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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An Evaluation of the Effect of Network Cost Optimization for Leadership Class Supercomputers

Dragonfly-based networks are an extensively deployed network topology in large-scale high-performance computing due to their cost-effectiveness and efficiency. The US will soon have three Exascale supercomputers for leadership class workloads deployed using dragonfly networks. Compared to indirect networks of similar scale, the dragonfly network has considerably reduced cable lengths, cable counts, and switch counts, resulting in significant network cost savings for a given system size, however, these cost reductions result in reduced global minimal paths and more challenging routing. Additionally, large scale dragonfly networks often require a taper at the global link level, resulting in less bisection bandwidth than is achievable in other traditional non-blocking topologies of equivalent scale. While dragonfly networks have been extensively studied, they have yet to be fully evaluated in an extreme scale (i.e., exascale) system that targets capability workloads. In this paper, we present the results of the first large scale evaluation of a dragonfly network on an exascale system (Frontier) and compare its behavior to a similar scale fat-tree network on a previous generation TOP500 system (Summit). This evaluation aims to determine the effect of network cost optimizations by measuring a tapered topology’s impact on capability workloads. Our evaluation is based on a collection of synthetic microbenchmarks, mini-apps, and full scale applications. It compares the scaling efficiencies of each benchmark between the dragonfly-based Frontier and the fat-tree-based Summit systems. Our results show that a dragonfly network is $\sim \mathbf{3 0 \%}$ more cost efficient than a fat-tree topology, which amortizes to $\sim 3 \%$ of an exascale system cost. Furthermore, while tapered dragonfly networks impose significant tradeoffs, the impacts are not as broad as initially thought and are mostly seen in applications with global communication patterns, particularly all-to-all (e.g., FFT-based algorithms), but also local communication patterns (e.g., nearest-neighbor algorithms) that are sensitive to network performance variability.

Khan, Awais↗
DOE OSTI2021

Material Identification Using Dual Energy X-ray Absorptiometry

Two implementations of dual energy X-ray absorptiometry were studied to identify materials using X-ray attenuation data taken with the Digital Radiography and Computed Tomography (DRCT) systems that were developed for the Recovered Chemical Materiel Directorate (RCMD). Maitrejean et al.’s approach utilizes eigen effects through Principal Component Analysis, while Osipov et al.’s approach proposed a physics-based method. Both approaches approximate mass attenuation coefficients of materials as a linear combination of basis functions (eigen effects) or physics-based equations. A set of coefficients {a 1 , a 2 , a 3 } or {B, D} were found by parameter optimization in EXCEL Solver. The identification parameters, {$\frac{a_{2}}{a_{1}}$, $\frac{a_{3}}{a_{1}}$} or estimated effective atomic number $\hat{Z}$ from {B, D}, were calculated to identify material of an aluminum 8 step wedge and a steel 8 step wedge in X-ray radiography images taken by a DRCT system. Maitrejean et al.’s approach was unable to provide reliable $\frac{a_{3}}{a_{1}}$ ratio values for identification of materials. Osipov et al.’s approach was found to be more robust in identify materials with a semi-empirical formula derived from test results in this study.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Analysis and Compensation of Tx and Rx IQ Imbalances in Uplink IM-OFDMA Systems

Index modulation-based orthogonal division multiple access (IM-OFDMA) has recently been proposed as a potential technique for future wireless communication systems due to its superior spectral efficiency and error performance over conventional multiple access schemes. However, its performance is still under investigation by researchers in light of a variety of scenarios and assumptions. Following this direction, in this Article, the individual and joint effects of the transmitter (Tx) and receiver (Rx) in-phase and quadrature imbalances (IQI) on the bit-error-rate (BER) performance of the uplink IM-OFDMA scheme are investigated by considering whether each user's RF front-end is identical or not. Moreover, to reduce the detrimental effect of IQI, a preamble-based estimation and compensation method is proposed for IM-OFDMA. Closed-form expressions for the average BER of IM-OFDMA are obtained by considering the physical effect of the Tx and Rx IQI. Also, using Monte Carlo simulations, the derived expressions are verified under different system configurations. Furthermore, analytical and simulation results reveal that Tx and Rx IQI cause an error floor in the BER performance of IM-OFDMA schemes. However, the proposed estimation and compensation method not only reduces the impact of IQI but also leads to a better BER performance compared to the case of no IQI, which mainly refers to the frequency diversity caused by the IQI.

42 ENGINEERING↗
DOE OSTI2024

HPC Network Simulation Tuning via Automatic Extraction of Hardware Parameters

Popular HPC network interconnection simulators such as SST/macro provide a variety of configurable parameters to explore the design space of hardware components such as network interface cards (NIC), switches, and links among them. While such knobs provide flexibility to explore design trade-offs for novel hardware, manually configuring simulations for matching configurations of the existing hardware to focus on topology exploration can be cumbersome and error-prone, leading to widely inaccurate simulations. This challenge is compounded when specifications of various (proprietary) technologies are not readily available or intentionally omitted. In this work, we propose a framework to autotune the multiple network models’ simulation configurations within SST/macro using Tree-structured Parzen Estimator-based Bayesian optimization to observe the effect on simulation accuracy across different message regimes. These regimes consist of small to large message sizes and latency to bandwidth-bound messages. We provide a detailed analysis of the simulation error for four representative HPC systems. Our Bayesian optimization based autotuning framework for network models achieves a maximum of 5x improvement in accuracy over best-effort manual configurations based on available hardware specifications.

Simulation, autotuning↗
DOE OSTI2022

Model-Based Framework to Optimize Charger Station Deployment for Battery Electric Vehicles

The development of battery electric vehicles (BEVs) is accelerating due to their environmental advantages over gasoline and diesel-powered vehicles, including a decrease in air pollution and an increase in energy efficiency. The deployment of charging infrastructure will need to increase to keep pace with demand, especially for large commercial vehicles for which few public chargers currently exist. In this paper, a new flexible framework is proposed for optimizing the placement of charging stations for BEVs, within which different physical models and optimization techniques may be used. Furthermore, a set of metrics is suggested to help enforce complex constraints and facilitate direct comparison between different optimization techniques. Unlike many existing charger placement techniques, the proposed method directly considers the historical driving patterns on a vehicle-by-vehicle basis, using transparent models to assess impacts of candidate charger placements, thus improving the explainability of the results. In the developed framework, modeled BEVs are first generated along the road network to mimic historical traffic data and are simulated traveling along a given route according to a simplified vehicle model. During the simulation, the charger placement problem is initially relaxed to allow vehicles to charge at any node along the road network, and vehicle states are tracked to assess areas of high charging demand. Charging stations are then placed based on the results of the relaxed simulation, and suggested placements are evaluated via road network simulation with fixed charger locations. This proposed framework is applied to a sample problem of placing charging stations along five major highway corridors for Class 8 over-the-road electric trucks. A novel mixed integer programming (MIP) formulation is proposed to optimize charger placements based upon the expected charging demand. Constraints were imposed on the final placement results to limit expected wait times at each station and ensure a minimum threshold of trucking routes are viable for BEVs. The results demonstrate the flexibility and potential effectiveness of the developed model-based framework for scalable charger station deployment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Massive compression for high data rate macromolecular crystallography (HDRMX): impact on diffraction data and subsequent structural analysis

New higher-count-rate, integrating, large-area X-ray detectors with framing rates as high as 17400 images per second are beginning to be available. These will soon be used for specialized macromolecular crystallography experiments but will require optimal lossy compression algorithms to enable systems to keep up with data throughput. Some information may be lost. Can we minimize this loss with acceptable impact on structural information? To explore this question, we have considered several approaches: summing short sequences of images, binning to create the effect of larger pixels, use of JPEG-2000 lossy wavelet-based compression, and use of Hcompress, which is a Haar-wavelet-based lossy compression borrowed from astronomy. We also explore the effect of the combination of summing, binning, and Hcompress or JPEG-2000. In each of these last two methods one can specify approximately how much one wants the result to be compressed from the starting file size. These provide particularly effective lossy compressions that retain essential information for structure solution from Bragg reflections.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Interfacial Effects on the Dielectric Properties of Elastomer Composites and Nanocomposites

Elastomer-based composites and nanocomposites are discussed, with the emphasis on the filler and interfacial effects on their dynamics, and the resulting manifestation in their macroscopic dielectric or mechanical response. Specifically, selected polydimethylsiloxane (PDMS)/barium-titanate and styrene-butadiene rubber (SBR)/graphene oxide nanocomposites are discussed, as examples where controlled spatial distribution of filler (structured composites) gives rise to significantly different dielectric and thermomechanical behaviors. Also, ethylene–propylene–diene (EPDM)/carbon black (CB) composites are presented, as examples of systems that exhibit an abnormal temperature dependence of dielectric relaxation; and this response is discussed in the context of CB cluster polarization and quantified through a simple scaling model of the same. Finally, multi-filler EPDM/CB/ceramic elastomer nanocomposites are discussed, as examples of systems with antagonistic interfacial effects between conductive and dielectric fillers, as well as with strong interphase responses that can overwhelm the dielectric contributions from the fillers; in these systems, interphasial responses result in counter-intuitive dielectric behaviors and in strong deviations from standard design principles typically employed in the design of dielectric composite systems.

Li, Bo↗
DOE OSTI2021

The Surface Chemistry and Structure of Colloidal Lead Halide Perovskite Nanocrystals

Since the initial discovery of colloidal lead halide perovskite nanocrystals, there has been significant interest placed on these semiconductors because of their remarkable optoelectronic properties, including very high photoluminescence quantum yields, narrow size- and composition-tunable emission over a wide color gamut, defect tolerance, and suppressed blinking. These material attributes have made them attractive components for next-generation solar cells, light emitting diodes, low-threshold lasers, single photon emitters, and X-ray scintillators. While a great deal of research has gone into the various applications of colloidal lead halide perovskite nanocrystals, comparatively little work has focused on the fundamental surface chemistry of these materials. While the surface chemistry of colloidal semiconductor nanocrystals is generally affected by their particle morphology, surface stoichiometry, and organic ligands that contribute to the first coordination sphere of their surface atoms, these attributes are markedly different in lead halide perovskite nanocrystals because of their ionicity. Herein, emerging work on the surface chemistry of lead halide perovskite nanocrystals is highlighted, with a particular focus placed on the most-studied composition of CsPbBr 3 . We begin with an in-depth exploration of the native surface chemistry of as-prepared, 0-D cuboidal CsPbBr 3 nanocrystals, including an atomistic description of their surface termini, vacancies, and ionic bonding with ligands. We then proceed to discuss various post-synthetic surface treatments that have been developed to increase the photoluminescence quantum yields and stability of CsPbBr 3 nanocrystals, including the use of tetraalkylammonium bromides, metal bromides, zwitterions, and phosphonic acids, and how these various ligands are known to bind to the nanocrystal surface. To underscore the effect of post-synthetic surface treatments on the application of these materials, we focus on lead halide perovskite nanocrystal-based light emitting diodes, and the positive effect of various surface treatments on external quantum efficiencies. We also discuss the current state-of-the-art in the surface chemistry of 1-D nanowires and 2-D nanoplatelets of CsPbBr 3 , which are more quantum confined than the corresponding cuboidal nanocrystals but also generally possess a higher defect density because of their increased surface area-to-volume ratios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Improving Projections of Antarctic Ice Sheet Contribution to Sea‐Level Change Through 2300 by Capturing Gravitational, Rotational, and Deformational Effects

Ice-mass change induces regionally varying patterns of sea-level change due to gravitational, rotational, and deformational (GRD) effects, which in turn influence marine-based ice stability in Antarctica. For improved projection of the Antarctic Ice Sheet (AIS), there is a need for including GRD effects in modeling and improving understanding of basin-by-basin sensitivity of ice evolution to GRD effects under a range of climate scenarios. We couple a high-resolution, higher-order ice-sheet model with a 1D global sea-level model that fully captures GRD effects, and simulate ice evolution in Antarctica under the Ice Sheet Model Intercomparison Project for CMIP6 experiments. We perform two sets of coupled simulations incorporating 1D Maxwell solid Earth structure suitable for West and East Antarctica and show that the Amundsen Sea Embayment (ASE) in West Antarctica has the highest sensitivity to GRD effects—in high-emission scenarios, grounding-line retreat accelerates by hundreds of kilometers by 2300 without GRD effects, but GRD effects delay this retreat on a timescale of decades. However, we find that delay times do not show a clear relationship to the strength of climate forcing alone. Furthermore, GRD effects can influence ice-sheet dynamics more than the choice of climate model for a given emissions scenario. In contrast, East Antarctica exhibits minimal sensitivity to GRD effects throughout the study period. These findings underscore the critical role of GRD effects in shaping future West AIS evolution, highlighting the importance of constraining the regional 3D Earth structure and bed topography in West Antarctica, particularly the ASE.

58 GEOSCIENCES↗
DOE OSTI2023

Initial Neutronics Investigation of a Chlorine Salt-Based Breeder Blanket

Tritium breeding blankets within D-T-fueled fusion reactors contain lithium compounds and typically require neutron multiplier materials to achieve a tritium breeding ratio (TBR) consistent with self-sustaining operation. Liquid breeder blankets have some advantages over solid blankets, and previous blanket studies have investigated liquid metal as well as liquid salt–based blankets. Liquid salts have reduced magnetohydrodynamic effects as compared to liquid metals, but typically have a lower TBR. Recently, advanced fission reactor concepts have considered chloride-based salts in their design, and there is a significant amount of research work occurring to study these salts. Chloride salts have previously been considered for fusion reactors, but studies have typically found lower breeding ratios than for fluoride salts, such as 2(LiF)-BeF 2 (flibe) so they have not been further developed. In this work, we use a one-dimensional cylindrical radiation transport model of a conceptual tokamak fusion reactor to investigate the neutronics feasibility of using a chloride salt–based blanket that uses chlorine enriched in 37 Cl, which has both a low capture cross section and a substantial (n,2n) cross section. It is found that chloride salts (LiCl mixed with BeCl 2 and/or PbCl 2 ) can potentially achieve a ~3% to 5% higher TBR than fluoride molten salts, notably flibe, in the absence of a solid multiplier. Including a solid multiplier, however, does narrow this advantage, with TBRs estimated within ~1% of flibe with a 2-cm Be multiplier. Chloride salts can also reach lower melting points than flibe, potentially improving the scope for the use of reduced activation ferritic-martensitic steel as a structural material. There is substantial uncertainty in the calculations driven by limited thermochemical data for the Cl salts, plus cross-section uncertainties. The production of 36 Cl through 35 Cl(n,g) and 37 Cl(n,2n) has the potential to challenge the waste disposal rating of the blanket. Calculations indicate that, while this is not an immediate showstopper, this case depends upon the exact waste disposal rating criteria used for 36 Cl. Further work could reduce these uncertainties with improved thermochemical data, higher-fidelity modeling for downselected salts, and more refined waste disposal calculations and regulatory guidance. Lastly, it must be recognized that, as for all molten salts, corrosion and chemistry can present appreciable technical challenges that require further assessment in developing a practical blanket concept, and also that the enrichment of chlorine presents an additional technical and supply chain challenge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Robustness of energy performance of Zero-Net-Energy (ZNE) homes

Zero-net-energy (ZNE) homes produce an adequate amount of energy on-site to meet their energy demand based on source energy for an entire year. California building energy efficiency standards require new residential buildings started in 2020 to be ZNE. For various reasons, a home designed as ZNE may not achieve ZNE performance in real operation. Here we aimed to quantify the robustness of the energy performance of ZNE homes due to weather variability, climate change, and the uncertainty of occupant behavior. A single-family ZNE house, based on the optimal cost-effective design in three California climate zones, was used to develop the EnergyPlus simulation models. Weather variations were considered from a combination of the historical 30 years’ actual meteorological year (AMY) weather data, typical year weather data in TMY3, and future weather data based on Intergovernmental Panel on Climate Change scenarios. Three scenarios of occupant behavior from the energy perspective were defined to represent the uncertainty about occupants’ activities, comfort requirements, and their adaptive interactions with buildings and systems. In terms of annual source energy, the simulation results of the ZNE homes showed: (1) a decrease of 23–38 percent for occupants with energy austerity behavior and an increase of 120–130 percent for occupants with energy wasteful behavior, compared with the baseline assumption of normal occupants; (2) a variation range of –15 percent to +14 percent for the results using 30-year AMY weather data compared with the baseline results using TMY3 weather data; (3) an increase of 10–13 percent with future weather in Fresno and Riverside and a decrease of 15 percent with San Francisco; and (4) climate change can reduce the gap between the austerity and wasteful consumption. These findings provide insights into how ZNE homes may perform in reality and inform architects, engineers, occupants, and policymakers to pay more attention to occupant behavior on design, operation, and regulations of ZNE homes to ensure energy performance robustness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Identification of Potent and Selective Inhibitors of Acanthamoeba : Structural Insights into Sterol 14α-Demethylase as a Key Drug Target

Acanthamoeba are free-living pathogenic protozoa that cause blinding keratitis, disseminated infection, and granulomatous amebic encephalitis, which is generally fatal. The development of efficient and safe drugs is a critical unmet need. Acanthamoeba sterol 14α-demethylase (CYP51) is an essential enzyme of the sterol biosynthetic pathway. Repurposing antifungal azoles for amoebic infections has been reported, but their inhibitory effects on Acanthamoeba CYP51 enzymatic activity have not been studied. Here, we report catalytic properties, inhibition, and structural characterization of CYP51 from Acanthamoeba castellanii. The enzyme displays a 100-fold substrate preference for obtusifoliol over lanosterol, supporting the plant-like cycloartenol-based pathway in the pathogen. The strongest inhibition was observed with voriconazole (1 h IC 50 0.45 μM), VT1598 (0.25 μM), and VT1161 (0.20 μM). The crystal structures of A. castellanii CYP51 with bound VT1161 (2.24 Å) and without an inhibitor (1.95 Å), presented here, can be used in the development of azole-based scaffolds to achieve optimal amoebicidal effectiveness.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Adaptive Neuro Fuzzy Inference System for Cyber-Intrusion Detection in a Smart Grid

The evolution of the power grid has brought increasing deployment of advance metering infrastructure, penetration of intelligent electronic devices, and integration of physical power system components with information and communications technologies. With the fast-expanding connectivity, cyber vulnerabilities arise due to the use of internet-based communication systems. These systems are targets of cyber-intrusions which attempt to disturb the normal power system functions. Traditional intrusion detection algorithms have been developed without an explicit model of the cyber components. In this paper, an algorithm to detect false data injections in the power system is proposed considering both cyber and physical models of the power system. The algorithm is based on an Adaptive Neuro Fuzzy Inference System (ANFIS) which collects information from state variables of the cyber-physical system to meet the performance requirements of the grid. Simulations of the proposed approach using the IEEE 13-bus test system validate the effectiveness of this artificial intelligence-based algorithm.

Adaptive Neuro Fuzzy Inference System (ANFIS), cyb↗
DOE OSTI2020

A new model for the effective thermal conductivity of polycrystalline solids

We introduce a novel model for the effective thermal conductivity of polycrystalline solids based on the thin-interface description of grain boundaries (GBs). In contrast to existing models, our new model treats a GB as an autonomous “phase” with its own thermal conductivity. The Kapitza resistance/conductance of a thin interface is then derived in terms of the interface thermal conductivity and width. In turn, the effective thermal conductivity of polycrystals is derived in terms of grain size, grain and GB conductivities, and GB width. This treatment allows the model to simulate the change of the Kapitza resistance/conductance with segregation/doping, GB structure/phase transition, or GB decohesion. Moreover, since the model assumes a finite width for GBs, it is expected to give better predictions than its sharp-interface-based counterparts for nanoscale grains. The predictions of the new model deviate from the corresponding ones from existing models by 1%–100% as the grain size approaches the GB width. High-fidelity finite-element simulations were conducted to validate the predictions of the new model. These simulations proved the higher accuracy of the new model. We also discuss how to generalize this treatment to other types of interfaces in heterogeneous materials. The advantages and limitations of the new model are summarized, and some future directions are highlighted.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Thin-Film Fracture Behavior for Diketopyrrolopyrrole Semiconducting Polymeric Films

Fracture energy, which quantifies a material’s resistance to the propagation of a pre-existing crack, is a key parameter for ensuring the mechanical reliability of stretchable organic electronic devices. However, most existing methods, such as a four-point bending fracture energy, utilized for measuring the fracture energy of semiconducting polymeric thin films are complicated by substrate effects, making it challenging to isolate the intrinsic behavior of the film from interfacial influences. In this study, we employed a pseudo free-standing pure shear method to systematically investigate the cohesive fracture energy of poly(diketopyrrolopyrrole-terthiophene) P(DPP-T)-based thin films to examine the effects of nanoconfinement, side chain length, degree of crystallinity, and strain rates. This method effectively eliminates substrate interference, enabling a direct assessment of the cohesive fracture energy of P(DPP-T) thin films. We found that thinner films and those with lower molecular weights exhibited significantly reduced fracture energies due to diminished chain entanglements. Additionally, films with shorter side chains displayed notably higher fracture energies, which were attributed to an increase in the degree of crystallinity. Finally, slower strain rates led to higher fracture energies, consistent with an enhanced stress relaxation. These insights offer practical guidelines for designing mechanically robust semiconducting polymers, contributing to the advancement of reliable, durable, flexible, and wearable electronic devices.

Zhang, Song [Univ. of Southern Mississippi, Hattie↗
DOE OSTI2020

Assessing Global and Local Radiative Feedbacks Based on AGCM Simulations for 1980–2014/2017

In order to avoid contamination of unobservable and uncertain effective radiative forcing (ERF) on the diagnosis of radiative feedbacks based on short-term climate variability, we verify the Kernel-Gregory feedback calculation method using atmospheric model experiments with prescribed ERF. We show that both clear-sky radiative fluxes and all-sky radiative feedbacks have a closure between model simulations and kernel derivations. A near-zero global mean net cloud feedback is found in the simulation with prescribed ERF, which results in a more negative global net climate feedback, -2 W m -2 K -1 . Consistent with AMIP6 ensemble mean results, the lapse rate feedback is the largest contributor among all feedbacks to temperature amplification over the three poles (Arctic, Antarctic and Tibetan Plateau), followed by surface albedo feedback and Planck feedback deviation from its global mean. Except for the higher surface albedo feedback in the Antarctic, other feedbacks are almost same between the Arctic and Antarctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effect of fluctuating redox conditions on trace metal release from wetland soils from South Carolina and stream sediments from Tennessee

Natural aquatic systems undergo fluctuating redox conditions due to microbial activity, varying water saturation levels, and nutrients dynamics. With fluctuating oxic and anoxic conditions, trace metals can be mobilized or sequestered in response to changes in iron and sulfur speciation and the concentrations and lability of organic carbon. We conducted a systematic laboratory-based microcosm study to examine the effect of redox fluctuations on trace metal mobility in samples collected from two different natural aquatic systems: riparian wetlands and a stream. We incubated water-saturated soils under three cycles of anoxic-oxic conditions (τanoxic:τoxic = 3) spanning 24 days and monitored the change in dissolved and bioavailable metal (copper (Cu), nickel (Ni), zinc (Zn), cobalt (Co), iron (Fe), and manganese (Mn)) concentrations. The dataset includes the results of the variation in metal concentrations due to redox fluctuations in wetland soils and stream sediments. Additionally, the variation in the bioavailable concentration of metals obtained using passive samplers based on diffuse gradient in thin-films technique is included in the dataset. We have also reported the change in the pH values and dissolved oxygen concentrations in the microcosms during the entire study of 24 days. The dataset also contains the dissolved organic carbon and sulfate concentrations, and the data on fractions of metals bound to reducible and oxidizable phases. For materials from both the wetlands and the stream, anoxic conditions favored Co and Zn release, which corresponded with the reductive dissolution of iron oxides. In contrast, dissolved Cu concentrations increased under oxic conditions for both sites and correlated positively with the release of sulfate. In wetland soils, dissolution of Fe (hydr)oxides increased Ni solubility; however, in stream sediments, Ni release occurred when sulfides or organic matter were oxidized. For stream sediments, each subsequent redox cycle increased the bioavailability of trace metals. Upon redox fluctuations in wetland soils, the bioavailability of Zn and Cu increased, whereas bioavailable Ni and Co decreased. This study illustrates that different trace metals display distinct bioavailability patterns during oxic-anoxic fluctuations in natural environments. The biogeochemical cycling of carbon and nitrogen in systems with redox fluctuations may be influenced by these patterns in trace metal availability in addition to the availability of electron donors and acceptors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Decoding the Oxygen Activity with Iron through Ligand-to-Metal Charge Transfer in Li-Rich Layered Cathodes

The quest for high-energy-density and cost-effective cathode materials has revitalized lithium-rich iron-based oxides, where Fe 3+ ions with their stable half-filled d 5 electronic configuration demonstrate unique potentials in regulating oxygen redox activity through ligand-to-metal charge transfer. Using operando 57 Fe Mössbauer spectroscopy, synchrotron X-ray techniques, and density functional theory calculations, we unravel the enhanced Fe–O redox activity through the LMCT process and the concomitant evolution of local structure distortion in the Li-rich layered system Li 1.2 MO 2 (M = Ni, Mn, Fe). The metastable Fe 4+ intermediates facilitate early activation of oxygen redox through LMCT along with increased delithiation at a lowered potential (below 4.5 V). Here, this process inherently suppresses Jahn–Teller distortion of Fe 4+ and exhibits Fe–O redox dominance over conventional Fe 3+ /Fe 4+ redox in Li-rich oxides. The Fe–O coupling redox exhibits improved initial Coulombic efficiency and 95% capacity retention over 200 cycles at 4.4 V. However, the LMCT process is accompanied by aggravated cation migration and voltage fade at low cutoff potentials, which requires further mitigation for the utilization of Fe–O redox. Overall, these findings demonstrate the regulating mechanism of iron for oxygen redox through LMCT and provide fundamental insights into the design principles for high-performance, cost-effective iron-based cathode materials.

36 MATERIALS SCIENCE↗