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DOE OSTI2021

A Bi-Layer Dense/Porous Solid Electrolyte Interphase for Enhanced Lithium-Metal Stability

Due to its high theoretical capacity and low electrochemical potential, lithium metal is a highly investigated anode for next-generation high-energy batteries. However, the unstable chemical and topographical heterogeneous surface of lithium gives rise to safety and efficiency concerns that prevent it from being utilized in practical applications. Exposure to electrolyte leads to non-uniform, mixed organic-inorganic solid-electrolyte interphase (SEI) formation, starting a cascading to non-uniform flux distribution, consumption of active materials, and dendrite growth. The SEI is the key feature that will lead to harnessing the capabilities possible with lithium metal. In this work, the formation of a closed-host bi-layer solid electrolyte interphase (SEI) improves the stability of lithium anode. This is successfully realized by forming an interconnected porous LiF-rich artificial SEI in contact with Li metal, and a dense, stable in-situ formed upper layer SEI. The porous layer increases the number of Li/LiF interfaces, which reduces local volume fluctuations and improves Li+ diffusion along these interfaces. Additionally, the tortuous porous structure guides uniform Li+ flux distribution and mechanically suppresses dendrite propagation. The dense upper layer of the SEI accomplishes a closed-host design through reaction with LiNO3 additive and prevents continuous consumption of active materials seen without the additive included in the electrolyte. The duality of a dense top layer with porous bottom layer led to extended cycle life and improved rate performance, evidenced with symmetric cell testing, as well as full cell testing paired with sulfur and LiFePO4 (LFP) cathodes. This work is a good example of a rational design of the SEI, based on comprehensive consideration of various critical factors to improve Li-metal anode stability, and highlights a new pathway to improve cycling and rate performances of Li metal batteries.

25 ENERGY STORAGE↗

DOE OSTI2020

Toward fusion plasma scenario planning for NSTX-U using machine-learning-accelerated models

One of the most promising devices for realizing power production through nuclear fusion is the tokamak. To maximize performance, it is preferable that tokamak reactors achieve advanced operating scenarios characterized by good plasma confinement, improved magnetohydrodynamic (MHD) stability, and a largely non-inductively driven plasma current. Such scenarios could enable steady-state reactor operation with high \emph{fusion gain} --- the ratio of produced fusion power to the external power provided through the plasma boundary. Precise and robust control of the evolution of the plasma boundary shape as well as the spatial distribution of the plasma current, density, temperature, and rotation will be essential to achieving and maintaining such scenarios. The complexity of the evolution of tokamak plasmas, arising due to nonlinearities and coupling between various parameters, motivates the use of model-based control algorithms that can account for the system dynamics. In this work, a learning-based accelerated model trained on data from the National Spherical Torus Experiment Upgrade (NSTX-U) is employed to develop planning and control strategies for regulating the density and temperature profile evolution around desired trajectories. The proposed model combines empirical scaling laws developed across multiple devices with neural networks trained on empirical data from NSTX-U and a database of first-principles-based computationally intensive simulations. The reduced execution time of the accelerated model will enable practical application of optimization algorithms and reinforcement learning approaches for scenario planning and control development. An initial demonstration of applying optimization approaches to the learning-based model is presented, including a strategy for mitigating the effect of leaving the finite validity range of the accelerated model. The approach shows promise for actuator planning between experiments and in real-time.

machine learning↗

DOE OSTI2021

A Geometry-Driven Longitudal Topic Model

A simple and scalable framework for longitudinal analysis of Twitter data is developed that combines latent topic models with computational geometric methods. Dimensionality reduction tools from computational geometry are applied to learn the intrinsic manifold on which the latent, temporal topics reside. Then shortest path distances on the manifold are used to link together these topics. The proposed framework permits visualization of the low-dimensional embedding which provides clear interpretation of the complex, high-dimensional trajectories that may exist among latent topics. Practical application of the proposed framework is demonstrated through its ability to capture and effectively visualize natural progression of latent COVID-19 related topics learned from Twitter data. Interpretability of the trajectories is achieved by comparing to real-world events. In addition, the framework permits study of spatial variation in Twitter behavior for learned topics. The analysis demonstrates that the proposed framework is able to capture granular-level impact of COVID-19 on public discussions. We end by arguing that Twitter data, when analyzed within the proposed framework, can serve as a valuable supplementary data stream for COVID-related studies.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Development of a simplified calibrated building simulation model of a supermarket for proposed ECMs and control strategies impact evaluation

Calibrated building energy simulation is an important pathway to more energy-efficient buildings, but the information requirements of some approaches to this problem are significant. This is particularly true for supermarkets and other so-called “big-box” retail stores. Another characteristic of supermarkets is the significant interaction between Heating Ventilating and Air Conditioning (HVAC) and refrigeration systems in these buildings. These buildings could contain a wide variety of systems and a degree of load diversity that makes calibrated modeling a challenge. This paper describes a simplified approach that uses OpenStudio and EnergyPlus to combine known building parameters with “typical” parameters, resulting in a simplified building that is amenable to calibration. This approach was applied to a big-box store located in Nashville, Tennessee, and a calibrated model was obtained that was used to study potential energy conservation measures. Further, the paper also explores the capabilities of whole-building energy modeling tools, such as EnergyPlus, for modeling the HVAC controls and sequences and their impact evaluation. Although some measures are precluded by the model simplicity, several measures were found to improve the efficiency of the model and demonstrate that the simplified modeling approach is effective. Practical Application: This paper introduces a hybrid approach of building energy model calibration using limited information available from the actual building in combination with characteristics of a “typical” building of the same type. This hybrid approach would also be applicable for other building types than discussed in this paper to calibrate the building energy model using limited information from the actual building.

42 ENGINEERING↗

DOE OSTI2025

Investigating Resiliency of Transportation Network under Targeted and Potential Climate Change Disruptions

Ensuring robustness and resilience in intermodal transportation systems is essential for the continuity and reliability of global logistics. These systems are vulnerable to various disruptions, including natural disasters and technical failures. Despite significant research on freight transportation resilience, investigating the robustness of the system after targeted and climate-change-driven disruption remains a crucial challenge. Drawing on network science methodologies, this study models the interdependencies within the rail and water transport networks and simulates different disruption scenarios to evaluate system responses. Here, we use the data from the U.S. Department of Energy Volpe Center for network topology and tonnage projections. The proposed framework quantifies deliberate, stochastic, and climate-driven infrastructure failure, using higher resolution downscaled multiple Earth System Models’ simulations from Coupled Model Intercomparison Project Phase version 6. We show that the disruptions of a few nodes could have a larger impact on the total tonnage of freight transport than on network topology. For example, the removal of targeted 20 nodes can bring the total tonnage carrying capacity to 30% with about 75% of the rail freight network intact. This research advances the theoretical understanding of transportation resilience and provides practical applications for infrastructure managers and policymakers. By implementing these strategies, stakeholders and policymakers can better prepare for and respond to unexpected disruptions, ensuring sustained operational efficiency in transportation networks.

Climate Change Disruptions↗

DOE OSTI2022

Data for Metabolic Engineering of Oleaginous Yeast Rhodotorula toruloides for Overproduction of Triacetic Acid Lactone

The plant-sourced polyketide triacetic acid lactone (TAL) has been recognized as a promising platform chemical for the biorefinery industry. However, its practical application was rather limited due to low natural abundance and inefficient cell factories for biosynthesis. Here, we report the metabolic engineering of oleaginous yeast Rhodotorula toruloides for TAL overproduction. We first introduced a 2-pyrone synthase gene from Gerbera hybrida (GhPS) into R. toruloides and investigated the effects of different carbon sources on TAL production. We then systematically employed a variety of metabolic engineering strategies to increase the flux of acetyl-CoA by enhancing its biosynthetic pathways and disrupting its competing pathways. We found that overexpression of ATP-citrate lyase (ACL1) improved TAL production by 45% compared to the GhPS overexpressing strain, and additional overexpression of acetyl-CoA carboxylase (ACC1) further increased TAL production by 29%. Finally, we characterized the resulting strain I12-ACL1-ACC1 using fed-batch bioreactor fermentation in glucose or oilcane juice medium with acetate supplementation and achieved a titer of 28 or 23 g/L TAL, respectively. This study demonstrates that R. toruloides is a promising host for the production of TAL and other acetyl-CoA-derived polyketides from low-cost carbon sources.

Conversion↗

DOE OSTI2024

Data for "Design of Diverse, Functional Mitochondrial Targeting Sequences Across Eukaryotic Organisms Using Variational Autoencoder"

Mitochondria play a key role in energy production and metabolism, making them a promising target for metabolic engineering and disease treatment. However, despite the known influence of passenger proteins on localization efficiency, only a few protein-localization tags have been characterized for mitochondrial targeting. To address this limitation, we leverage a Variational Autoencoder to design novel mitochondrial targeting sequences. In silico analysis reveals that a high fraction of the generated peptides (90.14%) are functional and possess features important for mitochondrial targeting. We characterize artificial peptides in four eukaryotic organisms and, as a proof-of-concept, demonstrate their utility in increasing 3-hydroxypropionic acid titers through pathway compartmentalization and improving 5-aminolevulinate synthase delivery by 1.62-fold and 4.76-fold, respectively. Moreover, we employ latent space interpolation to shed light on the evolutionary origins of dual-targeting sequences. Overall, our work demonstrates the potential of generative artificial intelligence for both fundamental research and practical applications in mitochondrial biology.

AI/ML↗

DOE OSTI2021

Broadband titanium nitride disordered metasurface absorbers

We experimentally demonstrate titanium nitride (TiN) broadband metasurface perfect absorbers by conformally coating plasmonic TiN films onto disordered anodic aluminum oxide (AAO) nanotemplates. The disordered metasurface absorbers exhibit polarization-insensitive and weak angle-dependent perfect absorption over the entire visible and near-infrared spectral regions (300 < λ < 2500 nm). We show from experimental results and numerical simulations that the light scattering induced by the strong disorder of the AAO nanopores and the strong absorption of the TiN deposited on their sidewall are of critical importance for achieving broadband perfect absorption. The TiN disordered metasurface perfect absorbers are superior to many other types of broadband perfect absorbers previously reported and are more suitable for practical applications especially in harsh environments. The device concept for broadband perfect absorption based on plasmonic metal-nitride film coated disordered dielectric media could potentially be extended to significantly enhance the efficiency of solar energy harvesting and the performance of hot-carrier based optoelectronics.

Chang, Chun-Chieh (ORCID:0000000337282454)↗

DOE OSTI2022

Megawatt pulses from an all-fiber and self-starting femtosecond oscillator

Mamyshev oscillators produce high-performance pulses, but technical and practical issues render them unsuitable for widespread use. Here we present a Mamyshev oscillator with several key design features that enable self-starting operation and unprecedented performance and simplicity from an all-fiber laser. The laser generates 110 nJ pulses that compress to 40 fs and 80 nJ with a grating pair. The pulse energy and duration are both the best achieved by a femtosecond all-fiber laser to date, to our knowledge, and the resulting peak power of 1.5 MW is 20 times higher than that of prior all-fiber, self-starting lasers. Finally, the simplicity of the design, ease of use, and pulse performance make this laser an attractive tool for practical applications.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Fast quantum ghost imaging with a single-photon-sensitive time-stamping camera

Quantum ghost imaging (QGI) leverages correlations between entangled photon pairs to reconstruct an image using light that has never physically interacted with an object. Despite extensive research interest, this technique has long been hindered by slow acquisition speeds, due to the use of raster-scanned detectors or the slow response of intensified cameras. Here, we utilize a single-photon-sensitive time-stamping camera to perform QGI at ultra-low-light levels with rapid data acquisition and processing times, achieving high-resolution and high-contrast images in under 1 min. Our work addresses the trade-off between image quality, optical power, data acquisition time, and data processing time in QGI, paving the way for practical applications in biomedical and quantum-secured imaging.

Mavian, Alex (ORCID:0000000279448830)↗

DOE OSTI2022

Controlled precision QUBO-based algorithm to compute eigenvectors of symmetric matrices

We describe an algorithm to compute the extremal eigenvalues and corresponding eigenvectors of a symmetric matrix which is based on solving a sequence of Quadratic Binary Optimization problems. This algorithm is robust across many different classes of symmetric matrices; It can compute the eigenvector/eigenvalue pair to essentially any arbitrary precision, and with minor modifications, can also solve the generalized eigenvalue problem. Performance is analyzed on small random matrices and selected larger matrices from practical applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Dynamically tunable second-harmonic generation using hybrid nanostructures incorporating phase-change chalcogenides

Nonlinear metasurfaces with high conversion efficiencies have been vastly investigated. However, strong dynamic tunability of such devices is limited in conventional passive plasmonic and dielectric material platforms. Germanium antimony telluride (GST) is a promising phase-change chalcogenide for the reconfiguration of metamaterials due to strong nonvolatile changes of the real and imaginary parts of the refraction index through amorphous-crystalline phase change. The orderly structured GST has an even higher potential in tunable second-harmonic generation (SHG) with a non-centrosymmetric crystal structure at the crystalline phase, while the amorphous phase of GST does not exhibit bulk second-order nonlinearity. Here, we experimentally demonstrate SHG switches by actively controlling the crystalline phase of GST for a GST-based hybrid metasurface featuring a gap-surface plasmon resonance, and a quarter-wave asymmetric Fabry–Perot (F–P) cavity incorporating GST. We obtain SHG switches with modulation depths as high as ~ 20 dB for the wavelengths at the on-state resonance. We also demonstrate the feasibility of multi-level SHG modulation by leveraging three controlled GST phases, i.e., amorphous, semi-crystalline, and crystalline, for the gap-surface plasmon hybrid device, which features stronger light–matter interaction and has higher resonant SHG efficiencies than the asymmetric F–P cavity device at respective GST phases. This research reveals that GST-based dynamic SHG switches can be potentially employed in practical applications, such as microscopy, optical communication, and photonic computing in the nonlinear regime.

42 ENGINEERING↗

DOE OSTI2022

Thermal dynamics of P2-Na 0.67 Ni 0.33 Mn 0.67 O 2 cathode materials for sodium ion batteries studied by in situ analysis

Cobalt-free layered Na 0.67 Ni 0.33 Mn 0.67 O 2 is an attractive cathode material for sodium ion batteries. The thermal stability of cathode materials is crucial to their practical applications. In the current work, we investigate structural and morphological evolution in P2-type Na 0.67 Ni 0.33 Mn 0.67 O 2 cathode materials during annealing via in situ synchrotron X-ray diffraction and transmission electron microscopy. Insights are obtained from the two complementary in situ characterizations (at different length scales) in term of the thermal stability of P2-Na 0.67 Ni 0.33 Mn 0.67 O 2 cathode materials. Here, the results indicate that the hexagonal P2 phase remains unchanged during the heat treatment process, and thermally driven expansion/contraction of lattice parameters exhibit an anisotropic character in the a and c directions. In addition, interfaces/grain boundaries play an important role in the structural stability, which leads to the distinct morphological evolution between the polycrystalline and single-crystal particles.

25 ENERGY STORAGE↗

DOE OSTI2024

Molten flux growth of single crystals of quasi-1D hexagonal chalcogenide BaTiS3

Abstract BaTiS 3 , a quasi-1D complex chalcogenide, has gathered considerable scientific and technological interest due to its giant optical anisotropy and electronic phase transitions. However, the synthesis of high-quality BaTiS 3 crystals, particularly those featuring crystal sizes of millimeters or larger, remains a challenge. Here, we investigate the growth of BaTiS 3 crystals utilizing a molten salt flux of either potassium iodide, or a mixture of barium chloride and barium iodide. The crystals obtained through this method exhibit a substantial increase in volume compared to those synthesized via the chemical vapor transport method, while preserving their intrinsic optical and electronic properties. Our flux growth method provides a promising route toward the production of high-quality, large-scale single crystals of BaTiS 3 , which will greatly facilitate advanced characterizations of BaTiS 3 and its practical applications that require large crystal dimensions. Additionally, our approach offers an alternative synthetic route for other emerging complex chalcogenides. Graphical Abstract

Materials Science↗

DOE OSTI2023

Navigating the complexities of solvent and binder selection for solution processing of sulfide solid-state electrolytes

We introduce a paradigm of solvent and binder selection for solution-processing Li 6 PS 5 Cl solid-state electrolyte particles based on Hansen solubility parameters. Treatment of the Li 6 PS 5 Cl in selected solvents results in particle morphological change, but crystallographic structure remains intact. Although solution processing reduced the Li 6 PS 5 Cl ionic conductivity, it promotes interfacial stability by alleviating reduction of the solid electrolyte in contact with Li metal. In conclusion, these findings have the potential to enhance the stability, structural integrity, and performance of sulfide solid-state electrolytes in practical applications.

25 ENERGY STORAGE↗

DOE OSTI2024

Thermomechanical properties of stereolithographic 3D-printed zinc oxide nanocomposites

Stereolithography (SLA) is a highly versatile additive manufacturing technique that utilizes various ink formulations to fabricate 3D-printed nanocomposite structures with desired properties. Zinc oxide (ZnO) is a promising candidate due to its excellent mechanical and thermal stability, and compatibility with various polymeric matrices. Here, in this work, varying ink formulations containing ZnO nanoparticles, along with employing appropriate post-printing curing parameters to fabricate SLA 3D-printed acrylate-based nanocomposites with improved mechanical and thermal properties, were reported. This study can significantly contribute to expanding its potential use in practical applications such as biomedical and structural applications.

36 MATERIALS SCIENCE↗

DOE OSTI2024

High pressure rinse simulations for PIP-II SRF cavities

The implementation of High Pressure Rinse (HPR) not only ensures thorough cleaning of the inner high purity niobium surface of Superconducting Radio Frequency (SRF) cavities but also unlocks their full potential for achieving peak performance. By effectively removing contaminants and impurities, HPR sets the stage for enhanced superconducting properties, improved energy efficiency, and superior operational stability. A simulation tool has been developed, facilitating the accurate prediction of both the quality and effectiveness of the rinsing process before its execution in the cleanroom. This tool, the focus of this paper, stands as a pivotal advancement in optimizing Superconducting Radio Frequency (SRF) cavity preparation. Furthermore, our paper will also present correlations with cavity cold testing results, demonstrating the practical applicability and reliability of the simulation predictions in real-world scenarios.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

Approaching scalable VQE of interacting bosons with NISQ devices [Slides]

Scaling up variational quantum eigensolver (VQE) algorithms to practical applications utilizing quantum advantage with noisy intermediate-scale quantum (NISQ) devices is challenging. The expansive cost-function evaluation and demanding optimization quickly exhaust the precious quantum resource available on NISQ devices. In this work, we discuss the appropriate VQE strategy suitable for multi-site interacting boson systems, for example, the Holstein model and the Rabi lattice model. We investigate the cost-function setup and the optimization tactics to utilize the limited quantum resource efficiently. Our strategy illustrates that the scalable VQE algorithms of interacting bosons have a promising future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗