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At least 865 records · Page 48

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DOE OSTI2018

Cobalt nanoparticle-encapsulated carbon nanowire arrays: Enabling the fast redox reaction kinetics of lithium-sulfur batteries

The commercial application of lithium-sulfur batteries is still impeded by the unsatisfying cyclability due to the sluggish reaction kinetics and shuttling effect of polysulfide intermediates. We develop a cobalt nanoparticle-encapsulated carbon nanowire arrays on carbon cloth (CC@Co-CNAs) to enable the fast redox reaction kinetics of the lithium sulfur batteries. The nanowire array-decorated carbon cloth as conductive matrix for sulfur active material could provide highly exposed cobalt nanoparticle active sites, owing to the high length-diameter ratio of the prepared CC@Co-CNAs. The binding affinity between the cobalt nanoparticle-incorporated materials and polysulfide intermediates is enhanced by Co-S bonds, which facilitates the redox reaction of active materials and consequently results in a high sulfur utilization for cathode especially with high sulfur loading. The lithium sulfur battery with CC@Co-CNAs as electrode materials delivers a high initial discharge capacity of 1228 mAh g –1 at 0.25 C, and a high initial discharge capacity of 807 mAh g –1 at 1C with a low capacity fading rate of 0.06% per cycle during 300 cycles. Furthermore, a discharge capacity of 958 mAhg –1 at 0.1 C is achieved for the cell even with a corresponding sulfur loading of 6.2 mg cm –2 .

25 ENERGY STORAGE↗

DOE OSTI2022

High-performance organic photodetectors enabled by a refined fibrillar multiphase morphology

Film morphology of donor:acceptor blend layers plays a critical role in photon-to-current efficiency and dark/noise current of organic photodetectors (OPDs). One effective approach to manipulate crystallization and mesoscale phase separation of such blend layers is sequential casting (SC). However, the guiding strategies to control the morphology and the impacts on OPD performance of the SC films remain elusive, as the film structural evolution during SC is different from conventional blend casting (BC). In this report a refined fibrillar multiphase morphology is demonstrated by SC in an NT812:IEICO-4F blend film, where the high-quality IEICO-4F crystallites infiltrate the robust NT812 fibril network from the surface to the bulk. Such a morphology leads to improved charge generation and collection, reduced trap states, and enhanced charge block capability of resultant device, enabling simultaneous achievement of high external quantum efficiency and low dark/noise current. A maximum special detectivity of 5 × 10 13 Jones is achieved at 860 nm under –0.1 V, which is among the highest detectivities for vis-to-NIR OPDs. The linear dynamic range and response speed are also improved. Such enhancements are parallelly observed from OPD devices based on other blend systems with similar fibrillar refinement, which provides guidelines for film structure manipulation towards high OPD performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Triple oxygen and hydrogen stable isotope composition of water in Murchison carbonaceous chondrite accessed by thermogravimetry-enabled laser spectroscopy

For this work, we have developed the capability to measure 17 O/ 16 O in H 2 O and OH - of hydrous minerals by a technique using thermogravimetric analysis coupled with isotope ratio infrared spectroscopy (TGA-IRIS) on a suite of liquid water standards, terrestrial mineral standards, multi-mineral synthetic mixtures of terrestrial samples, and Murchison carbonaceous chondrite. This 17 O/ 16 O analytical capability is combined with the previously developed TGA-IRIS capability of 18 O/ 16 O, which enables us to calculate Δ `17 O values. Additionally, we have made 2 H/ 1 H measurements by TGA-IRIS on the suite of materials. Analyses of 328 standard water samples sealed into silver tubes (0.25 μL, 174 VSMOW and 154 GISP) analyzed over the course of three years yielded δ 18 O values by TGA-IRIS with precision of ±0.30 ‰, δ 17 O of ±0.24 ‰, Δ `17 O of ±0.126 ‰, and δ 2 H ± 7.5 ‰ (± 1 Std. Dev.). TGA-IRIS analyses of a suite of hydrous minerals (oxy-hydroxide, mica, serpentines, sulfide, phyllosillicates) yields similar precision. TGA-IRIS analyses of the CM2 carbonaceous chondrite Murchison resulted in δ 18 O, δ 17 O, Δ `17 O, and δ 2 H values of the H 2 O and/or OH - from its hydrous minerals. Δ `17 O values of Murchison H 2 O range from 1.034 ‰ at 350 °C, to -0.368 ‰ at 650 °C, to -1.75 ‰ at 850 °C. TGA-IRIS can generate Δ `17 O values of H 2 O and/or OH - in hydrous materials that are well within the precision needed for the analysis of meteoritic samples, as well as samples returned from asteroids, such as Ryugu and Bennu.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Enabling fast, stable and accurate peridynamic computations using multi-time-step integration

Peridynamics is a nonlocal extension of classical continuum mechanics that is well-suited for solving problems with discontinuities such as cracks. This paper extends the peridynamic formulation to decompose a problem domain into a number of smaller overlapping subdomains and to enable the use of different time steps in different subdomains. This approach allows regions of interest to be isolated and solved at a small time step for increased accuracy while the rest of the problem domain can be solved at a larger time step for greater computational efficiency. Lastly, performance of the proposed method in terms of stability, accuracy, and computational cost is examined and several numerical examples are presented to corroborate the findings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

An adaptive fast multipole method in Cartesian basis, enabled by algorithmic differentiation

A novel form of the fast multipole method is realized by the combination of adaptive data structures with implementation of the multipole expansions and their translations in Cartesian basis, and enabled by algorithmic differentiation. It may be possible to generalize it to any kernel that allows its formulation as a function of small quantities with respect to which they can be expanded. There is no hard and fast rule recipe that works for all cases. However, it is shown how to do it for the softened Coulomb kernel, which is different from the Coulomb kernel. The characteristics and performance of the method are mapped and shown to provide an attractive option for a generic fast multipole algorithm in a wide region of the parameter space. The algorithm is illustrated with a beam dynamics application.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Adaptive simulations enable computational design of electron beam processing of nanomaterials with supersonic micro-jet precursor

Focused Electron Beam Induced Processing (FEBIP) is a powerful tool for the “direct-write” of nanomaterials with the possibility of atomistic control on suspended 2D material substrates. FEBIP capabilities have been significantly expanded by using a localized jet-based delivery of precursors, and especially when a thermally energized supersonic micro-jet enhances the delivery of mass flux along with controlling the far-from-equilibrium thermodynamic state of adsorbed adatoms. The possibilities of growing nanomaterials with “dialed-in” composition with ultra-high growth rates and aspect ratios up to 100:1 have been demonstrated using the supersonic micro-jet-FEBIP. Bringing this scientific discovery to the level of maturity required for practical applications in additive nanomanufacturing requires simulation tools that are capable of capturing the complex flow physics of micro-jet-substrate interactions that bridge a wide range of flow regimes from the high-density gas micro-jet expanding into the vacuum environment of FEBIP. To address this significant computational challenge, a new approach has been developed and described in this work for a multiscale adaptive DSMC (Direct Simulation Monte Carlo) algorithm to predict the micro-jet gas dynamics in an FEBIP environment, spanning the full range of flow regimes from low Knudsen (Kn) number O(0.01) continuum flow to high Kn of O(10) for the molecular flow within a unified computational framework. Here, the fundamental principles of the adaptive DSMC algorithm are described, its viability as a DSMC technique is demonstrated, and computational improvements for the benchmark cases are discussed in the context of advancing 3D nanofabrication with FEBIP. Ultimately, combining the first principle simulations via adaptive DSMC with the complementary experimental data will enable the creation of the powerful CAD tools for in silico design and optimal operation of micro-jet-FEBIP.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Machine learning-enabled prediction of chemical durability of A 2 B 2 O 7 pyrochlore and fluorite

Pyrochlore-structure type and its derivative in a general formula A 2 B 2 O 7 (A = rare earth elements and actinides; B = Ti, Sn, Zr, Hf, Pb, Si, etc.) display excellent structural flexibility and rich crystal chemistry as promising nuclear waste form materials capable of immobilizing actinides and fission products. It is essential to understand these materials’ chemical durability and element release of radionuclides in order to evaluate their performance in near-field environment. However, it is a formidable grand technological challenge to experimentally perform durability testing across hundreds of thousands of possibilities resulting from their extreme compositional complexities due to cation substitutions at both A and B-sites. In this work, we demonstrate a machine learning approach to determine the key materials parameters and structural characteristics governing the leaching behaviors from a small set of selected compositions as model systems, enabling a science-based prediction of their chemical durability that can be extended to a wide range of chemical compositions. The combination of four key structural characteristics and materials parameters, including ionic radius size difference , ionic potential difference , electronegativity difference , and lattice parameter , creates features an optimized prediction of the chemical durability. Two machine learning models, linear regression and Kernel ridge regression models, are trained on the randomly-split training dataset derived from the experimentally-determined elemental release rates, and subsequently tested on the testing dataset. The predicted leaching rates from both machine learning models show an excellent agreement with the experimental data, demonstrating the feasibility of rapidly evaluating the material properties of new compositions. These results highlight the immense potential of synergizing informatics through machine learning-based models and well-controlled experiments of selected model systems to accelerate materials design and discovery with optimized compositions and performance of promising materials for effective nuclear waste management.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Core-shell structured tow-pregs enabled additive manufacturing of continuously reinforced thermoset composites

One of the major challenges in thermally curable polymer composite additive manufacturing is the slow curing time of thermally curable resins, coupled with a significant drop in thermoset viscosity upon heating, making the formation of complex shapes difficult. To tackle these issues, we have introduced a novel rapid composite preformation strategy called Tow-Preg Cladding (TPC). This technique involves the use of a thin and rapidly curable dual-cure resin, which combines a thermally curable resin (such as epoxy) with a fast photo-curable resin. The dual-cure resin is applied as a coating over a thermally curable resin tow-preg, enabling the formation of a rigid cladding that supports and shapes the tow-pregs into the desired geometries and patterns. The key advantage of this approach lies in the sequential formation of an interpenetrating polymer network (IPN) at the interlayer between laminates, resulting from the curing of the photocurable resin and the thermally curable resin sequentially. This IPN formation enhances interlaminar bonding in the composite, contributing to its overall strength and performance. The composites produced using this technique exhibited impressive mechanical properties, including longitudinal tensile strength of 1058.2 MPa, longitudinal tensile modulus of 74.2 GPa, flexural strength of 1080.4 MPa, and flexural modulus of 41.7 GPa. Overall, our Tow-Preg Cladding approach shows great promise in overcoming the challenges associated with thermally curable polymer composite additive manufacturing. It offers a viable solution to creating strong, shape-specific thermoset composites efficiently with enhanced mechanical properties.

42 ENGINEERING↗

DOE OSTI2024

Advances in mass spectrometry-enabled multiomics at single-cell resolution

We report biological organisms are multifaceted, intricate systems where slight perturbations can result in extensive changes in gene expression, protein abundance and/or activity, and metabolic flux. These changes occur at different timescales, spatially across cells of heterogeneous origins, and within single-cells. Hence, multimodal measurements at the smallest biological scales are necessary to capture dynamic changes in heterogeneous biological systems. Of the analytical techniques used to measure biomolecules, mass spectrometry (MS) has proven to be a powerful option due to its sensitivity, robustness, and flexibility with regard to the breadth of biomolecules that can be analyzed. Recently, many studies have coupled MS to other analytical techniques with the goal of measuring multiple modalities from the same single-cell. It is with these concepts in mind that we focus this review on MS-enabled multiomic measurements at single-cell or near-single- cell resolution.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Slow manifolds of classical Pauli particle enable structure-preserving geometric algorithms for guiding center dynamics

Since variational symplectic integrators for the guiding center was proposed, structure-preserving geometric algorithms have become an active research field in plasma physics. We found that the slow manifolds of the classical Pauli particle enable a family of structure-preserving geometric algorithms for guiding center dynamics with long-term stability and accuracy. This discovery overcomes the difficulty associated with the unstable parasitic modes for variational symplectic integrators when applied to the degenerate guiding center Lagrangian. It is a pleasant surprise that Pauli's Hamiltonian for electrons, which predated the Dirac equation and marks the beginning of particle physics, reappears in classical physics as an effective algorithm for solving an important plasma physics problem. This technique is applicable to other degenerate Lagrangians reduced from regular Lagrangians.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗

DOE OSTI2025

A network-enabled pipeline for gene discovery and validation in non-model plant species

Identifying key regulators of important genes in non-model crop species is challenging due to limited multi-omics resources. To address this, we introduce the network-enabled gene discovery pipeline NEEDLE, a user-friendly tool that systematically generates coexpression gene network modules, measures gene connectivity, and establishes network hierarchy to pinpoint key transcriptional regulators from dynamic transcriptome datasets. After validating its accuracy with two independent datasets, we applied NEEDLE to identify transcription factors (TFs) regulating the expression of cellulose synthase-like F6 ( CSLF6 ), a crucial cell wall biosynthetic gene, in Brachypodium and sorghum. Our analyses uncover regulators of CSLF6 and also shed light on the evolutionary conservation or divergence of gene regulatory elements among grass species. These results highlight NEEDLE’s capability to provide biologically relevant TF predictions and demonstrate its value for non-model plant species with dynamic transcriptome datasets.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Enabling end-to-end secure federated learning in biomedical research on heterogeneous computing environments with APPFLx

Facilitating large-scale, cross-institutional collaboration in biomedical machine learning (ML) projects requires a trustworthy and resilient federated learning (FL) environment to ensure that sensitive information such as protected health information is kept confidential. Specifically designed for this purpose, this work introduces APPFLx - a low-code, easy-to-use FL framework that enables easy setup, configuration, and running of FL experiments. APPFLx removes administrative boundaries of research organizations and healthcare systems while providing secure end-to-end communication, privacy-preserving functionality, and identity management. Furthermore, it is completely agnostic to the underlying computational infrastructure of participating clients, allowing an instantaneous deployment of this framework into existing computing infrastructures. Experimentally, the utility of APPFLx is demonstrated in two case studies: (1) predicting participant age from electrocardiogram (ECG) waveforms, and (2) detecting COVID-19 disease from chest radiographs. Here, ML models were securely trained across heterogeneous computing resources, including a combination of on-premise high-performance computing and cloud computing facilities. By securely unlocking data from multiple sources for training without directly sharing it, these FL models enhance generalizability and performance compared to centralized training models while ensuring data remains protected. In conclusion, APPFLx demonstrated itself as an easy-to-use framework for accelerating biomedical studies across organizations and healthcare systems on large datasets while maintaining the protection of private medical data.

Biomedical Research↗

DOE OSTI2024

Nonvolatile electrochemical memory at 600°C enabled by composition phase separation

Silicon-based microelectronics are limited to ~150°C and therefore not suitable for the extremely high temperatures in aerospace, energy, and space applications. While wide-band-gap semiconductors can provide high-temperature logic, nonvolatile memory devices at high temperatures have been challenging. In this work, we develop a nonvolatile electrochemical memory cell that stores and retains analog and digital information at temperatures as high as 600°C. Through correlative scanning transmission electron microscopy, we show that this high-temperature information retention is a result of composition phase separation between the oxidized and reduced forms of amorphous tantalum oxide. This result demonstrates a memory concept that is resilient at extreme temperatures and reveals phase separation as the principal mechanism that enables nonvolatile information storage in these electrochemical memory cells.

42 ENGINEERING↗

DOE OSTI2025

Uniform secondary current distribution at disk electrodes under Tafel kinetics enabled by concentric current-shielding rings

Non-uniform secondary current distribution at rotating disk electrodes (RDE) is a common problem when using resistive electrolyte media or large applied currents. In a recent publication, we have shown that auxiliary electrodes such as the ring of a rotating ring disk electrode (RRDE) can help suppress current non-uniformities at the disk enabling reliable electroanalytical measurements. However, this previous work considered linear kinetics where current distribution non-uniformities were moderate. In the present contribution, we consider current distribution non-uniformities encountered under Tafel kinetics. We show, for the case of 2,5-dihydroxy-1,4-benzoquinone (DHBQ) reduction, that optimally chosen ring conditions serve to provide effective shielding at the disk edge rendering the overall disk current distribution to be uniform. Numerical modeling and scaling analysis (using the Wagner number) are presented to aid a user in determining the optimal ring current density for achieving uniform disk current distribution under Tafel kinetics. This approach is especially useful when studying soluble-soluble redox transitions for which, unlike deposit distribution in electrodeposition, the current distribution non-uniformity is not visually apparent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Enabling high rate charge and discharge capability, low internal resistance, and excellent cycleability for Li-ion batteries utilizing graphene additives

A liquid-phase mixing method is adopted to uniformly disperse the graphene nanosheets onto LiNi 1/3 Co 1/3 Mn 1/3 O 2 cathode for high-performance Li-ion batteries (LIBs). The electrochemical performance was characterized using a full pouch cells with state-of-the-art electrode areal loading (compared to half coin cells). The addition of graphene sheets (i.e., only 1 wt%) significantly improves the high rate capability for charging and discharging operation. For example, 6 times improvement in 5 C charging was achieved providing further insights in enabling extreme fast charging for LIBs. Other benefits include longer cycleability, lower internal resistance, and higher lithium ion diffusion coefficient, demonstrated by charge-discharge cycling tests and electrochemical impedance spectroscopy. Higher capacity retention of 88.2% and decreased internal resistance of ~0.9 Ω are observed after 400 cycles. The diffusion coefficient of Li ions is 6.49 × 10 -8 cm 2 s -1 when charged to 4.2 V, which is approximately 1.37 times higher compared to the configuration with no graphene sheet (4.74 × 10 -8 cm 2 s -1 ). To conclude, the improved performance is ascribed to a robust network among the active materials formed by graphene sheets, which serves as an extended current conductor and facilitates charge transfer, ionic reversibility, and ionic transportation.

25 ENERGY STORAGE↗

DOE OSTI2020

Enabling fast charging of lithium-ion batteries through secondary- /dual- pore network: Part I - Analytical diffusion model

Battery performance is strongly correlated with electrode microstructural properties. Enabling fast charging of lithium-ion batteries requires improved through-plane ionic diffusion that can be achieved through, among other strategies, structured electrodes with a secondary- or dual-pore network (SPN). In this work, an analytical model investigates the impact of such an SPN on ionic diffusion with a composite electrode, considering various pore-channel geometries and comparing to standard electrodes with identical gravimetric- and volumetric-specific theoretical capacities. Relevant SPN design parameters and tortuosity coefficients are identified according to three optimization objectives that aim to balance the improved overall through-plane diffusion, thanks to the coarse aligned channels, and degraded in-plane diffusion because of the porous matrix densification required to maintain gravimetric- and volumetric-specific theoretical capacities. The model indicates that a relatively low amount of SPN is required and that electrodes with high through-plane tortuosity and low in-plane tortuosity benefit most from such architecture.

25 ENERGY STORAGE↗

DOE OSTI2020

Enabling high rate capability, low internal resistance, and excellent cyclability for vanadium redox flow batteries utilizing ultrafast laser-structured graphite felt

The electrochemical performance of vanadium redox flow batteries (VRFBs) was enhanced via laser-patterned graphite felt (GF) electrodes. The laser-structured GF electrodes engineered via preparing a series of well-ordered microscopic channel structures with an average width of 200 μm, creating a three-dimensional carbon framework. The ultrafast laser patterning increased the porosity by 10%, as compared to pristine electrode. The analysis of the overpotential distribution using electrochemical impedance spectroscopy revealed that the electrode polarization involving charge transfer and diffusion resistance is strongly alleviated with the aid of carbon micro-perforation. The advanced design of laser-structured GF electrode also exhibits high rate capability, low internal resistance, and excellent cyclability. The improved performance was attributed to the synergistic effect involving (i) high electrochemically active surface area for rapid electrochemical reactions (i.e., V(II)/V(III) and V(IV)/V(V) redox couples) and (ii) excellent transport properties for facile electron/ion/species transport. The micro-scale channels created with the laser-ablation technique act as capillary structures and enabled homogeneous and rapid wetting of GF electrodes as formulated with the classical Washburn equation. The VRFB equipped with the laser-structured GF electrodes delivered a high discharge capacity with exceptional capacity retention upon extended cycling (>84.9%). In conclusion, accordingly, the design of laser-structured electrode paves the pathway towards finely tuning the electrode internal microstructure for improved cyclability, durability, and capacity retention in various electrochemical energy storage/conversion devices (e.g. all-vanadium redox flow batteries).

25 ENERGY STORAGE↗