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At least 631 records · Page 35

Compact cryomodule for mobile stand-alone superconducting industrial accelerators

Superconducting RF (SRF) accelerators have the potential to be more profitable in comparison with normally conducting accelerators, as long they can be made compact, achieve operational simplicity, autonomy, trans- portability, satisfactory energy efficiency, as well as have reasonable costs. The development of SRF technologies such as Nb 3 Sn coating, conductively-cooled resonators, and high-capacity liquid-helium-free cryocoolers made SRF accelerators mobile and energetically and economically efficient at a beam power of tens of kW. One of the key elements of such an accelerator is the cryomodule, which must have minimal thermal losses to enable operation from low power cryoheads and enable conductive cooling of SRF resonator. In this research we present the design and test results of a compact cryomodule for an industrial stand-alone SRF linear accelerator proto- type, based on 650 MHz elliptical resonators, being developed at Fermi National Accelerator Laboratory.

43 PARTICLE ACCELERATORS↗

Novel thermal energy storage component: Development, performance, and phase transition diagnosis

Thermal energy storage (TES) using phase change materials (PCMs) is a promising technology for capturing and storing excess thermal energy for later use. However, challenges such as poor heat transfer efficiency and a lack of modular, scalable designs have limited widespread adoption of TES in real-world applications. This study developed and evaluated modular brick-type and blade-type TES prototypes featuring an aluminum housing, an embedded serpentine coil for active or passive thermal exchange, and a cost-effective metal mesh to enhance PCM thermal conductivity. The blade-type TES achieved notable geometric efficiency, with a thickness-to-length ratio of 0.03 and a thickness-to-width ratio of 0.08, enabling highly compact and modular thermal storage suitable for space-constrained applications. The paper presents a detailed evaluation of the TES prototypes’ performance. The comparative analysis indicated that the TES prototypes provide a highly cost-effective, thermally optimized alternative for compact energy storage and load shifting. A novel diagnostic technique was also introduced: using a portable endoscope to capture real-time visualizations of PCM phase transitions inside the TES. This method provides critical insights into internal heat transfer mechanisms, identifies potential issues, and offers valuable support for optimizing the TES design and developing the control algorithm. Overall, the modular brick-type and blade-type TES designs demonstrated in this work provide a scalable, efficient, and economically viable solution for advancing TES across residential, commercial, and industrial sectors. The designs’ compact structure, enhanced thermal performance, and integrated diagnostic capabilities make them strong candidates for future deployment in energy-efficient systems.

Gao, Zhiming [ORNL] (ORCID:0000000271397995)↗

Interfaces in all solid state Li-metal batteries: A review on instabilities, stabilization strategies, and scalability

With technological advancements in electrochemical energy storage systems increasing at a spectacular rate, batteries equipped with a lithium anode hold the key towards unlocking high energy densities. While lithium-ion batteries with layered anodes (e.g. graphite) and liquid organic electrolytes have been ubiquitous in portable electronics, electric vehicles, and grid applications, all solid-state batteries that use the combination of a lithium anode and a solid-state electrolyte (SSE) will further advance the present technology. The underlying challenge that limits the successful development of all solid-state batteries (ASSBs) is dictated largely by the highly reactive interfaces at the anode/SSE and the cathode/SSE interface. In this comprehensive review, we present an overview of the following: (i) characterization of the electrode/SSE interface via multimodal characterization, which include X-ray-, electron-, neutron-, optical-, and computation-based methods: (ii) parasitic reactions that occur from chemical, mechanical or electrochemical instabilities and interfacial engineering strategies for improving the stability of these interfaces classified by the class of inorganic SSEs (sulfide-, NASICON-, and garnet-type SSEs); (iii) laboratory-to-industry scale processing perspectives of SSEs; (iv) scalability and manufacturing aspects of current interfacial strategies; and (v) the prospects of all ASSBs within the context of extreme fast charging capability. Here, this review seeks to highlight key efforts in the field of ASSBs, by focusing particularly on stabilizing the electrode/SSE interfaces, which will help to bridge fundamental studies to technological relevance.

25 ENERGY STORAGE↗

Achieving low-temperature hydrothermal relithiation by redox mediation for direct recycling of spent lithium-ion battery cathodes

Lithium-ion battery (LIB) recycling is an urgent need to address the massive generation of spent LIBs from portable devices and electrical vehicles. However, the large-scale recycling is hampered by economic and safety issues associated with today's recycling processes. In this study, we demonstrate a safe and energy efficient direct regeneration process based on low-temperature hydrothermal relithiation (LTHR) at low pressure for spent LiNi x Co y Mn z O 2 (0 < x,y,z <1, x + y + z = 1, or NCM) cathode materials. A low concentration of low-cost redox mediator is employed to improve the relithiation kinetics of spent NCM materials, enabling full relithiation temperature to be reduced from 220 °C to 100 °C or below. Correspondingly, the pressure incurred in the relithiation process can be reduced from ~25 bar to 1 bar, offering significantly improved operation safety. Specifically, three NCM materials, including chemically delithiated NCM111, cycled (degraded) NCM111, and cycled NCM622, were successfully regenerated with complete recovery of composition, crystal structure, and electrochemical performance, achieving the same effectiveness as that achieved at high temperature process. Meanwhile, the total energy consumption of spent cell recycling and the greenhouse gas emission is also reduced. This work provides a facile and scalable way to more sustainable LIB recycling with high economic return, high operation safety and low cost.

25 ENERGY STORAGE↗

Progress in direct recycling of spent lithium nickel manganese cobalt oxide (NMC) cathodes

With the widespread use of lithium-ion batteries (LIBs) in portable electronics and electric vehicles (EVs), the end-of-life (EOL) LIBs are projected to reach 1336 GWh by 2040 under the sustainable development scenario. Proper recycling is urgently needed to minimize the release of hazardous waste and reduce mining activities by reintroducing critical minerals into the supply chain. Lithium nickel manganese cobalt oxide (LiNi x Mn y Co z O 2 , NMCs) cathodes have become dominant in the LIB market, especially with the increasing production of EVs, which are also the most valuable components in EOL LIBs. Unlike pyrometallurgical and/or hydrometallurgical methods, which convert spent NMCs into metals or metal compounds, direct recycling technologies aim to maximize the value of spent cathodes by restoring their degraded structure and composition. Furthermore, this review summarizes direct recycling methods for NMC cathodes published in the last decade and provides insights into the challenges and future development of direct recycling techniques.

Cathode↗

Development of a River Dynamical Core for E3SM to simulate compound flooding on Exascale-class heterogeneous supercomputers

Flooding events pose significant risk to human life, property, and infrastructure. Physically-consistent quantification of altered flood risks in global models requires hyper-resolution (~1 km) or fine flood simulations using two-dimensional (2D) physics schemes, both of which are unavailable in the current generation Earth System Models. Here, in this work, we have developed the River Dynamical Core (RDycore), which is an open-source, 2D shallow water equation (SWE) library for the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM). RDycore uses PETSc and libCEED libraries that allows it to run efficiently on CPUs and GPUs, as well as select a time-integration algorithm at runtime without requiring any code modifications. RDycore achieves spatial error convergence rates for problems with analytical and manufactured solutions similar to those reported previously in the literature, or consistent with the implemented first-order spatial discretization scheme. RDycore's accuracy in predicting flooding for a well-studied dam break problem is comparable to existing SWE models. For a problem with 471 million grid cells, RDycore achieves a speedup of 6.6x and 7.6x on GPUs compared to CPUs when using 320 compute nodes on DOE's Perlmutter and Frontier supercomputers, respectively. The one-way coupling of the RDycore library within E3SM is demonstrated by performing multiple 5-day flooding simulations during Hurricane Harvey driven by five precipitation datasets. The E3SM--RDycore simulations at 30 m spatial resolution accurately simulate maximum water height during the hurricane when benchmarked against a previously published study and achieve a speedup of 15x (Perlmutter) and 21x (Frontier) on GPUs relative to CPUs. The work presented here is the foundational step in providing hardware and algorithmic portability framework for simulating kilometer-scale river dynamics within E3SM.

Flood Simulation↗

A Full-Induction Magnetohydrodynamics Solver for Liquid Metal Fusion Blankets in Vertex-CFD

Multiphysics modeling of liquid metal fusion blankets, which produce tritium and convert energy of neutrons created via fusion reactions into heat, is crucial for predicting performance, ensuring structural integrity, and optimizing energy production. While traditional blanket modeling of liquid metal flows during normal steady operating conditions commonly employs the inductionless approximation of the magnetohydrodynamics (MHD) equations, transient scenarios, when the plasma-confining magnetic field varies on millisecond time scales, require a full-induction MHD approach that dynamically evolves the magnetic field via the time-dependent induction equation. This paper presents the formulation, implementation, and initial verification of a full-induction MHD solver integrated within the open-source Vertex-CFD framework, which aims to achieve tight multiphysics coupling, a flexible software design enabling easy extension and addition of physics models, and performance portability across computing platforms. The solver utilizes finite element spatial discretization, implicit Runge–Kutta time integration, and an inexact Newton method to solve the resulting discrete nonlinear system, leveraging Trilinos packages for efficient computation. Verification against selected benchmark problems demonstrates accuracy and robustness of the solver. Furthermore, when the solver is applied to an idealized blanket model in 2.5D and full 3D, results obtained with Vertex-CFD are in good agreement with recently published quasi-2D simulations. These findings establish a computational foundation for future simulations of transient MHD phenomena in liquid metal blankets with Vertex-CFD, and open avenues for future extensions and performance optimizations.

Endeve, Eirik [ORNL] (ORCID:0000000312519507)↗

Reducing ion diffusion at atmospheric pressure through intermingled positive and negative ions

Increasing ion molecule reaction times for ambient ionization techniques can increase sensitivity of detection. Longer reaction times result in an increase in analyte signal relative to the reactant ion signal, however with a subsequent decrease in the total ion intensity. This loss in the total number of ions reaching the detector limits the extent to which increased reaction time can improve detection in practical applications. In this study ion loss was measured using either electric fields or gas flow to control ion transit time. Ion transit times ranged from 40 ms to 8s, which resulted in ion densities ranging from 5 x 10 6 to 2 x 10 4 ions/cm 3 , respectively. These results provide insights into practical reaction time limitations or experimental boundaries when exploring sensitivity enhancements in ambient ionization. When exploring longer reaction times with an atmospheric flow tube coupled to a mass spectrometer (AFT-MS), an additional corona discharge ionization source of the same polarity was added in an attempt to increase total ion signal, but no improvement in signal was observed. This observation suggested that there was a maximum ion density being reached by the corona discharge that could not be increased by adding more of the same polarity ions. A hypothesis was that intermingling both polarities of ions would reduce ion loss and increase the measured ion signal. When two corona discharge sources—one each of positive and negative polarity—were used simultaneously in an AFT-MS, the total ion signal of either polarity measured by the MS was approximately double the current from a single corona discharge source. An increase in the negative ion signal was also observed when ~10 parts-per-trillion vapor levels of an explosive (RDX) were introduced. In this case both the nitrate reactant ions and the RDX signal more than doubled with the addition of a corona discharge source producing positive ions. When intermingling positive and negative ions, an increase in ion current was also observed when the AFT was coupled directly to a Faraday detector or to an ion mobility spectrometer. This was the first demonstration of interfacing the AFT to an IMS. The observations and developments from this work will help in creating more portable instruments with improved sensitivity for detection of chemicals.

47 OTHER INSTRUMENTATION↗

High stability of flexible perovskite transparent conductive oxide film via van der Waals heteroepitaxy

Transparent conducting oxides (TCOs), such as indium-tin oxide (ITO) and indium gallium zinc oxide (IGZO), are essential components in the design of flexible optoelectronic devices. However, it is still a challenge to prepare low-cost flexible transparent conductive film for achieving the flexible functionality together with high optical transparency and electrical conductivity. Herein, fluorphlogopite (mica) is selected as the bendable and transparent substrate for the fabrication of low-cost perovskite CaVO 3 TCO epitaxial film. Benefitting from thin mica substrate with high Young’s modulus of 200 GPa, flexible CaVO 3 TCO epitaxial film exhibits high mechanical stability in terms of electrical conductivity and optical transparency after bending up to 10 5 cycles. The change of resistance can reflect the bending curvature and strain state. Finally, our results provide a new pathway to design superior mechanical flexibility and stability CaVO 3 TCO films for application in flexible, light-weight, and portable smart optoelectronic devices.

36 MATERIALS SCIENCE↗

The role of coverage effects on the structure–sensitivity of formic acid electrooxidation on Pd surfaces

Direct formic acid (FA) fuel cells (DFAFCs) with Pd anode catalysts are promising for small portable applications. During the electrooxidation of formic acid (FAO), CO accumulates on the Pd electrocatalyst, thereby decreasing its performance. In this work, we use density functional theory (DFT; RPBE) to elucidate the significance of coverage effects on the structure–sensitivity of FAO over four low–index Pd surfaces: Pd(1 1 1), Pd(1 0 0), Pd(1 1 0), and Pd(2 1 1). We construct coverage–dependent Gibbs free energy diagrams and in agreement with experiment, predict that Pd(1 0 0) and Pd(2 1 1) are the most active surfaces. Additionally, we find that the presence of CO spectator species can alter the preferred electrooxidation pathway under different applied potentials. Furthermore, such pathway transitions appear to be critical for rationalizing experimental trends regarding electrocatalytic activity and are only captured when coverage effects are accounted for. Insights derived from this work may facilitate the design of improved FAO electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerating high-order continuum kinetic plasma simulations using multiple GPUs

Kinetic plasma simulations solve the Vlasov-Poisson or Vlasov-Maxwell equations to evolve scalar-variable distribution functions in position-velocity phase space and vector-variable electromagnetic fields in configuration space. The immense computational cost of evolving high-dimensional variables, and their large number of degrees of freedom, often limits the utility of continuum kinetic simulations and presents a challenge when it comes to accurately simulating real-world physical phenomena. To address this challenge, we present techniques that accelerate and minimize the computational work required for a scalable Vlasov-Poisson solver. We show theoretical hardware compute and communication bounds for solving a fourth-order finite-volume Vlasov-Poisson system. These bounds are then used to inform and evaluate the design of performance portable algorithms for a multiple graphics processing unit (GPU) accelerated version of the Vlasov-Poisson solver VCK-CPU [1]. We demonstrate that the multi-GPU Vlasov solver implementation, VCK-GPU, simultaneously minimizes required inter-process data transfer while also being bounded by the machine network performance limits. This results in an overall strong scaling speedup per timestep of up to 40x in three-dimensional phase space (one position, two velocity coordinates) and 54x in four dimensional phase space (two position, two velocity coordinates) and a 341x increase in simulation throughput of the GPU accelerated code over the existing CPU code. The GPU code is also able to weak scale up to 256 compute nodes and 1024 GPUs. In conclusion, we demonstrate that the improved compute performance enables exploring configurations which were previously computationally infeasible, including resolving fine-scale distribution function filamentation and multi-species dynamics with realistic electron-proton mass ratios.

Continuum kinetics↗

Spontaneous sodium ion storage behaviors of reduced graphene oxide anodes exceeding 100% Coulombic efficiency by modulated ion solvation

Rechargeable batteries are essential energy storage devices that power portable devices and electrical vehicles throughout the world. In general, it is thought that the electrochemical performance of rechargeable batteries is mostly determined by the electrodes within them and that the electrolyte plays a relatively passive role. However, ion transport and storage can be greatly influenced by the electrolyte solution structure, specifically, ion solvation within the bulk and ion desolvation across the electrode/electrolyte interfaces. Herein, we studied the role of the electrolyte as an active component of electrochemical energy storage devices. We found that with an appropriate electrolyte formulation, ion storage in disordered carbonaceous anode materials can occur spontaneously without externally supplied electrical energy. Reduced graphene oxide (RGO) in an ether-based electrolyte demonstrates ‘spontaneous' ion storage behaviors of adsorbing and inserting the solvated ions utilizing facilitated permeability and wettability of RGO, which results in Coulombic efficiency of ~145% due to additional charging capacity of ~180 mAh g -1 during electrochemical processes. The unexpected spontaneous ion storage behavior was extensively investigated using a combination of electrochemical analyses and diagnostics, advanced characterizations, and computational simulation. In conclusion, we believe the spontaneous ion storage behavior offers a new way to further improve the energy efficiency of practical rechargeable batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystallization-induced emission enhancement of alkyl chain-dependent pyrene-based luminogens: Visual detection of nitro-explosives

In view of the widespread applications and urgent need for efficient blue emitting materials, the synthesis of such materials has seen renewed interest. In the present work, three alkyl chain-dependent blue emitting pyrene-based luminogens were synthesized and characterized. Here, the experimental results show that these luminogens exhibited high photoluminescence efficiency both in solution (>86%) and in the solid state (>35%). Interestingly, 1,3,6,8-tetrakis (pentylphenyl)pyrene (TPPy), as a photoelectric functional material, was endowed with higher quantum yield (72%) and competitiveness due to a remarkable crystallization-induced emission enhancement (CIEE) property. More importantly, TPPy exhibits high sensitivity and selectivity for ortho-nitroaniline (o-NA) with low limit of detection (9.99 × 10 -8 M), which is mainly due to the distinctive odd-even effects of the terminal alkyl chain. The results demonstrate that this type of luminogen can potentially be utilized for practical applications in the field of contaminant or explosive detection as a sensitive and portable fluorimeter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

47 OTHER INSTRUMENTATION↗

On the effects of quadrupolar relaxation in Earth’s field NMR spectra

There is growing interest in using low-field magnetic resonance experiments for routine chemical characterization. Earth’s field NMR is one such technique that can garner structural information and enable sample differentiation with low cost and highly portable designs. The resulting NMR spectra are primarily influenced by $J$-couplings, resulting in so-called $J$-coupled spectra (JCS). Many small molecules include atoms with NMR-active nuclei that are quadrupolar either at natural abundance or are often isotopically enriched (e.g., 2 H, 6 Li, 11 B, 14 N, 17 O, etc.) where the effects of quadrupolar J-couplings and relaxation on JCS of strongly- and weakly-coupled spin systems have not been explored to date. Herein, using a set of seven fluoropyridine samples with unique substitution and $J$-couplings, we demonstrate that the 14 N relaxation rates can induce drastic line-broadening in the JCS. This includes a previously unexplored unique line broadening mechanism enabled by strongly coupled spins at low-field. In conclusion, numerical simulations are used to model and refine the magnitudes and signs of $J$-couplings, as well as indirectly determine the 14 N relaxation rates in a single 1D experiment that has a higher fidelity than observed in high-field NMR experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Translational research in the MPICH project

The MPICH project is an example of translational research in computer science before that term was well known or even coined. The project began in 1992 as an effort to develop a portable, high-performance implementation of the emerging Message-Passing Interface (MPI) Standard. It has enabled the widespread adoption of MPI as a way to write scalable parallel applications on systems of all sizes including upcoming exascale supercomputers. In this paper, we describe how the translational research process was used in MPICH, how that led to its success, the challenges encountered and lessons learned, and how the process could be applied to other similar projects.

97 MATHEMATICS AND COMPUTING↗

A scalable matrix-free spectral element approach for unsteady PDE constrained optimization using PETSc/TAO

In this work, we provide a new approach for the efficient matrix-free application of the transpose of the Jacobian for the spectral element method for the adjoint-based solution of partial differential equation (PDE) constrained optimization. This results in optimizations of nonlinear PDEs using explicit integrators where the integration of the adjoint problem is not more expensive than the forward simulation. Solving PDE constrained optimization problems entails combining expertise from multiple areas, including simulation, computation of derivatives, and optimization. The Portable, Extensible Toolkit for Scientific computation (PETSc) together with its companion package, the Toolkit for Advanced Optimization (TAO), is an integrated numerical software library that contains an algorithmic/software stack for solving linear systems, nonlinear systems, ordinary differential equations, differential algebraic equations, and large-scale optimization problems and, as such, is an ideal tool for performing PDE-constrained optimization. This paper describes an efficient approach in which the software stack provided by PETSc/TAO can be used for large-scale nonlinear time-dependent problems. Time integration can involve a range of high-order methods, both implicit and explicit. The PDE-constrained optimization algorithm used is gradient-based and seamlessly integrated with the simulation of the physical problem.

97 MATHEMATICS AND COMPUTING↗