a solar power conversion efficiency of 28.3%. When all light from radiative recombination is trapped and reabsorbed (complete photon recycling) the power conversion efficiency increases to 29%. If the surface recombination velocity is reduced to 10 cm/sec, photon recycling is much more effective and the power conversion efficiency reaches 30.6%.

14 SOLAR ENERGY↗
DOE OSTI2024

Additive manufacturing of LiCoO 2 electrodes via vat photopolymerization for lithium ion batteries

Additive manufacturing has the potential to revolutionize the fabrication of lithium-ion batteries for a diversity of applications including in portable, biomedical, aerospace, and the transportation fields. Standard commercial batteries consist of stacked layers of various components (current collectors, cathode, anode, separator and electrolyte) in a two-dimensional manner. By leveraging the latest advances in additive manufacturing and computer-aided design, an improved geometric and electrochemical configuration of these batteries can maximize energy efficiency while allowing design optimization to reduce dead space for a given application. In this work, a composite UV photosensitive resin was prepared and used as feedstock in a vat photopolymerization system. The resin was loaded with LiCoO 2 acting as electrochemically active material for the cathode of a lithium-ion battery, and was further improved with the addition of conductivity-enhancing carbonaceous additives. Challenges to additive manufacturing arise from the opacity and high viscosity of the composite nature of these electrochemically-active resins, which cause light refraction during selective UV curing. Subsequently, items were printed and subjected to a thermal post-processing step to obtain an adequate compromise between electrochemical performance and mechanical integrity. Both sintered and green state 3D printed cathodes were assembled into half-cell lithium-ion batteries using lithium metal as a reference and counter electrode. Electrochemical cycling of these batteries yielded satisfactory results approaching commercial LiCoO 2 cathodes’ performance, with the potential advantages of additive manufacturing – high surface area anode–cathode configurations for power performance as well as shape conformability.

25 ENERGY STORAGE↗
DOE OSTI2025

Discovery of hybrid chemical synthesis pathways with DORAnet

Developing efficient tools for discovering novel synthesis pathways is essential to advance chemical production methods that maximize the use of resources and energy. We introduce DORAnet (Designing Optimal Reaction Avenues Network Enumeration Tool), an open-source computational framework that addresses key limitations in current computer-aided synthesis planning (CASP) tools. DORAnet integrates both chemical/chemocatalytic (i.e., non-enzymatic) and enzymatic transformations, enabling the discovery of hybrid synthesis pathways. With 390 expert-curated chemical/chemocatalytic reaction rules and 3606 enzymatic rules derived from MetaCyc, it provides extensive flexibility for synthetic chemists and biotechnologists. The framework features customizable network expansion strategies, advanced filtering, and pathway search, ranking, and visualization tools. Validated against known reaction data, DORAnet successfully identified both established and novel synthesis routes for key industrial chemicals. In a case study involving 51 high-volume targets, DORAnet frequently ranked known commercial pathways among the top three results, demonstrating its practical relevance and ranking accuracy, while also uncovering numerous alternative (hybrid) synthesis pathways that were highly ranked.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Data Assimilation using Non-invasive Monte Carlo Sensitivity Analysis of Reactor Kinetics Parameters

Accurately predicting the criticality of an experiment before interacting with the experimental components is very important for criticality safety. Radiation transport software can be utilized to calculate the effective neutron multiplication factor of a nuclear system. Because of the integral nature of the effective neutron multiplication factor, the value calculated contains various sources of nuclear-data induced uncertainty. The sensitivity analysis and data assimilation technique presented in this paper exhibit one possible method of identifying and reducing the effective neutron multiplication factor nuclear-data induced uncertainty. The results presented in this work show that it is possible to use relative sensitivity coefficients of the prompt neutron decay constant and the effective delayed neutron fraction to 239 Pu nuclear data to reduce nuclear-data induced uncertainties in the effective neutron multiplication factor. This work has been utilized by members of the Los Alamos National Laboratory project EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) for optimally designing a new experiment, which will be used to reduce compensating errors in 239 Pu nuclear data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2011

Self-neutralized ion beam

A vacuum arc ion source provides high current beams of metal ions that have been used both for accelerator injection and for ion implantation, and in both of these applications the degree of space charge neutralization of the beam is important. In accelerator injection application, the beam from the ion source may be accelerated further (post-acceleration), redirected by a bending magnet(s), or focused with magnetic or electrostatic lenses, and knowledge of the beam space charge is needed for optimal design of the optical elements. In ion implantation application, any build-up of positive charge in the insulating targets must be compensated by a simultaneous flux of cold electrons so as to provide overall charge neutrality of the target. We show that in line-of-sight ion implantation using a vacuum arc ion source, the high current ion beam carries along its own background sea of cold electrons, and this copious source of electrons provides a ''self-neutralizing'' feature to the beam. Here we describe experiments carried out in order to demonstrate this effect, and we provide an analysis showing that the beam is space-charge-neutralized to a very high degree.

43 PARTICLE ACCELERATORS↗
DOE OSTI2011

Spectral Formulation for the Solution of Full-Wave Scattering from a Conducting Wedge Tipped with a Corrugated Cylinder

A spectral mode-matching technique is formulated to solve for the full-wave scattering of a corrugated cylinder-tipped wedge in the presence of an impressed electric or magnetic line source. Asymptotic approximations of large-order Bessel or Henkel functions for a fixed argument were introduced in order to overcome numerical difficulties in their regular series expansions. The corrugations on the conducting cylinder have the shape of annular sectors. The primary objective of this work is to investigate the impact of corrugations on the scattered field in the shadow region of the structure. An optimally designed corrugated cylinder placed at the tip of a conducting wedge can effectively suppress electromagnetic scattering in the shadow region. Obtained numerical results using the proposed approach prove the above concept. These results were validated against numerical data obtained using a nodal finite element method. The aim of this research is to utilize these corrugated tips in horn antenna design for the reduction of side-lobe level and the shaping of the respective E-plane radiation pattern.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Monte Carlo code G3sim for simulation of plastic scintillator detectors with wavelength shifter fiber readout

A detailed description of a compact Monte Carlo simulation code ''G3sim'' for studying the performance of a plastic scintillator detector with wavelength shifter (WLS) fiber readout is presented. G3sim was developed for optimizing the design of new scintillator detectors used in the GRAPES-3 extensive air shower experiment. Propagation of the blue photons produced by the passage of relativistic charged particles in the scintillator is treated by incorporating the absorption, total internal, and diffuse reflections. Capture of blue photons by the WLS fibers and subsequent re-emission of longer wavelength green photons is appropriately treated. The trapping and propagation of green photons inside the WLS fiber is treated using the laws of optics for meridional and skew rays. Propagation time of each photon is taken into account for the generation of the electrical signal at the photomultiplier. A comparison of the results from G3sim with the performance of a prototype scintillator detector showed an excellent agreement between the simulated and measured properties. The simulation results can be parametrized in terms of exponential functions providing a deeper insight into the functioning of these versatile detectors. G3sim can be used to aid the design and optimize the performance of scintillator detectors prior to actual fabrication that may result in a considerable saving of time, labor, and money spent.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Entropy-based separation of yeast cells using a microfluidic system of conjoined spheres

A physical model is derived to create a biological cell separator that is based on controlling the entropy in a microfluidic system having conjoined spherical structures. A one-dimensional simplified model of this three-dimensional problem in terms of the corresponding effects of entropy on the Brownian motion of particles is presented. This dynamic mechanism is based on the Langevin equation from statistical thermodynamics and takes advantage of the characteristics of the Fokker-Planck equation. This mechanism can be applied to manipulate biological particles inside a microfluidic system with identical, conjoined, spherical compartments. This theoretical analysis is verified by performing a rapid and a simple technique for separating yeast cells in these conjoined, spherical microfluidic structures. The experimental results basically match with our theoretical model and we further analyze the parameters which can be used to control this separation mechanism. Both numerical simulations and experimental results show that the motion of the particles depends on the geometrical boundary conditions of the microfluidic system and the initial concentration of the diffusing material. This theoretical model can be implemented in future biophysics devices for the optimized design of passive cell sorters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Induced spin-accumulation and spin-polarization in a quantum-dot ring by using magnetic quantum dots and Rashba spin-orbit effect

The effect of magnetic contacts on spin-dependent electron transport and spin-accumulation in a quantum ring, which is threaded by a magnetic flux, is studied. The quantum ring is made up of four quantum dots, where two of them possess magnetic structure and other ones are subjected to the Rashba spin-orbit coupling. The magnetic quantum dots, referred to as magnetic quantum contacts, are connected to two external leads. Two different configurations of magnetic moments of the quantum contacts are considered; the parallel and the anti-parallel ones. When the magnetic moments are parallel, the degeneracy between the transmission coefficients of spin-up and spin-down electrons is lifted and the system can be adjusted to operate as a spin-filter. In addition, the accumulation of spin-up and spin-down electrons in non-magnetic quantum dots are different in the case of parallel magnetic moments. When the intra-dot Coulomb interaction is taken into account, we find that the electron interactions participate in separation between the accumulations of electrons with different spin directions in non-magnetic quantum dots. Furthermore, the spin-accumulation in non-magnetic quantum dots can be tuned in the both parallel and anti-parallel magnetic moments by adjusting the Rashba spin-orbit strength and the magnetic flux. Thus, the quantum ring with magnetic quantum contacts could be utilized to create tunable local magnetic moments which can be used in designing optimized nanodevices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

A theoretical study on the performances of thermoelectric heat engine and refrigerator with two-dimensional electron reservoirs

Theoretical thermoelectric nanophysics models of low-dimensional electronic heat engine and refrigerator devices, comprising two-dimensional hot and cold reservoirs and an interconnecting filtered electron transport mechanism have been established. The models were used to numerically simulate and evaluate the thermoelectric performance and energy conversion efficiencies of these low-dimensional devices, based on three different types of electron transport momentum-dependent filters, referred to herein as k{sub x}, k{sub y}, and k{sub r} filters. Assuming the Fermi-Dirac distribution of electrons, expressions for key thermoelectric performance parameters were derived for the resonant transport processes, in which the transmission of electrons has been approximated as a Lorentzian resonance function. Optimizations were carried out and the corresponding optimized design parameters have been determined, including but not limited to the universal theoretical upper bound of the efficiency at maximum power for heat engines, and the maximum coefficient of performance for refrigerators. From the results, it was determined that k{sub r} filter delivers the best thermoelectric performance, followed by the k{sub x} filter, and then the k{sub y} filter. For refrigerators with any one of three filters, an optimum range for the full width at half maximum of the transport resonance was found to be <2k{sub B}T.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Electrothermally driven high-frequency piezoresistive SiC cantilevers for dynamic atomic force microscopy

Cantilevers with resonance frequency ranging from 1 MHz to 100 MHz have been developed for dynamic atomic force microscopy. These sensors are fabricated from 3C-SiC epilayers grown on Si(100) substrates by low pressure chemical vapor deposition. They use an on-chip method both for driving and sensing the displacement of the cantilever. A first gold metallic loop deposited on top of the cantilever is used to drive its oscillation by electrothermal actuation. The sensing of this oscillation is performed by monitoring the resistance of a second Au loop. This metallic piezoresistive detection method has distinct advantages relative to more common semiconductor-based schemes. The optimization, design, fabrication, and characteristics of these cantilevers are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

High-Q silicon photonic crystal cavity for enhanced optical nonlinearities

We fabricate and experimentally characterize an H0 photonic crystal slab nanocavity with a design optimized for maximal quality factor, Q = 1.7 × 10{sup 6}. The cavity, fabricated from a silicon slab, has a resonant mode at λ = 1.59 μm and a measured Q-factor of 400 000. It displays nonlinear effects, including high-contrast optical bistability, at a threshold power among the lowest ever reported for a silicon device. With a theoretical modal volume as small as V = 0.34(λ/n){sup 3}, this cavity ranks among those with the highest Q/V ratios ever demonstrated, while having a small footprint suited for integration in photonic circuits.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Numerical studies on the performance of a flow distributor in tank

Flow distributors are generally observed in several nuclear power plants. During core make-up tank (CMT) injection into the reactor, the condensation and thermal stratification are observed in the CMT, and rapid condensation disturbs the injection operation. To reduce the condensation phenomena in the tank, CMT was equipped with a flow distributor. The optimal design of the flow distributor is very important to ensure the structural integrity the CMT and its safe operation during certain transient or accident conditions. In the present study, we numerically investigated the performance of a flow distributor in tank with different shape factors such as the total number of holes, pitch-to-hole diameter ratios, diameter of the hole, and the area ratios. These data will contribute to a design of the flow distributor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗