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DOE OSTI2024

Overview of Quantum Sensing Materials and Techniques for Energy Sector Applications

The energy sector has become increasingly dependent upon highly sensitive sensing devices for a wide range of applications. Variables such as temperature, pH, electromagnetic fields, ions, and pressure must be measured with high precision, often in harsh conditions (e.g. highly corrosive environments due to high temperature, pressure and humidity). These sensors are deployed in infrastructure such as transformers, pipelines, mines, nuclear power plants, and other areas to ensure safe operating conditions and uninterrupted, optimized service. Moreover, new opportunities for sensors have emerged due to the expansion of smart grids/meters, driverless vehicles, and the discovery of new oil, gas, and critical mineral deposits. The continued maturation of quantum sensing technologies offers exciting opportunities for quantum-enhanced measurements within the energy sector that may provide significant improvements in sensitivity beyond the classical limit. Here, an overview of established and emerging quantum materials for sensing applications will be provided, from trapped ions to color centers in diamond and silicon carbide. Associated quantum sensing methods for these materials will be discussed, with an emphasis on platforms that are nearing commercial viability. Specific application opportunities within the energy sector for quantum sensors will then be analyzed, including oil/gas discovery, greenhouse gas emission monitoring, pH and ion sensing, current measurement in electric vehicle batteries, and quantum-enhanced spectroscopy. Remaining barriers, such as quantum sensor platform miniaturization and ruggedization, will also be analyzed. A specific project at the National Energy Technology Laboratory involving the functionalization of qubits using metal-organic frameworks for enhanced quantum sensing will also be highlighted. Here, nitrogen vacancy centers (NV) in nanodiamonds, a commercially available qubit with long coherence times and utilizable quantum properties at room temperature, are encapsulated in a controlled way using the metal-organic framework ZIF-8. The ZIF-8 provides a well-defined, porous scaffold that can be controlled to promote the selective uptake of specific target analytes, such as gas molecules or ions. The quantum sensing performance of this composite material is either preserved or enhanced following ZIF-8 encapsulation; the optically detected magnetic resonance response of the NV nanodiamonds with and without the ZIF-8 coating are identical, while the ZIF-8 coating increases the longitudinal spin relaxation lifetime (T1) of the NV centers, an important parameter for spin relaxometry-based quantum sensing experiments. Taken together, these results demonstrate the importance of qubit functionalization as a crucial step for rationally designing high performance quantum sensors.

Crawford, Scott↗

DOE OSTI2019

Machine Learning-Guided Approach for Studying Solvation Environments

Molecular-level understanding and characterization of solvation environments are often needed across chemistry, biology, and engineering. Toward practical modeling of local solvation effects of any solute in any solvent, in this work, we report a static and all-quantum mechanics-based cluster-continuum approach for calculating single-ion solvation free energies. This approach uses a global optimization procedure to identify low-energy molecular clusters with different numbers of explicit solvent molecules and then employs the smooth overlap for atomic positions learning kernel to quantify the similarity between different low-energy solute environments. From these data, we use sketch maps, a nonlinear dimensionality reduction algorithm, to obtain a two-dimensional visual representation of the similarity between solute environments in differently sized microsolvated clusters. After testing this approach on different ions having charges 2+, 1+, 1–, and 2–, we find that the solvation environment around each ion can be seen to usually become more similar in hand with its calculated single-ion solvation free energy. Without needing either dynamics simulations or an a priori knowledge of local solvation structure of the ions, this approach can be used to calculate solvation free energies within 5% of experimental measurements for most cases, and it should be transferable for the study of other systems where dynamics simulations are not easily carried out.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Vertical-Substrate MPCVD Epitaxial Nanodiamond Growth

Color center-containing nanodiamonds have many applications in quantum technologies and biology. Diamondoids, molecular-sized diamonds have been used as seeds in chemical vapor deposition (CVD) growth. However, optimizing growth conditions to produce high crystal quality nanodiamonds with color centers requires varying growth conditions that often leads to ad-hoc and time-consuming, one-at-a-time testing of reaction conditions. In order to rapidly explore parameter space, we developed a microwave plasma CVD technique using a vertical, rather than horizontally oriented stage-substrate geometry. With this configuration, temperature, plasma density, and atomic hydrogen density vary continuously along the vertical axis of the substrate. Finally, this variation allowed rapid identification of growth parameters that yield single crystal diamonds down to 10 nm in size and 75 nm diameter optically active center silicon-vacancy (Si-V) nanoparticles. Furthermore, this method may provide a means of incorporating a wide variety of dopants in nanodiamonds without ion irradiation damage.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Thermoelectric transport coefficients in mono-layer MoS{sub 2} and WSe{sub 2}: Role of substrate, interface phonons, plasmon, and dynamic screening

The thermoelectric transport coefficients of electrons in two recently emerged transition metal di-chalcogenides (TMD), MoS{sub 2} and WSe{sub 2}, are calculated by solving Boltzmann transport equation using Rode's iterative technique in the diffusive transport regime and the coupled current (electrical and heat) equations. Scattering from remote phonons along with the hybridization of TMD plasmon with remote phonon modes and dynamic screening under linear polarization response are investigated in TMDs sitting on a dielectric environment. The transport coefficients are obtained for a varying range of temperature and doping density for three different types of substrates—SiO{sub 2}, Al{sub 2}O{sub 3}, and HfO{sub 2}. The Seebeck co-efficient for MoS{sub 2} and WSe{sub 2} is found to be higher than 3D semiconductors even with diffusive transport. The electronic thermal conductivity is found to be low, however, the thermoelectric figure of merit is limited by the high phonon thermal conductivity. It is found that judicious selection of a dielectric environment based on temperature of operation and carrier density is crucial to optimize the thermoelectric performance of TMD materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Toward quantum Monte Carlo forces on heavier ions: Scaling properties

Quantum Monte Carlo (QMC) forces have been studied extensively in recent decades because of their importance with spectroscopic observables and geometry optimization. Here, we benchmark the accuracy and computational cost of QMC forces. The zero-variance zero-bias (ZVZB) force estimator is used in standard variational and diffusion Monte Carlo simulations with mean-field based trial wavefunctions and atomic pseudopotentials. Statistical force uncertainties are obtained with a recently developed regression technique for heavy tailed QMC data [P. Lopez Rios and G. J. Conduit, Phys. Rev. E 99, 063312 (2019)]. By considering selected atoms and dimers with elements ranging from H to Zn (1 ≤ Z eff ≤ 20), we assess the accuracy and the computational cost of ZVZB forces as the effective pseudopotential valence charge, Z eff , increases. We find that the costs of QMC energies and forces approximately follow simple power laws in Zeff. The force uncertainty grows more rapidly, leading to a best case cost scaling relationship of approximately Z e ff 6.5 ( 3 ) for diffusion Monte Carlo. We find that the accessible system size at fixed computational cost scales as Z e ff − 2 , insensitive to model assumptions or the use of the “space warp” variance-reduction technique. Our results predict the practical cost of obtaining forces for a range of materials, such as transition metal oxides where QMC forces have yet to be applied, and underscore the importance of further developing force variance-reduction techniques, particularly for atoms with high Z eff .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Two-frequency sub-Doppler spectroscopy of the caesium D{sub 1} line in various configurations of counterpropagating laser beams

Sub-Doppler resonances in caesium vapours are studied in a laser field produced by counterpropagating two-frequency light beams with mutually orthogonal linear polarisations. The beams are in resonance with optical transitions in the D{sub 1} line, the frequency difference of the field spectral components being equal to the hyperfine ground-state splitting in the Cs atom (∼9.2 GHz). It has already been shown that in this configuration, the hypercontrast effect can be observed for sub-Doppler resonances, which makes this configuration promising for the employment in new-generation miniature optical frequency standards. In the present work, two different two-frequency configurations are compared with each other and with the single-frequency configuration widely used in practice for observing saturated absorption resonances. The parameters of nonlinear resonances are measured at various temperatures of caesium vapours and at different optical field intensities. The results of the investigations performed make it possible to find an optimal two-frequency scheme for exciting nonlinear resonances and to estimate a potential of the scheme for its applications in quantum metrology. (laser spectroscopy of atoms)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Novel Sensors for Particle Tracking: a Contribution to the Snowmass Community Planning Exercise of 2021

Five contemporary technologies are discussed in the context of their potential roles in particle tracking for future high energy physics applications. These include sensors of the 3D configuration, in both diamond and silicon, submicron-dimension pixels, thin film detectors, and scintillating quantum dots in gallium arsenide. Drivers of the technologies include radiation hardness, excellent position, vertex, and timing resolution, simplified integration, and optimized power, cost, and material.

Detectors↗

DOE OSTI2022

Novel Sensors for Particle Tracking: a Contribution to the Snowmass Community Planning Exercise of 2021

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRSDate not supplied

A Holistic DSMC Transport Database for Re-Entry and Ablation Modeling

Hybrid simulation frameworks combining Computational Fluid Dynamics (CFD) and Direct Simulation Monte Carlo (DSMC) are frequently employed to efficiently perform high-fidelity solutions of environments containing combined continuum/rarified flow. The use of DSMC, a stochastic, particle-based method, is necessary for high-Knudsen flow where continuum-based assumptions governing CFD break down. However, the DSMC methodology is generally very computationally inefficient to model the continuum regime. In a CFD/DSMC hybrid approach, obtaining an accurate, high-fidelity solution hinges on the consistent treatment of transport properties and the used thermo-chemical models employed within the two solvers. In principle, in regions where CFD and DSMC are both employed, the same gas mixture under the same conditions should have the same properties, regardless of simulation type. Observed differences should be due to non-equilibrium processes, rather than differences in physical models. While the transport models governing CFD and DSMC simulations are starkly different, they can effectively be linked via their use of reduced Chapman-Enskog collision integrals. In CFD, these integrals are typically stored as fitted polynomial expressions and used to directly compute gas transport properties via mixing rules or the full Chapman-Enskog formulation. In DSMC, they can be used to derive the collision parameters needed for the phenomenological collision cross-section models that govern particle interactions, via a Nelder-Mead optimization scheme. The goal of this work is to provide a unified DSMC transport database encompassing the vast majority of known gas species encountered during atmospheric entry, on Earth or any other Solar body. This goal is largely possible due to recently performed ab-initio quantum chemistry calculations. Combined with other high-fidelity literature sources, the planned database will consist of collision integral data for over 200 neutral and ionized species and over 17000 binary collisions. From these collision integrals, Nelder-Mead optimization is used to compute Variable Soft Sphere (VSS) collision model parameters for DSMC, fitted from 300 K to 20000 K. Initial comparisons of transport properties of relevant equilibrium gas mixtures show great agreement between CFD and DSMC-derived results. The completed database will be able to be readily applied to model binary collisions of any gas mixture containing the included species over the specified temperature range, making it a valuable tool for future planetary probe modeling efforts. An example is shown below. Equilibrium mixture transport properties for a 19-species Titan atmospheric model [4] are computed using both fitted VSS parameters and the original CFD collision integral values. Deviations in computed properties between the two approaches is less than 5% for the entire temperature range.

M R Gosma↗

DOE OSTI2017

Final Report: Hot Carrier Collection in Thin Film Silicon with Tailored Nanocrystalline/Amorphous Structure

This project developed, characterized, and perfected a new type of highly tunable nanocrystalline silicon (nc-Si:H) incorporating quantum confined silicon nanoparticles (SiNPs). A dual zone deposition process and system were developed and demonstrated. The depositions of SiNPs, the amorphous phase, and co-deposited material were characterized and optimized. Material design and interpretation of results were guided by new theoretical tools that examined both the electronic structure and carrier dynamics of this hybrid material. Heterojunction and p-i-n solar cells were demonstrated and characterized. Photo-thin-film-transistors allowed mobility to be studied as a function SiNP density in the films. Rapid (hot) transfer of carriers from the amorphous matrix to the quantum confined SiNPs was observed and connected to reduced photo-degradation. The results carry quantum confined Si dots from a novelty to materials that can be harnessed for PV and optoelectronic applications. The growth process is broadly extendable with alternative amorphous matrices, novel layered structures, and alternative NPs easily accessible. The hot carrier effects hold the potential for third generation photovoltaics.

14 SOLAR ENERGY↗

DOE OSTI2016

Selective-area growth of heavily n–doped GaAs nanostubs on Si(001) by molecular beam epitaxy

Using an aspect ratio trapping technique, we demonstrate molecular beam epitaxy of GaAs nanostubs on Si(001) substrates. Nanoholes in a SiO{sub 2} mask act as a template for GaAs-on-Si selective-area growth (SAG) of nanostubs 120 nm tall and ≤100 nm in diameter. We investigate the influence of growth parameters including substrate temperature and growth rate on SAG. Optimizing these parameters results in complete selectivity with GaAs growth only on the exposed Si(001). Due to the confined-geometry, strain and defects in the GaAs nanostubs are restricted in lateral dimensions, and surface energy is further minimized. We assess the electrical properties of the selectively grown GaAs nanostubs by fabricating heterogeneous p{sup +}–Si/n{sup +}–GaAs p–n diodes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

On the adaptivity and complexity embedded into differential evolution

This research deals with the comparison of the two modern approaches for evolutionary algorithms, which are the adaptivity and complex chaotic dynamics. This paper aims on the investigations on the chaos-driven Differential Evolution (DE) concept. This paper is aimed at the embedding of discrete dissipative chaotic systems in the form of chaotic pseudo random number generators for the DE and comparing the influence to the performance with the state of the art adaptive representative jDE. This research is focused mainly on the possible disadvantages and advantages of both compared approaches. Repeated simulations for Lozi map driving chaotic systems were performed on the simple benchmark functions set, which are more close to the real optimization problems. Obtained results are compared with the canonical not-chaotic and not adaptive DE. Results show that with used simple test functions, the performance of ChaosDE is better in the most cases than jDE and Canonical DE, furthermore due to the unique sequencing in CPRNG given by the hidden chaotic dynamics, thus better and faster selection of unique individuals from population, ChaosDE is faster.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

A Stochastic Quasi-Newton Method in the Absence of Common Random Numbers

We present Q-SASS, a quasi-Newton method for unconstrained stochastic optimization that does not rely on common random numbers. Most existing quasi-Newton approaches leverage common random numbers to construct second-order updates. However, motivated by challenges in variational quantum algorithms—where such coordination is not possible—we consider the setting in which function values and gradients are accessible only through noisy probabilistic zeroth- and first-order oracles, and no common random numbers can be exploited. We derive high-probability tail bounds on the iteration complexity of our algorithm for nonconvex, convex, and strongly convex (more generally, those satisfying the PL condition) objective functions. Finally, we demonstrate the empirical benefits of our quasi-Newton updating scheme on both synthetic and quantum chemistry problems.

Complexity bound↗

DOE OSTI2016

Enhanced light extraction efficiency of GaN-based light-emittng diodes by nitrogen implanted current blocking layer

Highlights: • A nitrogen implanted current-blocking layer was successfully demonstrated. • Light-extraction efficiency and radiant intensity was increased by more than 20%. • Ion implantation was successfully implemented in GaN based light-emitting diodes. - Abstract: GaN-based light emitting diodes (LEDs) with a nitrogen implanted current-blocking layer (CBL) were successfully demonstrated for improving the light extraction efficiency (LEE) and radiant intensity. The LEE and radiant intensity of the LEDs with a shallow implanted CBL with nitrogen was greatly increased by more than 20% compared to that of a conventional LED without the CBL due to an increase in the effective current path, which reduces light absorption at the thick p-pad electrode. Meanwhile, deep implanted CBL with a nitrogen resulted in deterioration of the LEE and radiant intensity because of formation of crystal damage, followed by absorption of the light generated at the multi-quantum well(MQW). These results clearly suggest that ion implantation method, which is widely applied in the fabrication of Si based devices, can be successfully implemented in the fabrication of GaN based LEDs by optimization of implanted depth.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Accurate Prediction of Adiabatic Ionization Potentials of Organic Molecules using Quantum Chemistry Assisted Machine Learning

In previous work (Dandu et al., J. Phys. Chem. A, 2022, 126, 4528–4536), we were successful in predicting accurate atomization energies of organic molecules using machine learning (ML) models, obtaining an accuracy as low as 0.1 kcal/mol compared to the G4MP2 method. In this work, we extend the use of these ML models to adiabatic ionization potentials on data sets of energies generated using quantum chemical calculations. Atomic specific corrections that were found to improve atomization energies from quantum chemical calculations have also been used in this study to improve ionization potentials. Here, the quantum chemical calculations were performed on 3405 molecules containing eight or fewer non-hydrogen atoms derived from the QM9 data set, using the B3LYP functional with the 6–31G(2df,p) basis set for optimization. Low-fidelity IPs for these structures were obtained using two density functional methods: B3LYP/6–31+G(2df,p) and ωB97XD/6–311+G(3df,2p). Highly accurate G4MP2 calculations were performed on these optimized structures to obtain high-fidelity IPs to use in ML models based on the low-fidelity IPs. Our best performing ML methods gave IPs of organic molecules within a mean absolute deviation of 0.035 eV from the G4MP2 IPs for the whole data set. This work demonstrates that ML predictions assisted by quantum chemical calculations can be used to successfully predict IPs of organic molecules for use in high throughput screening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

An Experimental and Computational Approach to Investigating CO 2 Uptake of Cellulose-producing Algae from Cellulosic Ethanol Production (Final Report)

This project combined experimental algal cultures with predictive quantum calculations to evaluate system-level CO 2 uptake and conversion efficiency of cellulose-producing Nannochloropsis sp. algae. Recently, Nannochloropsis sp. has garnered attention as a novel host organism for converting low-cost CO 2 produced from cellulosic ethanol fermentations into algal lipids for biodiesel production and microcrystalline cellulose as a high-value co-product. As depicted in the figure below, this project (1) optimized Nannochloropsis salina (N. salina) cultures on effluent gas produced directly from cellulosic ethanol fermentation, (2) characterized the fermentation products, quantify cellulose production, and calculate CO 2 uptake efficiency with predictive quantum calculations, (3) conducted a life cycle and techno economic analysis of the proposed integration, and (4) provided training opportunities to students attending UC Riverside.

09 BIOMASS FUELS↗

DOE OSTI2016

Optimized thermal amplification in a radiative transistor

The thermal performance of a far-field radiative transistor made up of a VO{sub 2} base in between a blackbody collector and a blackbody emitter is theoretically studied and optimized. This is done by using the grey approximation on the emissivity of VO{sub 2} and deriving analytical expressions for the involved heat fluxes and transistor amplification factor. It is shown that this amplification factor can be maximized by tuning the base temperature close to its critical one, which is determined by the temperature derivative of the VO{sub 2} emissivity and the equilibrium temperatures of the collector and emitter. This maximization is the result of the presence of two bi-stable temperatures appearing during the heating and cooling processes of the VO{sub 2} base and enables a thermal switching (temperature jump) characterized by a sizeable variation of the collector-to-base and base-to-emitter heat fluxes associated with a slight change of the applied power to the base. This switching effect leads to the optimization of the amplification factor and therefore it could be used for thermal modulation purposes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Optimizing the quality factor of InP nanobeam cavities using atomic layer deposition

Photonic crystal nanobeam cavities are valued for their small mode volume, CMOS compatibility, and high coupling efficiency-crucial features for various low-power photonic applications and quantum information processing. However, despite their potential, nanobeam cavities often suffer from low quality factors due to fabrication imperfections that create surface states and optical absorption. In this work, we demonstrate InP nanobeam cavities with up to 140% higher quality factors by applying a coating of Al 2 O 3 via atomic layer deposition to terminate dangling bonds and reduce surface absorption. Additionally, changing the deposition thickness allows precise tuning of the cavity mode wavelength without compromising the quality factor. This Al 2 O 3 atomic layer deposition approach holds great promise for optimizing nanobeam cavities that are well-suited for integration with a wide range of photonic applications.

42 ENGINEERING↗