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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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At least 127 records · Page 7

Electronic Structure Theories of Singlet Fission and Multiple Exciton Generation (Final Report)

This DOE grant supported the development of electronic structure theory, algorithms, and computer programs for simulating singlet fission and multiple excision generation processes from Sept. 2013 to Aug. 2018 (which was terminated due to the PI’s departure from Northwestern University to industry). One of the main achievements is the development of the so-called active space decomposition (ASD) method hat describes exciton dynamics in organic semiconductors and spin dynamics in strongly correlated materials. The resulting software was interfaced with the Brilliantly Advanced General Electronic-structure Library (BAGEL) package and widely disseminated to the research community.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The 先生 (SENSEI†) Experiment: sub-GeV dark matter searches with skipper-CCD

Skipper-CCDs are pixeled Silicon-based detectors that can perform multiple non-disruptive measurements of the same charge package. Their sub-electron resolution allows the detection of eV energy transfers, such as that expected from ultra-light dark matter interacting with electrons in a Silicon target. SENSEI (Sub-Electron Noise Skipper Experimental Instrument) is the first experiment to use Skipper-CCD for this purpose and to publish world-leading results using this technology. In this talk, we present an overview of the SENSEI experiment and the current status after the successful commissioning of the second batch of science-grade sensors at SNOLAB. We will also discuss the prospects in rare-events searches with skipper-CCDs: from SENSEI’s 100 g detector to OSCURA’s 10 kg array, and more.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Solid-State Mixed-Potential Electrochemical Sensors for Natural Gas Leak Detection and Quality Control (Final Technical Report)

Mitigation of methane emissions are a critical factor to limiting the impact of the natural gas industry on global climate change. Throughout the period of 2020-2024, the University of New Mexico and its commercialization partner and subcontractor, SensorComm Technologies, Inc. (SCT), have worked together to develop a low-cost Artificial Intelligence (AI)-driven Internet of Things (IoT)-based multi-gas sensor platform for methane emissions detection. In the final year of the project, we extended this work to include hydrogen detection in support of a transition to a hydrogen economy where hydrogen could be transported through existing natural gas infrastructure. Mixed potential electrochemical sensors were first prototyped by ceramic additive manufacturing and then transitioned to conventional ceramic manufacturing tape casting and screen-printing technologies in preparation for mass production. Demonstrated limits of detection of 5 ppm of methane in natural gas and 1 ppm of hydrogen were measured. These limits of detection are among the lowest of solid-state electrochemical sensors that have been reported in the literature or available in the industry. Machine learning algorithms were developed to identify natural gas mixtures with > 98% accuracy level and quantify methane concentrations at 97% accuracy. The presence of hydrogen could also be identified, and its concentration quantified at these accuracy levels. These algorithms were optimized for running on portable computing hardware which enabled > 1 Hz processing rates. A portable packaged IoT system was integrated with the electrochemical sensor in collaboration with SCT. The package consists of readout electronics with < 1 mV resolution, sensor temperature control, and data transmission over cellular wireless and/or Wi-Fi networks. Field testing was performed in two rounds at Colorado State University’s Methane Emissions Technology Evaluation Center (CSU METEC). The first round of testing demonstrated successful measurements of methane from an underground natural gas leak of 20 standard liters per minute (SLPM), which agreed with previously published literature using more sophisticated and expensive analytical equipment. The second round of testing showed that an above ground leak of 2 SLPM of hydrogen could be detected at 32 ft. This project has resulted in six published peer reviewed journal articles, over ten presentations at professional conferences, and one full patent application filed in 2023. Future work on this project includes increased sensitivity, higher production yields, and applications in the hydrogen safety and flare emissions monitoring spaces.

03 NATURAL GAS↗

The SENSEI Experiment: sub-GeV dark matter searches with skipper-CCDs

Skipper-CCDs are pixeled Silicon-based detectors that can perform multiple non-disruptive measurements of the same charge package. Their sub-electron resolution allows the detection of eV energy transfers, such as that expected from ultra-light dark matter interacting with electrons in a Silicon target. SENSEI (Sub-Electron Noise Skipper Experimental Instrument) is the first experiment to use Skipper-CCD for this purpose and to publish world-leading results using this technology. In this talk, we present an overview of the SENSEI experiment and the current status after the successful commissioning of the second batch of science-grade sensors at SNOLAB. We will also discuss the prospects in rare-events searches with skipper-CCDs: from SENSEI’s 100 g detector to OSCURA’s 10 kg array, and more.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Advanced Packaging Designs (Keystone Project 1)

The primary deliverable for this project will be to demonstrate an optimized power module design, with a ceramic-free electrically insulating substrate, through the development of a rapid multiphysics optimization workflow.

ADVANCED PROPULSION SYSTEMS↗

Power Electronics Materials and Bonded Interfaces - Reliability and Lifetime

Advanced packaging technologies are currently being designed and developed by the power electronics industry however, the maximum operating temperature is still limited to 175 degrees Celsius for the silicon carbide devices. Bonded materials such as sintered copper and polymeric materials are potential candidates for high temperature operation, but it is critical to characterize and evaluate its reliability under harsh operating conditions. In this project, we discuss the results of the accelerated experiments conducted on sintered copper and polymeric materials. Additionally, a novel framework to develop the lifetime prediction model of bonded interfaces through employing statistical and machine learning models are described. In this task, scanning acoustic microscope images of bonded interfaces obtained under thermal cycling experiments are used as the data.

ENGINEERING↗

SmoQyDQMC.jl: A flexible implementation of determinant quantum Monte Carlo for Hubbard and electron-phonon interactions

We introduce the SmoQyDQMC.jl package, a Julia implementation of the determinant quantum Monte Carlo algorithm. SmoQyDQMC.jl supports generalized tight-binding Hamiltonians with on-site Hubbard and generalized electron-phonon ( e e -ph) interactions, including non-linear e e -ph coupling and anharmonic lattice potentials. Our implementation uses hybrid Monte Carlo methods with exact forces for sampling the phonon fields, enabling efficient simulation of low-energy phonon branches, including acoustic phonons. The SmoQyDQMC.jl package also uses a flexible scripting interface, allowing users to adapt it to different workflows and interface with other software packages in the Julia ecosystem. The code for this package can be downloaded from our GitHub repository at https://github.com/SmoQySuite/SmoQyDQMC.jl or installed using the Julia package manager. The online documentation, including examples, can be obtained from our document page at https://smoqysuite.github.io/SmoQyDQMC.jl/stable/.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

System and method for scalable optical interconnect for quantum computing

The present disclosure relates to an interconnect system for interfacing an electronic subsystem to a qubit package, wherein the qubit package has a plurality of independent qubits. The system makes use of an optical fiber cable having a plurality of optical fibers, which is interfaced to the electronic subsystem. A 3D optical structure is used which has a plurality of internal waveguides, and which is configured to interface the optical fiber cable to the qubit package. The 3D optical structure further has at least one subsystem for using the plurality of waveguides to receive signals of a first type from at least one of the qubits package or the optical fiber cable, to convert the signals from the first type to a second type, and to transmit the signals in the second type to the other one of the fiber optic cable or the qubit package.

Patra, Susant K.↗

First-Principles Calculations of Thermoelectric Transport Properties of Quaternary and Ternary Bulk Chalcogenide Crystals

Chalcogenide crystals have a wide range of applications, especially as thermoelectric materials for energy conversion. Thermoelectric materials can be used to generate an electric current from a temperature gradient based on the Seebeck effect and based on the Peltier effect, and they can be used in cooling applications. Using first-principles calculations and semiclassical Boltzmann theory, we have computed the Seebeck coefficient, electrical conductivity, electronic thermal conductivity, power factor, and figure of merit of 30 chalcogenide crystals. A Quantum Espresso package is used to calculate the electronic properties and locate the Fermi level. The transport properties are then calculated using the BoltzTraP code. The 30 crystals are divided into two groups. The first group has four crystals with quaternary composition (A 2 BCQ 4 ) (A = Tl; B = Cd, Hg; C = Si, Ge, Sn; Q = S, Se, Te). The second group contains 26 crystals with the ternary composition (A’B’Q 2 ) (A’ = Ag, Cu, Au, Na; B’ = B, Al, Ga, In; Q = S, Se, Te). Among these 30 chalcogenide crystals, the results for 11 crystals: Tl 2 CdGeSe 4 , Tl 2 CdSnSe 4 , Tl 2 HgSiSe 4 , Tl 2 HgSnS 4 , AuBSe 2 , AuBTe 2 , AuAlTe 2 , AuGaTe 2 , AuInTe 2 , AgAlSe 2 , and AgAlTe 2 are revealed for the first time. In addition, temperature-dependent transport properties of pure and doped AgSbSe 2 and AgSbTe 2 crystals with dopant compositions of AgSb 0.94 Cd 0.06 Te 2 and AgSbTe 1.85 Se 0.15 were explored. These results provide an excellent database for bulk chalcogenides crucial for a wide range of potential applications in renewable energy fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TurboRVB: A many-body toolkit for ab initio electronic simulations by quantum Monte Carlo

TurboRVB is a computational package for ab initio Quantum Monte Carlo (QMC) simulations of both molecular and bulk electronic systems. The code implements two types of well established QMC algorithms: Variational Monte Carlo (VMC) and diffusion Monte Carlo in its robust and efficient lattice regularized variant. A key feature of the code is the possibility of using strongly correlated many-body wave functions (WFs), capable of describing several materials with very high accuracy, even when standard mean-field approaches [e.g., density functional theory (DFT)] fail. The electronic WF is obtained by applying a Jastrow factor, which takes into account dynamical correlations, to the most general mean-field ground state, written either as an antisymmetrized geminal power with spin-singlet pairing or as a Pfaffian, including both singlet and triplet correlations. This WF can be viewed as an efficient implementation of the so-called resonating valence bond (RVB) Ansatz, first proposed by Pauling and Anderson in quantum chemistry [L. Pauling, The Nature of the Chemical Bond (Cornell University Press, 1960)] and condensed matter physics [P.W. Anderson, Mat. Res. Bull 8, 153 (1973)], respectively. The RVB Ansatz implemented in TurboRVB has a large variational freedom, including the Jastrow correlated Slater determinant as its simplest, but nontrivial case. Moreover, it has the remarkable advantage of remaining with an affordable computational cost, proportional to the one spent for the evaluation of a single Slater determinant. Therefore, its application to large systems is computationally feasible. The WF is expanded in a localized basis set. Several basis set functions are implemented, such as Gaussian, Slater, and mixed types, with no restriction on the choice of their contraction. The code implements the adjoint algorithmic differentiation that enables a very efficient evaluation of energy derivatives, comprising the ionic forces. Thus, one can perform structural optimizations and molecular dynamics in the canonical NVT ensemble at the VMC level. For the electronic part, a full WF optimization (Jastrow and antisymmetric parts together) is made possible, thanks to state-of-the-art stochastic algorithms for energy minimization. In the optimization procedure, the first guess can be obtained at the mean-field level by a built-in DFT driver. The code was efficiently parallelized by using a hybrid MPI-OpenMP protocol, which is also an ideal environment for exploiting the computational power of modern Graphics Processing Unit accelerators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring the role of electronic structure on photo-catalytic behavior of carbon-nitride polymorphs

A fully self-consistent density-functional theory (DFT) with improved functionals is used herein to provide a comprehensive account of structural, electronic, and optical properties of C 3 N 4 polymorphs. Using our recently developed van Leeuwen-Baerends (vLB) corrected local-density approximation (LDA), we implemented LDA + vLB within full-potential N th -order muffin-tin orbital (FP-NMTO) method and show that it improves structural properties and band gaps compared to semi-local functionals (LDA/GGA). We demonstrate that the LDA + vLB predicts band-structure and work-function for well-studied 2D-graphene and bulk-Si in very good agreement with experiments, and more exact hybrid functional (HSE) calculations as implemented in the Quantum-Espresso (QE) package. The structural and electronic-structure (band gap) properties of C 3 N 4 polymorphs calculated using FP-NMTO-LDA + vLB is compared with more sophisticated hybrid-functional calculations. We also perform detailed investigation of photocatalytic behavior using QE-HSE method of C 3 N 4 polymorphs through work-function, band (valence and conduction) position with respect to water reduction and oxidation potential. Our results show $γ$-C 3 N 4 as the best candidate for photocatalysis among all the C 3 N 4 polymorphs but it is dynamically unstable at ‘zero’ pressure. We show that $γ$-C 3 N 4 can be stabilized under hydrostatic-pressure, which improves its photocatalytic behavior relative to water reduction and oxidation potentials.

36 MATERIALS SCIENCE↗

Runtime power allocation approach for GAMESS hybrid CPU‐GPU implementation

Summary To improve power consumption of applications at the runtime, modern processors provide frequency scaling capabilities, which along with workload optimization, are also available on GPU accelerators. In this work, a runtime strategy is proposed to distribute a given power allocation among the host components and the GPU according to the current application performance and power usage, such that GPU execution is prioritized over CPU for power allocation to maximize application performance. Next, the strategy is tailored to an application, a quantum‐chemistry package GAMESS for ab initio electronic structure calculations. Specifically, GAMESS hybrid CPU–GPU implementation as provided in the Libcchem library is considered. Experiments, performed on a 28‐core node with a Kepler GPU, resulted in performance gains of up to 50% under the proposed strategy and the largest power allocation considered here as compared with the scenario when this allocation was equally distributed among the computing‐platform components.

Sundriyal, Vaibhav↗

Runtime performance of a GAMESS quantum chemistry application offloaded to GPUs

Summary Computational chemistry is at the forefront of solving urgent societal problems, such as polymer upcycling and carbon capture. The complexity of modeling these processes at appropriate length and time scales is mainly manifested in the number and types of chemical species involved in the reactions and may require models of several thousand atoms and large basis sets to accurately capture the chemical complexity and heterogeneity in the physical and chemical processes. The quantum chemistry package General Atomic and Molecular Electronic Structure System (GAMESS) has a wide array of methods that can efficiently and accurately treat complex chemical systems. In this work, we have used the GAMESS Effective Fragment Molecule Orbital (EFMO) method for electronic structure calculation of a challenging mesoporous silica nanoparticle (MSN) model surrounded by about 4700 water molecules to investigate the strong scaling and GPU offloading on hybrid CPU‐GPU nodes. Experiments were performed on the Perlmutter platform at the National Energy Research Scientific Computing Center. Good strong scaling and load balancing have been observed on up to 88 hybrid nodes for different settings of the execution parameters for the calculation considered here. When GPUs are oversubscribed by offloading work from multiple CPU processes, using the NVIDIA multi‐process service (MPS) has consistently reduced time to solution and energy consumed. Additionally, for some configuration parameter settings, oversubscription with MPS improved performance by up to 5.8% over the case without oversubscription.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

PyQMC : An all-Python real-space quantum Monte Carlo module in PySCF

We describe a new open-source Python-based package for high accuracy correlated electron calculations using quantum Monte Carlo (QMC) in real space: PyQMC. PyQMC implements modern versions of QMC algorithms in an accessible format, enabling algorithmic development and easy implementation of complex workflows. Tight integration with the PySCF environment allows for a simple comparison between QMC calculations and other many-body wave function techniques, as well as access to high accuracy trial wave functions.

Wheeler, William A. (ORCID:0000000283910530)↗

All-electron APW+ lo calculation of magnetic molecules with the SIRIUS domain-specific package

We report APW+lo (augmented plane wave plus local orbital) density functional theory (DFT) calculations of large molecular systems using the domain specific SIRIUS multi-functional DFT package. The APW and FLAPW (full potential linearized APW) task and data parallelism options and the advanced eigen-system solver provided by SIRIUS can be exploited for performance gains in ground state Kohn–Sham calculations on large systems. This approach is distinct from our prior use of SIRIUS as a library backend to another APW+lo or FLAPW code. We benchmark the code and demonstrate performance on several magnetic molecule and metal organic framework systems. We show that the SIRIUS package in itself is capable of handling systems as large as a several hundred atoms in the unit cell without having to make technical choices that result in the loss of accuracy with respect to that needed for the study of magnetic systems.

Chemistry↗

High Precision, High Frequency Printed Antennas

An emerging trend in advanced manufacturing is printed electronics and sensors. The ability to print customized electronics and sensors integrated into functional packages is a growing need within a variety of growing markets such as smart manufacturing, internet of things (IoT), and the small satellite industry. Both Oak Ridge National Laboratory (ORNL) and the MITRE Corporation have seedling research efforts evaluating the potential for future printed electronic systems. High frequency, wide-bandwidth phased array antennas (i.e. >45 GHz) open the door to new applications. However, such sensors require currently prohibitively small feature sizes for commercial 3D printing technologies along with increasing challenges with connecting the driving electronics to such features. An additional finding with related advanced manufacturing challenges is the rapid production of 3D additive connectors for integration with commercial printed circuit boards (PCBs), primarily for advanced in-circuit inspection techniques. This work is developing additive manufacturing processes for producing connected and conductive fine scale 3D features. The primary focus was on aerosol-jet printing (AJP), which has a small minimum resolution (<50 µm) but is traditionally printed flat with small height/width aspect ratios <<1, and developing controls to enable fully 3D, high aspect ratio, and unsupported features. In Phase 1 of this effort, baselines of process performance were characterized, and test coupons produced for both ultra-high frequency antennas and microstructures to support reverse engineering of PCBs. In Phase 2, these efforts will be extended for system demonstration of ultra-high frequency antenna arrays, as well as reverse engineering circuitry for dense PCBs.

42 ENGINEERING↗

Design and implementation of a portable diagnostic system for Thomson scattering and optical emission spectroscopy measurements

A diagnostic system, which has a design goal of high-portability, has been designed at Oak Ridge National Laboratory (ORNL). This project aims at providing measurements of key plasma parameters (ne, Te, ni, Ti) for fusion-relevant devices, utilizing Thomson scattering (TS) and optical emission spectroscopy (OES). The innovative design employs mostly commercial off-the-shelf instrumentation and a traveling team of researchers to conduct measurements at various magnetic-confinement plasma devices. The TS diagnostic uses a Quantel Q-smart 1500 Nd:YAG laser with a 2ω harmonic generator to produce up to 850 mJ of 532 nm laser pulses at 10 Hz. Collection optics placed at the detection port consists of an 11 × 3 optical fiber bundle, where the TS diagnostic uses an 11 × 1 subset array of the fibers, the OES diagnostic uses another 11 fibers, and the remaining fibers are available to the host institution. The detection system is comprised of two separate IsoPlane-320 spectrometers with triple-grating turrets of various line spacing and two PI-MAX 4 intensified CCD detectors, used simultaneously to measure a broad range of ion, impurity, and electron parameters. The self-contained diagnostic package also includes a data processing and storage system. The design and initial implementation of the TS-OES diagnostic system are described. The experiments from the proof-of-principle operation of the portable package on a high density (∼2.5 × 1022 m−3) and low-temperature (∼5 eV) electrothermal arc source at ORNL are also discussed.

Kafle, N. (ORCID:000000028144787X)↗

Phoebe: a high-performance framework for solving phonon and electron Boltzmann transport equations

Understanding the electrical and thermal transport properties of materials is critical to the design of electronics, sensors, and energy conversion devices. Computational modeling can accurately predict material properties but, in order to be reliable, requires accurate descriptions of electron and phonon states and their interactions. While first-principles methods are capable of describing the energy spectrum of each carrier, using them to compute transport properties is still a formidable task, both computationally demanding and memory intensive, requiring integration of fine microscopic scattering details for estimation of macroscopic transport properties. To address this challenge, we present Phoebe—a newly developed software package that includes the effects of electron–phonon, phonon–phonon, boundary, and isotope scattering in computations of electrical and thermal transport properties of materials with a variety of available methods and approximations. This open source C++ code combines MPI-OpenMP hybrid parallelization with GPU acceleration and distributed memory structures to manage computational cost, allowing Phoebe to effectively take advantage of contemporary computing infrastructures. We demonstrate that Phoebe accurately and efficiently predicts a wide range of transport properties, opening avenues for accelerated computational analysis of complex crystals.

36 MATERIALS SCIENCE↗