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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Revealing the Origin and Nature of the Buried Metal‐Substrate Interface Layer in Ta/Sapphire Superconducting Films

Abstract Despite constituting a smaller fraction of the qubit's electromagnetic mode, surfaces and interfaces can exert significant influence as sources of high‐loss tangents, which brings forward the need to reveal properties of these extended defects and identify routes to their control. Here, we examine the structure and composition of the metal‐substrate interfacial layer that exists in Ta/sapphire‐based superconducting films. Synchrotron‐based X‐ray reflectivity measurements of Ta films, commonly used in these qubits, reveal an unexplored interface layer at the metal‐substrate interface. Scanning transmission electron microscopy and core‐level electron energy loss spectroscopy identified an intermixing layer (≈0.65 ± 0.05 nm) at the metal‐substrate interface containing Al, O, and Ta atoms. Density functional theory modeling reveals that the structure and properties of the Ta/sapphire heterojunctions are determined by the oxygen content on the sapphire surface prior to Ta deposition for two atomic terminations of sapphire. Using a multimodal approach, we gained deeper insights into the interface layer between the metal and substrate, which suggests that the orientation of deposited Ta films depend on the surface termination of sapphire. The observed elemental intermixing at the metal‐substrate interface influences the thermodynamic stability and electronic behavior of the film, which may also affect qubit performance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microbial drought resistance may destabilize soil carbon

Droughts are becoming more frequent and intense with climate change. As plants and microbes respond to drought, there may be consequences for the vast stocks of organic carbon stored in soils. If microbes sustain their activity under drought, soils could lose carbon, especially if inputs from plants decline. Empirical and theoretical studies reveal multiple mechanisms of microbial drought resistance, including tolerance and avoidance. Physiological responses allow microbes to acclimate to drought within minutes to days. Along with dispersal, shifts in community composition could allow microbiomes to maintain functioning despite drought. Microbes might also adapt to drier conditions through evolutionary processes. Together, these mechanisms could result in soil carbon losses larger than currently anticipated under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Quantifying the Effect of Magnetic Field Line Curvature Scattering on the Loss of Ring Current Ions

During geomagnetic storms, the ring current ions sometimes exhibit rapid loss as suggested by the fast recovery of the Dst index on a time scale of a few hours. Here, the effects of magnetic field line curvature (FLC) scattering on the loss of ring current ions, which have not been well quantified, are studied here by test particle simulations under the T89c magnetic field model. Our simulation results show that the prediction of ion loss based on a single–value cutoff of the κ parameter or maximum of δμ/μ of a single FLC scattering is not accurate. Instead, the e–folding lifetime (τ) for the loss of ring current ions due to cumulative FLC scattering has been calculated for different initial ion energies, equatorial pitch angles, and L shells under different geomagnetic conditions. The results show that in general the FLC scattering loss is faster for ions of higher energy, higher mass, smaller pitch angle, higher L, and at high Kp level. Specifically, we find that at Kp = 6 the lifetime can be <10 h at L > 5 for 100 s keV protons and at L > 4 for 100 s keV O + , which demonstrates that FLC scattering can be an important mechanism for the observed fast loss (τ < 10 h) of ring current ions during geomagnetic storms. Furthermore, we formulate an empirical formula for τ as a function of ion energy, pitch angle, position, species, and Kp. The empirical formula can be directly included in ring current models to account for the FLC scattering effects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Aryl hydrocarbon receptor-dependent toxicity by retene requires metabolic competence

Polycyclic aromatic hydrocarbons (PAHs) are a class of organic compounds frequently detected in the environment with widely varying toxicities. Many PAHs activate the aryl hydrocarbon receptor (AHR), inducing the expression of a battery of genes, including xenobiotic metabolizing enzymes like cytochrome P450s (CYPs); however, not all PAHs act via this mechanism. We screened several parent and substituted PAHs in in vitro AHR activation assays to classify their unique activity. Retene (1-methyl-7-isopropylphenanthrene) displays Ahr2-dependent teratogenicity in zebrafish, but did not activate human AHR or zebrafish Ahr2, suggesting a retene metabolite activates Ahr2 in zebrafish to induce developmental toxicity. To investigate the role of metabolism in retene toxicity, studies were performed to determine the functional role of cyp1a, cyp1b1, and the microbiome in retene toxicity, identify the zebrafish window of susceptibility, and measure retene uptake, loss, and metabolite formation in vivo. Cyp1a-null fish were generated using CRISPR-Cas9. Cyp1a-null fish showed increased sensitivity to retene toxicity, whereas Cyp1b1-null fish were less susceptible, and microbiome elimination had no significant effect. Zebrafish required exposure to retene between 24 and 48 hours post fertilization (hpf) to exhibit toxicity. After static exposure, retene concentrations in zebrafish embryos increased until 24 hpf, peaked between 24 and 36 hpf, and decreased rapidly thereafter. We detected retene metabolites at 36 and 48 hpf, indicating metabolic onset preceding toxicity. This study highlights the value of combining molecular and systems biology approaches with mechanistic and predictive toxicology to interrogate the role of biotransformation in AHR-dependent toxicity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Melanization slows the rapid movement of fungal necromass carbon and nitrogen into both bacterial and fungal decomposer communities and soils

Microbial necromass contributes significantly to both soil carbon (C) persistence and ecosystem nitrogen (N) availability, but quantitative estimates of C and N movement from necromass into soils and decomposer communities are lacking. Additionally, while melanin is known to slow fungal necromass decomposition, how it influences microbial C and N acquisition as well as elemental release into soils remains unclear. Here, we tracked decomposition of isotopically labeled low and high melanin fungal necromass and measured 13 C and 15 N accumulation in surrounding soils and microbial communities over 77 d in a temperate forest in Minnesota, USA. Mass loss was significantly higher from low melanin necromass, corresponding with greater 13 C and 15 N soil inputs. A taxonomically and functionally diverse array of bacteria and fungi was enriched in 13 C and/or 15 N at all sampling points, with enrichment being consistently higher on low melanin necromass and earlier in decomposition. Similar patterns of preferential C and N enrichment of many bacterial and fungal genera early in decomposition suggest that both microbial groups co-contribute to the rapid assimilation of resource-rich soil organic matter inputs. While overall richness of taxa enriched in C was higher than in N for both bacteria and fungi, there was a significant positive relationship between C and N in co-enriched taxa. Collectively, our results demonstrate that melanization acts as a key ecological trait mediating not only fungal necromass decomposition rate but also necromass C and N release and that both elements are rapidly co-utilized by diverse bacterial and fungal decomposers in natural settings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Restoration of Geographically Isolated Wetlands: An Amphibian-Centric Review of Methods and Effectiveness

Geographically isolated wetlands provide a critical habitat for pond-breeding amphibians, a taxa of broad conservation concern. Global wetland loss and degradation has made restoration essential for amphibian conservation. Restoration goals typically include recovering the wetlands’ physiochemical, hydrological, and ecological functions. However, for pond-breeding amphibians, successful restoration should also result in sustained populations, which is difficult to assess and infrequently reported. In this paper, we review the available evidence that restoration of geographically isolated wetlands promotes pond-breeding amphibian occupancy and population persistence. We provide an overview of restoration practices addressing hydrology, vegetation, and ecological processes within these unique environments and across spatial scales. We then summarize the evidence, and discuss the limitations, for evaluating successful restoration within the context of amphibian conservation across these categories. Finally, we provide recommendations for researchers and practitioners to leverage prior successes and establish systematic data collection and dissemination. Moving restoration of wetlands for amphibian conservation forward will require more robust data collection and reporting.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

All Solid-State Li/LLZO/LCO Battery Enabled by Alumina Interfacial Coating

Li 7 La 3 Zr 2 O 12 (LLZO) garnet-type lithium-ion conductors are being investigated as a promising solid electrolyte for solid-state lithium batteries. To enable a functional all-solid-state configuration intensive investigations are needed to reduce the cathode/electrolyte interfacial resistance which contributes the most to cell performance loss. Among the commercial cathode materials investigated so far, LiCoO 2 (LCO) is one of the most stable with garnet electrolytes as only a superficial reaction has been detected between the two materials. However, even this minor reaction would block the Li-ion transport through the interface, resulting in deteriorated cell performance. In this work, we demonstrate that a thin aluminum oxide layer (5 nm) can be an effective interlayer to impede the formation of a harmful interphase and enable facile Li-ion transfer between LCO and the LLZO garnet. Room-temperature-sputtered LCO thin films were employed to form an interface with the garnet electrolyte and annealed at 800 °C to reveal the effect of the interfacial reaction on the Li-ion transfer across the interface. An aluminum oxide layer was then introduced between LCO and the garnet electrolyte by sputtering a metallic aluminum layer which is then annealed together with the upper LCO layer in oxygen, or by direct atomic layer deposition of the oxide. Compared to the LCO/LLZO/Li cells without an aluminum oxide interlayer, those with the interlayer exhibited improved performance, i.e., a stable discharge capacity of up to 90 mAh/(g LCO) at a C/10 rate, a rate capability up to 1.68C and a stable galvanostatic cycling at 0.1C for over 100 cycles with a discharge capacity fade rate of 0.15% per cycle. It was determined that aluminum diffused into the LCO layer after preventing the initial detrimental reaction between LCO and the LLZO garnet from happening during high temperature annealing, suggesting that the coating does not have to remain a physically blocking layer during cycling to function.

Electrochemistry↗
DOE OSTI2024

Aging Mechanisms of Broad Area ~800 nm Laser Diodes

Here, this work presents a comprehensive study of early aging behavior (<500 hr) in ~800 nm, phosphide-based laser diodes grown by solid-source MBE with different oxygen concentration levels incorporated into the diode epitaxial layers during growth. The data indicate that lasing characteristics prior to aging are degraded by oxygen introduction, but the gradual power degradation rate after the onset of aging is not a strong function of oxygen at these concentration levels. Devices with oxygen concentrations of ~2.5 × 10 15 cm -3 showed significantly longer delay before the onset of aging (incubation time) than devices with less than 1 × 10 15 cm -3 oxygen. Generation-Recombination current and Laser Beam Induced Current measurements indicate that defect densities and aggregation are suppressed at the facets by oxygen, which can explain longer incubation times. Diagnostic data and parametric fits to diode simulation models show that increased cavity optical loss and defect density are primarily responsible for gradual power degradation during aging, rather than changes in nonradiative recombination. Mechanisms are proposed that explain this behavior, based on density functional theory (DFT) simulations and known recombination-enhanced defect generation phenomena.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Dynamic subcanopy leaf traits drive resistance of net primary production across a disturbance severity gradient

Across the globe, the forest carbon sink is increasingly vulnerable to an expanding array of low- to moderate-severity disturbances. However, some forest ecosystems exhibit functional resistance (i.e., the capacity of ecosystems to continue functioning as usual) following disturbances such as extreme weather events and insect or fungal pathogen outbreaks. Unlike severe disturbances (e.g., stand-replacing wildfires), moderate severity disturbances do not always result in near-term declines in forest production because of the potential for compensatory growth, including enhanced subcanopy production. Community-wide shifts in subcanopy plant functional traits, prompted by disturbance-driven environmental change, may play a key mechanistic role in resisting declines in net primary production (NPP) up to thresholds of canopy loss. However, the temporal dynamics of these shifts, as well as the upper limits of disturbance for which subcanopy production can compensate, remain poorly characterized. In this study, we leverage a 4-year dataset from an experimental forest disturbance in northern Michigan to assess subcanopy community trait shifts as well as their utility in predicting ecosystem NPP resistance across a wide range of implemented disturbance severities. Through mechanical girdling of stems, we achieved a gradient of severity from 0% (i.e., control) to 45, 65, and 85% targeted gross canopy defoliation, replicated across four landscape ecosystems broadly representative of the Upper Great Lakes ecoregion. We found that three of four examined subcanopy community weighted mean (CWM) traits including leaf photosynthetic rate (p = 0.04), stomatal conductance (p = 0.07), and the red edge normalized difference vegetation index (p < 0.0001) shifted rapidly following disturbance but before widespread changes in subcanopy light environment triggered by canopy tree mortality. Surprisingly, stimulated subcanopy production fully compensated for upper canopy losses across our gradient of experimental severities, achieving complete resistance (i.e., no significant interannual differences from control) of whole ecosystem NPP even in the 85% disturbance treatment. Additionally, we identified a probable mechanistic switch from nutrient-driven to light-driven trait shifts as disturbance progressed. Our findings suggest that remotely sensed traits such as the red edge normalized difference vegetation index (reNDVI) could be particularly sensitive and robust predictors of production response to disturbance, even across compositionally diverse forests. The potential of leaf spectral indices to predict post-disturbance functional resistance is promising given the capabilities of airborne to satellite remote sensing. We conclude that dynamic functional trait shifts following disturbance can be used to predict production response across a wide range of disturbance severities.

resistance↗
DOE OSTI2025

Topology-Aware Reinforcement Learning for Voltage Control: Centralized and Decentralized Strategies

Volt-VAR control (VVC) methods based on deep reinforcement learning (DRL) can effectively control distribution grid voltage and minimize power loss by implementing corrective and preventive control measures on the reactive power output of inverter-based distributed energy resources (DERs). However, model-free DRL-based VVC approaches usually cannot capture the important topological feature of the power system since they use a fully-connected network (FCN) to deliver the action. Therefore, this paper proposes a graph convolutional network (GCN)-based DRL approach that can employ the topological information of the network to take better control action for regulating the voltage. Our implementation allows for both centralized and decentralized configurations, utilizing a single agent and multiple agents respectively. Although the centralized GCN-based DRL approach has its advantages of minimizing voltage fluctuation and power loss, it is not suitable for large scale power systems due to its challenges in terms of scalability, computation speed and potential single points of failure. Therefore, these problems can be resolved using the decentralized GCN-based DRL approach. Moreover, to ensure the safe operation of the model, our proposed approach incorporates an exponential barrier function while formulating the reward function for each agent. To validate performance of the proposed approaches, the proposed model is tested on modified IEEE test systems and the performances are measured in terms on voltage fluctuation reduction, minimization of power loss and computational speed. Finally, the results show that the proposed topology-aware approach outperforms the FCN-based DRL approach in terms of reducing voltage fluctuation and minimizing power loss of the network. Moreover, it is shown that the decentralized GCN-based DRL has faster computational speed than other approaches.

42 ENGINEERING↗
DOE OSTI2022

How Well Does Kohn–Sham Regularizer Work for Weakly Correlated Systems?

Kohn–Sham regularizer (KSR) is a differentiable machine learning approach to finding the exchange-correlation functional in Kohn–Sham density functional theory that works for strongly correlated systems. Here we test KSR for a weak correlation. We propose spin-adapted KSR (sKSR) with trainable local, semilocal, and nonlocal approximations found by minimizing density and total energy loss. We assess the atoms-to-molecules generalizability by training on one-dimensional (1D) H, He, Li, Be, and Be 2+ and testing on 1D hydrogen chains, LiH, BeH 2 , and helium hydride complexes. The generalization error from our semilocal approximation is comparable to other differentiable approaches, but our nonlocal functional outperforms any existing machine learning functionals, predicting ground-state energies of test systems with a mean absolute error of 2.7 mH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Transcriptomic and metabolomic changes in postharvest sugarbeet roots reveal widespread metabolic changes in storage and identify genes potentially responsible for respiratory sucrose loss

Endogenous metabolism is primarily responsible for losses in sucrose content and processing quality in postharvest sugarbeet roots. The genes responsible for this metabolism and the transcriptional changes that regulate it, however, are largely unknown. To identify genes and metabolic pathways that participate in postharvest sugarbeet root metabolism and the transcriptional changes that contribute to their regulation, transcriptomic and metabolomic profiles were generated for sugarbeet roots at harvest and after 12, 40 and 120 d storage at 5 and 12°C and gene expression and metabolite concentration changes related to storage duration or temperature were identified. During storage, 8656 genes, or 34% of all expressed genes, and 225 metabolites, equivalent to 59% of detected metabolites, were altered in expression or concentration, indicating extensive transcriptional and metabolic changes in stored roots. These genes and metabolites contributed to a wide range of cellular and molecular functions, with carbohydrate metabolism being the function to which the greatest number of genes and metabolites classified. Because respiration has a central role in postharvest metabolism and is largely responsible for sucrose loss in sugarbeet roots, genes and metabolites involved in and correlated to respiration were identified. Seventy-five genes participating in respiration were differentially expressed during storage, including two bidirectional sugar transporter SWEET17 genes that highly correlated with respiration rate. Weighted gene co-expression network analysis identified 1896 additional genes that positively correlated with respiration rate and predicted a pyruvate kinase gene to be a central regulator or biomarker for respiration rate. Overall, these results reveal the extensive and diverse physiological and metabolic changes that occur in stored sugarbeet roots and identify genes with potential roles as regulators or biomarkers for respiratory sucrose loss.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Rational Design of Weakly‐Solvating Molecules for Salt‐In‐Pre‐Ionic‐Liquid Electrolytes for Li Metal Batteries

Lithium metal batteries (LMBs) promise step‐changes in energy densities but suffer from poor cycle life due to unstable electrolyte‐lithium interfaces. Conventional carbonate electrolytes exhibit excessive lithium‐ion solvation and low oxidative stability, leading to rapid capacity loss. Herein, we report a rationally designed weakly‐solvating cyclic sulfonamide, 1‐trifluoromethanesulfonyl)amide pyrrolidine (TFMSPyr), which integrates an electron‐withdrawing trifluoromethanesulfonyl functional group at pyrrolidinic‐N. TFMSPyr acts as a pre‐ionic‐liquid solvent that forms intrinsically localized, anion‐dominated solvation, coupling molecular architecture, solvation topology, and transport dynamics. As a result, LiFSI based salt‐in‐pre‐ionic‐liquid (SIPIL) electrolytes exhibit high lithium‐ion transference number, oxidative stability > 5 V versus Li/Li + and anion‐derived solid electrolyte interphases (SEI). Li||Cu cells with SIPIL deliver a first cycle Coulombic efficiency (CE) of ≈ 99% with average CE of 99.2% for 100 cycles, and lithium half‐cells with lithium iron phosphate (LFP) cathode exhibit 82% capacity retention after 400 cycles with CE of 99.98%. In anode‐free full cells, 95% of initial capacity is retained after 63 cycles with an average CE of 99.5%. These results demonstrate that molecular engineering of solvents offers a powerful pathway to stabilize lithium metal interfaces and enable practical Anodeless LMBs.

25 ENERGY STORAGE↗
DOE OSTI2025

Linking groundwater variability to ecosystem carbon and water use efficiencies across India

Carbon use efficiency (CUE) and water use efficiency (WUE) are important indicators of ecosystem health, reflecting the balance between carbon uptake and allocation, and the relationship between carbon assimilation and water loss. Although India shows large spatiotemporal variation in water table depth (WTD), and increasing groundwater stress, the influence of WTD on ecosystem functioning remains underexplored. This study uses satellite-based, modeled, and in-situ datasets to (1) quantify variations in CUE and WUE under shallow (SWTD) and deep (DWTD) WTD conditions across six homogeneous meteorological regions (HMRs), (2) evaluate temporal roles of gross primary productivity (GPP), net primary productivity (NPP), and evapotranspiration (ET) in driving these efficiencies, and (3) examine temporal responses to WTD shifts. SWTD regions generally showed 12 to 18 % higher GPP, 10 to 15 % higher NPP, and 10 to 20 % higher ET than DWTD zones, especially in semi-arid croplands and forests, leading to 8 to 12 % higher CUE and WUE. However, in humid and heavily irrigated regions such as northeastern and hilly India, CUE was up to 10 % higher in DWTD zones, possibly due to reduced respiration and better soil aeration compared to SWTD areas affected by waterlogging. During the Kharif (wet) season, DWTD croplands in humid zones had higher efficiencies, while in the Rabi (dry) season, SWTD croplands in northern India benefited from irrigation and cooler temperatures. These results highlight strong influence of WTD on carbon and water use processes and support the need for region-specific groundwater strategies.

Carbon use efficiency↗
DOE OSTI2024

A Eulerian three-fluid flow framework for the study of fuel dispersal behavior under loss-of-coolant accident conditions

As the nuclear industry explores new fuel designs to accommodate increased burnup, studying fuel behavior during loss-of-coolant accidents is essential for ensuring the safe operation of light-water reactors. Here, this study presents a computational model to simulate the intricate three-phase flow dynamics of fuel dispersal following cladding breach, where solid fuel particles and carrier fission gases interact with the surrounding liquid or gas medium. The model utilizes a Eulerian three-fluid framework to depict the phase interaction within interpenetrating continua, treating fragmented fuel as granular material. Closure relationships for bulk-flow properties of the solid phase and detailed interfacial exchange terms in high-temperature, high-speed gas-solid-liquid flow scenarios are proposed. The model was validated using adiabatic experimental results in the literature, focusing on characterizing fuel dispersal behavior during loss-of-coolant accidents conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched probability density functions reported in experimental studies. Key highlights of this study include the theoretical description of a coupled three-phase flow with phase change, interpretation of the high-pressure boundary conditions and insights into the transient behavior of gas-solid-liquid phase dynamics during a simulated high-speed dispersal event.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

A multiscale model to understand the interface chemistry, contacts, and dynamics during lithium stripping

A reversible Li-metal electrode, paired with a solid electrolyte, is critical for attaining higher energy density and safer batteries beyond the current lithium-ion cells. A stable stripping process may be even harder to attain as the stripping process will remove Li-atoms from the surface, and naturally reduce surface contact area, if not self-corrected by other mechanisms, such as diffusion and plastic deformation under an applied external stack pressure. Here, we capture these mechanisms occurring at multiple length- and time- scales, i.e., interface interactions, vacancy hopping, and plastic deformation, by integrating density functional theory (DFT) simulations, kinetic Monte Carlo (KMC), and continuum finite element method (FEM). By assuming the self-affine nature of multiscale contacts, we predict the steady-state contact area as a function of stripping current density, interface wettability, and stack pressure. We further estimate the exponential increase of overpotential due to contact area loss to maintain the same stripping current density. We demonstrate that a lithiophilic interface requires less stack pressure to reach the same steady-state contact area fraction than a lithiophobic interface. A “tolerable steady-state” contact area loss for maintaining stable stripping is estimated at 20 %, corresponding to a 10 % increase in overpotential. To constrain contact loss within the tolerance, the required stack pressure is 0.1, 0.5, and 2 times the yield strength of lithium metal for three distinct interfaces, lithiophilic Li/lithium oxide(Li2O), Li/lithium lanthanum zirconium oxide(LLZO), and lithiophoblic Li/lithium fluoride(LiF), respectively. The modeling results agree with experiments on the impact of the stack pressure quantitatively, while the discrepancy in stripping rate sensitivity is attributed to the simplifying interface interaction in our simulations. Overall, this multiscale simulation framework demonstrates the importance of electrochemical-mechanical coupling in understanding the dynamics of the Li/SE interface during stripping.

Feng, Min↗
DOE OSTI2020

Decoherence in Molecular Electron Spin Qubits: Insights from Quantum Many-Body Simulations

Quantum states are described by wave functions whose phases cannot be directly measured, but which play a vital role in quantum effects such as interference and entanglement. The loss of the relative phase information, termed decoherence, arises from the interactions between a quantum system and its environment. Decoherence is perhaps the biggest obstacle on the path to reliable quantum computing. Here we show that decoherence occurs even in an isolated molecule although not all phase information is lost via a theoretical study of a central electron spin qubit interacting with nearby nuclear spins in prototypical magnetic molecules. The residual coherence, which is molecule-dependent, provides a microscopic rationalization for the nuclear spin diffusion barrier proposed to explain experiments. The contribution of nearby molecules to the decoherence has a non-trivial dependence on separation, peaking at intermediate distances. Molecules that are far away only affect the long-time behavior. Because the residual coherence is simple to calculate and correlates well with the coherence time, it can be used as a descriptor for coherence in magnetic molecules. This work will help establish design principles for enhancing coherence in molecular spin qubits and serve to motivate further theoretical work

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Surface-Defect-Passivation-Enabled Near-Unity Charge Collection Efficiency in Bromide-Based Perovskite Gamma-Ray Spectrum Devices

Hybrid lead halide perovskites have superior charge transport properties to all-inorganic perovskites, but high-resolution spectroscopic radiation detectors have not been realized. Here we show that surface deep traps severely limit charge collection in formamidinium lead bromide (FAPbBr3) single-crystal devices, despite having a good bulk transport property. Three types of defect on the crystal surface, namely, FA vacancies, uncoordinated lead and Pb-Pb dimers caused by bromide loss, are found to form deep traps, resulting in non-radiative charge recombinations at the metal/perovskite interface. By tailoring the passivation functional groups, we find that ammonium bromide can passivate all these three deep traps on FAPbBr3 surfaces, improving the charge collection efficiency to near unity. The comparable bulk and surface recombination lifetimes indicate that all the surface defects are effectively passivated. Surface passivation also reduces the dark current by 10 times and decreases the dark counts by ~60 times. The energy resolution of the 137Cs spectra acquired using the FAPbBr3 detectors is improved from 5.7% to 1.7% when all the surface defects are passivated without changing the bulk properties, which is the best among solution-grown semiconductor detectors. Surface passivation is stable for more than six months, and FAPbBr3 spectroscopic detectors can operate at unprecedented high temperatures of more than 130 degrees C.

gamma ray↗