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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A machine-learning inverse model framework for rapid forecasting and history matching in unconventional reservoirs

Model-based optimization for real-time forecasting in unconventional reser-voirs requires novel methods and work?ows since the strategies and work?ows used in conventional reservoirs are either inapplicable, or prohibitively expen-sive and time-consuming. Insu?cient site data and computational expense of high-?delity simulations mean that work?ows with high-?delity simulations are not ideal for usage in comprehensive uncertainty quanti?cation stud-ies that require 1000s of forward model runs. We present an alternative, novel work?ow for unconventional reservoirs, based on the interplay between reduced-order models and machine-learning. Our physics-informed machine-learning (PIML) work?ow addresses the challenges to real-time reservoir management in uncoventionals, namely lack of data (the time-frame for which the wells have been producing), and computational expense of high-?delity modeling. We use the machine-learning paradigm of transfer-learning to bind together fast but less accurate reduced-order models with slow, but accurate high-?delity models and circumvent the di?culties inherent in the current state-of-the-art for unconventionals. Such a PIML work?ow, grounded in physics, is a viable candidate for real-time history matching and production forecasting in a fractured shale gas reservoir. The signi?cance of our approach is that while it is developed for a particu-lar well and site in the Marcelus Shale gas reservoir of the Appalachian basin (MSEEL), it is not wedded to it. We expect the same work?ow can be ap-plied to other shale formations (e.g., Woodford, Barnett, Utica, EagleFord) should site-data become available, using the same set of machine-learning techniques from transfer learning. Some ?ne-tuning (or minimal retraining of the neural networks) will be required to transfer knowledge across shale gas sites/formations but it is a clearly superior alternative to developing a new machine-learning model altogether when considering a di?erent site.

Srinivasan, Shriram↗
DOE OSTI2022

Automatic Qubit Characterization and Gate Optimization with QubiC

As the size and complexity of a quantum computer increases, quantum bit (qubit) characterization and gate optimization become complex and time-consuming tasks. Current calibration techniques require complicated and verbose measurements to tune up qubits and gates, which cannot easily expand to the large-scale quantum systems. We develop a concise and automatic calibration protocol to characterize qubits and optimize gates using QubiC, which is an open source FPGA (field-programmable gate array) based control and measurement system for superconducting quantum information processors. We propose multi-dimensional loss-based optimization of single-qubit gates and full XY-plane measurement method for the two-qubit CNOT gate calibration. We demonstrate the QubiC automatic calibration protocols are capable of delivering high-fidelity gates on the state-of-the-art transmon-type processor operating at the Advanced Quantum Testbed at Lawrence Berkeley National Laboratory. Finally, the single-qubit and two-qubit Clifford gate infidelities measured by randomized benchmarking are of 4.9(1.1) × 10 -4 and 1.4(3) × 10 -2 , respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Suppression of hybridization by Cd doping in CeCoIn 5

The interaction between superconductivity and magnetism in heavy fermion compounds has remained a challenge ever since the discovery of unconventional superconductivity in such systems. The heavy fermion Ce T In 5 ( T = Co,Rh,Ir) family offers a good platform to study the relationship between superconductivity and magnetism, whose ground state can be easily tuned by chemical doping, making the ambient-pressure experimental techniques like angle-resolved photoemission spectroscopy possible to address this old but engaging question. By Cd doping, the superconducting state of CeCoIn 5 can be smoothly tuned to an antiferromagnetic ground state, which can be reversed by applying pressure. In this study, we present an electronic structure study of CeCo ( In 0.85 Cd 0.15 ) 5 with an antiferromagnetic ground state and the results are compared with CeCoIn 5 . We found that the hybridization strength between the f electrons and conduction electrons in CeCoIn 5 has been suppressed by Cd doping, but still the Fermi surface includes a significant contribution from the Ce f electrons. Our results find that the electronic tuning effect by Cd doping arises from the change in the hybridization strength between the Ce f electrons and conduction electrons caused by the Cd dopant, and the subtle interplay between itinerancy and localization of the f electrons determines the ground state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A novel technique for minimizing energy functional using neural networks

An energy functional describes the equilibrium state of a system. In this work, we present a novel technique, Functional Optimization using Neural Networks (FONN), for minimizing the system’s energy. FONN utilizes neural networks to process information at discrete grid points, considering their interactions with neighboring grid points, to update the state of the system. The training process involves formulating a loss function based on the system’s energy, and with the help of multiple fine-tuning steps, the method employs a progressive energy reduction technique that decreases the energy in multiple steps. FONN’s effectiveness is demonstrated across various problems, including the minimization of the heat and Lyapunov energy. Furthermore, the paper explores the minimization of the elastic bending energy with an area constraint.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Leveraging prior mean models for faster Bayesian optimization of particle accelerators

Tuning particle accelerators is a challenging and time-consuming task that can be automated and carried out efficiently using suitable optimization algorithms, such as model-based Bayesian optimization techniques. One of the major advantages of Bayesian algorithms is the ability to incorporate prior information about beam physics and historical behavior into the model used to make control decisions. In this work, we examine incorporating prior accelerator physics information into Bayesian optimization algorithms by utilizing fast executing, neural network models trained on simulated or historical datasets as prior mean functions in Gaussian process models. We show that in ideal cases, this technique substantially increases convergence speed to optimal solutions in high-dimensional tuning parameter spaces. Additionally, we demonstrate that even in non-ideal cases, where prior models of beam dynamics do not exactly match experimental conditions, the use of this technique can still enhance convergence speed. Finally, we demonstrate how these methods can be used to improve optimization in practical applications, such as transferring information gained from beam dynamics simulations to online control of the LCLS injector, and transferring knowledge gained from experimental measurements across different operating modes, such as accelerating different ion species at the ATLAS heavy ion accelerator.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Ionic Liquid Gating of SrTiO 3 Lamellas Fabricated with a Focused Ion Beam

Here, in this work, we combine two previously incompatible techniques for defining electronic devices: shaping three-dimensional crystals by focused ion beam (FIB), and two-dimensional electrostatic accumulation of charge carriers. The principal challenge for this integration is nanometer-scale surface damage inherent to any FIB-based fabrication. We address this by using a sacrificial protective layer to preserve a selected pristine surface. The test case presented here is accumulation of 2D carriers by ionic liquid gating at the surface of a micron-scale SrTiO 3 lamella. Preservation of surface quality is reflected in superconductivity of the accumulated carriers. This technique opens new avenues for realizing electrostatic charge tuning in materials that are not available as large or exfoliatable single crystals, and for patterning the geometry of the accumulated carriers.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Giant elastocaloric effect at low temperatures in TmVO 4 and implications for cryogenic cooling

Adiabatic decompression of paraquadrupolar materials has significant potential as a cryogenic cooling technology. We focus on TmVO 4 , an archetypal material that undergoes a continuous phase transition to a ferroquadrupole-ordered state at 2.15 K. Above the phase transition, each Tm ion contributes an entropy of k B ln 2 due to the degeneracy of the crystal electric field groundstate. Owing to the large magnetoelastic coupling, which is a prerequisite for a material to undergo a phase transition via the cooperative Jahn–Teller effect, this level splitting, and hence the entropy, can be readily tuned by externally induced strain. Using a dynamic technique in which the strain is rapidly oscillated, we measure the adiabatic elastocaloric response of single-crystal TmVO 4 , and thus experimentally obtain the entropy landscape as a function of strain and temperature. The measurement confirms the suitability of this class of materials for cryogenic cooling applications and provides insight into the dynamic quadrupole strain susceptibility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Clear as mud redefined: Tunable transparent mineral scaffolds for visualizing microbial processes below ground

Microbes inhabiting complex porous microenvironments in sediments and aquifers catalyze reactions that are critical to global biogeochemical cycles and ecosystem health. However, the opacity and complexity of porous sediment and rock matrices have considerably hindered the study of microbial processes occurring within these habitats. Here, we generated microbially compatible, optically transparent mineral scaffolds to visualize and investigate microbial colonization and activities occurring in these environments, in laboratory settings and in situ. Using inexpensive synthetic cryolite mineral, we produced optically transparent scaffolds mimicking the complex 3D structure of sediments and rocks by adapting a suspension-based, freeze-casting technique commonly used in materials science. Fine-tuning of parameters, such as freezing rate and choice of solvent, provided full control of pore size and architecture. The combined effects of scaffold porosity and structure on the movement of microbe-sized particles, tested using velocity tracking of fluorescent beads, showed diverse yet reproducible behaviors. The scaffolds we produced are compatible with epifluorescence microscopy, allowing the fluorescence-based identification of colonizing microbes by DNA-based staining and fluorescence in situ hybridization (FISH) to depths of 100 µm. Additionally, Raman spectroscopy analysis indicates minimal background signal in regions used for measuring deuterium and 13 C enrichment in microorganisms, highlighting the potential to directly couple D 2 O or 13 C stable isotope probing and Raman-FISH for quantifying microbial activity at the single-cell level. To demonstrate the relevance of cryolite scaffolds for environmental field studies, we visualized their colonization by diverse microorganisms within rhizosphere sediments of a coastal seagrass plant using epifluorescence microscopy. The tool presented here enables highly resolved, spatially explicit, and multimodal investigations into the distribution, activities, and interactions of underground microbes typically obscured within opaque geological materials until now.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Field-induced spin polarization in the lightly Cr-substituted layered antiferromagnet NiP S 3

Tuning magnetic properties in layered magnets is an important route to realize novel phenomenon related to two-dimensional (2D) magnetism. Recently, tuning antiferromagnetic (AFM) properties through substitution and intercalation techniques has been widely studied in MPX 3 compounds. Interesting phenomena, such as diverse AFM structures and even the signatures of ferrimagnetism, have been reported. However, long-range ferromagnetic (FM) ordering has remained elusive. Here, in this work, we explored the magnetic properties of the Cr-substituted NiP S 3 . We found that Cr substitution is extremely efficient in controlling spin orientation in NiP S 3 . Our study reveals a field-induced spin polarization in lightly (9%) Cr-substituted NiP S 3 , which is likely attributed to the attenuation of AFM interactions and magnetic anisotropy due to Cr doping. Our work provides a possible strategy to achieve FM phase in AFM MPX 3 , which could be useful for investigating 2D magnetism as well as potential device applications.

2-dimensional systems↗
DOE OSTI2021

Develop On-Demand nanoplasmonic Device Concepts in a Semiconductor Compatible Hybrid System. Final Report

This report summarizes the research activities supported by the U.S. Department of Energy grant DE-SC-0010399. The goal of this project is to is to develop an on-demand nanoplasmonic platform that combines emerging oxide nanoelectronics with a low-loss semiconductor-friendly plasmonic materials. Toward this goal, several unique heterostructures formed between complex oxides and 2D layered materials have been developed. Based on these material systems, a set of atomic force microscope (AFM) based techniques have been developed that can allow long-living and reversible material phase transitions to be manipulated in nanoscale at room temperature. Using such technique and through interface coupling, we can effectively tune the plasmon propagations in unconventional plasmonic materials such as graphene and VO 2 . In addition, we also discovered a plethora of novel interface enabled electro-optic effects, including the spatial modulation of light using 2DEG, a giant programmable photothermoelectric effects at room temperature, a light induced superconducting transition, and a tunable giant third order optical nonlinearities. These major results are outlined in this report, along with lists of project participants and products.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Autonomous Tuning and Charge-State Detection of Gate-Defined Quantum Dots

Defining quantum dots in semiconductor-based heterostructures is an essential step in initializing solid-state qubits. With growing device complexity and increasing number of functional devices required for measurements, a manual approach to finding suitable gate voltages to confine electrons electrostatically is impractical. Here, we implement a two-stage device characterization and dot-tuning process, which first determines whether devices are functional and then attempts to tune the functional devices to the single or double quantum-dot regime. We show that automating well-established manual-tuning procedures and replacing the experimenter’s decisions by supervised machine learning is sufficient to tune double quantum dots in multiple devices without premeasured input or manual intervention. The quality of measurement results and charge states are assessed by four binary classifiers trained with experimental data, reflecting real device behavior. We compare and optimize eight models and different data preprocessing techniques for each of the classifiers to achieve reliable autonomous tuning, an essential step towards scalable quantum systems in quantum-dot-based qubit architectures.

Darulova, J↗
DOE OSTI2023

Selective hydrogenation via precise hydrogen bond interactions on catalytic scaffolds

Abstract The active site environment in enzymes has been known to affect catalyst performance through weak interactions with a substrate, but precise synthetic control of enzyme inspired heterogeneous catalysts remains challenging. Here, we synthesize hyper-crosslinked porous polymer (HCPs) with solely -OH or -CH 3 groups on the polymer scaffold to tune the environment of active sites. Reaction rate measurements, spectroscopic techniques, along with DFT calculations show that HCP-OH catalysts enhance the hydrogenation rate of H-acceptor substrates containing carbonyl groups whereas hydrophobic HCP- CH 3 ones promote non-H bond substrate activation. The functional groups go beyond enhancing substrate adsorption to partially activate the C = O bond and tune the catalytic sites. They also expose selectivity control in the hydrogenation of multifunctional substrates through preferential substrate functional group adsorption. The proposed synthetic strategy opens a new class of porous polymers for selective catalysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

In situ and operando force-based atomic force microscopy for probing local functionality in energy storage materials

Electrochemical energy storage is the key enabling component of electric vehicles and solar-/wind-based energy technologies. The enhancement of energy stored requires the detailed understanding of charge storage mechanisms and local electrochemical and electromechanical phenomena over a variety of length scales from atoms to full cells. Classical electrochemical techniques, such as voltammetry, represent the macroscopic electrochemical properties, and consequently do not allow to extract important information about local electrochemical reactions, ions adsorption, intercalations, and transport. Understanding, controlling, and tuning the local electrochemical functionalities in functional energy materials require in situ/operando techniques which limit the use of structural and functional characterization techniques that provide local information. Here, force-based atomic force microscopies (AFMs) have provided novel insights into locally probing electrochemical mechanisms on tens of nanometer and even molecular length scales and provide a viable pathway to probe electrochemical processes in situ/operando. In this review, we highlight the contributions in the development and application of force-based AFM methods to elucidate the local charge storage mechanism in a variety of energy-related materials. We will focus in particular on methods or AFM modalities in a liquid electrolyte environment.

25 ENERGY STORAGE↗
DOE OSTI2020

Cognition at the Point of Sensing

Over the last 15 years, compressive sensing techniques have been developed which have the potential to greatly reduce the amount of data collected by systems while preserving the amount of information obtained. A cost of this efficiency is that a computationally-intensive optimization routine must be used to put the sensed data into a form that a person can interpret. At the same time, machine learning techniques have experienced tremendous growth as well. Machines have demonstrated the ability learn how to effectively perform tasks such as detection and classification at speeds much faster than humanly possible. Our goal in this project was to study the feasibility of using compressive sensing systems "at the edge." That is, how can compressive sensing sensors be deployed such that information is created at the remote sensor rather than sending raw data to a central processing location? Studies were performed to analyze whether machine learning could be done on the compressively sensed data in its raw form. If a machine is performing the task, is it possible to do so without putting the data into a human interpretable form? We show that this is possible for some systems, in particular a compressive sensing snapshot imaging spectrometer. Machine learning tasks were demonstrated to be more effective and more robust to noise when the machine learning algorithm worked on data in its raw form. This system is shown to outperform a traditional spectrometer. Techniques for reducing the complexity of the reconstruction routine were also analyzed. Techniques for such as data regularization, deep neural networks, and matrix completion were studied and shown to have benefits over traditional reconstruction techniques. In this project we showed that compressive sensing sensors are indeed feasible at the edge. As always, sensors and algorithms must be carefully tuned to work in the constrained environment. In this project we developed tools and techniques to enable those analyses.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Shape tuning of large area silicon nanotip arrays through reactive ion etching

Nanostructures formed in silicon form an important class of structures that span a broad spectrum of application areas. Of these, columnar structures of silicon featuring tiplike apexes have their own niche applications. Here, the ability to afford shape tunability for these structures further enhances their application potential. In this paper, we present our findings on the large area fabrication of silicon nanotips defined through microsphere lithography and shape tuned through a combination of different reactive ion etching (RIE) techniques. The self-sharpening mechanism of the tips when using nonplanar etch masks (microspheres) under anisotropic etching conditions is elucidated. We further show that depending on the manner of etching (continuous versus discrete multistep etch), identical anisotropic etching recipes produce vastly different tip morphologies. Hourglass-shaped silicon tips were obtained when silicon was subjected to anisotropic followed by isotropic etching conditions. Sharp silicon tips with tip apex radii on the order of 2 nm have been successfully realized when the RIE shape tuned tips were subjected to a series of oxidative sharpening steps.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Graphitic Aza-Fused π-Conjugated Networks: Construction, Engineering, and Task-Specific Applications

2D π-conjugated networks linked by aza-fused units represent a pivotal category of graphitic materials with stacked nanosheet architectures. Extensive efforts have been directed at their fabrication and application since the discovery of covalent triazine frameworks (CTFs). Besides the triazine cores, tricycloquinazoline and hexaazatriphenylene linkages are further introduced to tailor the structures and properties. Diverse related materials have been developed rapidly, and a thorough outlook is necessitated to unveil the structure–property–application relationships across multiple subcategories, which is pivotal to guide the design and fabrication toward enhanced task-specific performance. Herein, the structure types and development of related materials including CTFs, covalent quinazoline networks, and hexaazatriphenylene networks, are introduced. Advanced synthetic strategies coupled with characterization techniques provide powerful tools to engineer the properties and tune the associated behaviors in corresponding applications. Case studies in the areas of gas adsorption, membrane-based separation, thermo-/electro-/photocatalysis, and energy storage are then addressed, focusing on the correlation between structure/property engineering and optimization of the corresponding performance, particularly the preferred features and strategies in each specific field. In the last section, the underlying challenges and opportunities in construction and application of this emerging and promising material category are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

3D LiMn 2 O 4 nThin Film Deposited by ALD: A Road toward High-Capacity Electrode for 3D Li-Ion Microbatteries

Miniaturized electronics suffer from a lack of energy autonomy. In that context, the fabrication of lithium-ion solid-state microbatteries with high performance is mandatory for powering the next generation of portable electronic devices. Here, the fabrication of a thin film positive electrode for 3D Li-ion microbatteries made by the atomic layer deposition (ALD) method and in situ lithiation step is demonstrated. The 3D electrodes based on spinel LiMn 2 O 4 films operate at high working potential (4.1 V vs Li/Li + ) and are capable of delivering a remarkable surface capacity (approximate to 180 mu Ah cm -2 ) at low C-rate while maintaining more than 40 mu Ah cm -2 at C/2 (time constant = 2 h). Both the thickness of the electrode material and the 3D gain of the template are carefully tuned to maximize the electrode performance. Further, advanced characterization techniques such as transmission electron and X-ray transmission microscopies are proposed as perfect tools to study the conformality of the deposited films and the interfaces between each layer: no interdiffusion or segregation are observed. This work represents a major issue towards the fabrication of 3D-lithiated electrode by ALD-without any prelithiation step by electrochemical technique-making it an attractive solution for the fabrication of 3D Li-ion solid-state microbatteries with semiconductor processing methods.

3D Li-ion micro-batteries↗
DOE OSTI2022

n-Type doping of a solution processed p-type semiconductor using isoelectronic surface dopants for homojunction fabrication

The p-n junction is one of the fundamental requirements for a practical semiconductor-based electronic device. Designing a heterojunction comprising of dissimilar p-type and n-type semiconductors calls for careful energy level considerations, both when selecting the semiconductor materials as well as the metal contacts. A homojunction based on a single semiconductor simplifies this task, as energy levels of the p-type and n-type materials are already fairly similar, allowing for easier selection of contacts. Traditionally, homojunctions rely on doping of a bulk semiconductor to achieve p- and n-type transport through controlled addition of aliovalent dopants via energy-intensive processes such as ion implantation or thermal annealing. Exact control of doping in nanocrystalline semiconductors is significantly more challenging, due to self-purification effects. However, owing to their large surface areas, surface moieties can be utilized to both dope the nanostructures as well as tune their energy levels. Here, we present a facile technique based on an isoelectronic surface dopant in order to achieve p- and n-type materials based on the same semiconductor. We show that thin p-type colloidal Bi 2 Te 3 nanowires can be switched to n-type through surface functionalization, thus increasing the availability of new nanocrystalline solution-processable p-n homojunctions.

42 ENGINEERING↗