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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Isotope engineering for spin defects in van der Waals materials

Abstract Spin defects in van der Waals materials offer a promising platform for advancing quantum technologies. Here, we propose and demonstrate a powerful technique based on isotope engineering of host materials to significantly enhance the coherence properties of embedded spin defects. Focusing on the recently-discovered negatively charged boron vacancy center ($${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − ) in hexagonal boron nitride (hBN), we grow isotopically purified h 10 B 15 N crystals. Compared to$${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − in hBN with the natural distribution of isotopes, we observe substantially narrower and less crowded$${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − spin transitions as well as extended coherence timeT 2 and relaxation timeT 1 . For quantum sensing,$${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − centers in our h 10 B 15 N samples exhibit a factor of 4 (2) enhancement in DC (AC) magnetic field sensitivity. For additional quantum resources, the individual addressability of the$${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − hyperfine levels enables the dynamical polarization and coherent control of the three nearest-neighbor 15 N nuclear spins. Our results demonstrate the power of isotope engineering for enhancing the properties of quantum spin defects in hBN, and can be readily extended to improving spin qubits in a broad family of van der Waals materials.

Science & Technology - Other Topics↗
DOE OSTI2022

Correlated nanoelectronics and the second quantum revolution

The growing field of correlated nanoelectronics exists at the intersection of two established fields: correlated oxide electronics and semiconductor nanoelectronics. The development of quantum technologies that exploit quantum coherence and entanglement for the purposes of computation, simulation, and sensing will require complex material properties to be controlled at nanoscale dimensions. Heterostructures and nanostructures formed at the interface between LaAlO 3 and SrTiO 3 exhibit striking behavior that arises from the ability to program the conductive behavior at extreme nanoscale dimensions. The active electronic layer, SrTiO 3 , exhibits a wide range of gate-tunable phenomena such as ferroelectricity, ferroelasticity, magnetism, superconductivity, and spin–orbit coupling, all of which can be controlled at the nanoscale using two reversible methods: conductive atomic force microscope lithography and ultra-low-voltage electron beam lithography. Mesoscopic devices such as single-electron transistors and quasi-one-dimensional electron waveguides can be “sketched” using these techniques, and the properties of these devices differ significantly from those created from traditional semiconductors, such as Si or GaAs. The strongly correlated nature of the SrTiO 3 system is evident from superconducting behavior as well as a state in which electrons are paired outside the superconducting state. A highly exotic phase was discovered in which a degenerate quantum liquid is formed from bound states of n = 2, 3, 4, … electrons. Further development of correlated nanoelectronics based on the LaAlO 3 /SrTiO 3 system can potentially lead to a general platform for quantum simulation as well as a pathway for the development of highly entangled states of multiple photons.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Nanosynthesis by atmospheric arc discharges excited with pulsed-DC power: a review

Plasma technology is actively used for nanoparticle synthesis and modification. All plasma techniques share the ambition of providing high quality, nanostructured materials with full control over their crystalline state and functional properties. Pulsed-DC physical/chemical vapour deposition, high power impulse magnetron sputtering, and pulsed cathodic arc are consolidated low-temperature plasma processes for the synthesis of high-quality nanocomposite films in vacuum environment. However, atmospheric arc discharge stands out thanks to the high throughput, wide variety, and excellent quality of obtained stand-alone nanomaterials, mainly core–shell nanoparticles, transition metal dichalcogenide monolayers, and carbon-based nanostructures, like graphene and carbon nanotubes. Unique capabilities of this arc technique are due to its flexibility and wide range of plasma parameters achievable by modulation of the frequency, duty cycle, and amplitude of pulse waveform. The many possibilities offered by pulsed arc discharges applied on synthesis of low-dimensional materials are reviewed here. Periodical variations in temperature and density of the pulsing arc plasma enable nanosynthesis with a more rational use of the supplied power. Parameters such as plasma composition, consumed power, process stability, material properties, and economical aspects, are discussed. Lastly a brief outlook towards future tendencies of nanomaterial preparation is proposed. Atmospheric pulsed arcs constitute promising, clean processes providing ecological and sustainable development in the production of nanomaterials both in industry and research laboratories.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Record-Low Thermal Boundary Resistance between Diamond and GaN-on-SiC for Enabling Radiofrequency Device Cooling

The implementation of 5G-and-beyond networks requires faster, high-performance, and power-efficient semiconductor devices, which are only possible with materials that can support higher frequencies. Gallium nitride (GaN) power amplifiers are essential for 5G-and-beyond technologies since they provide the desired combination of high frequency and high power. These applications along with terrestrial hub and backhaul communications at high power output can present severe heat removal challenges. The cooling of GaN devices with diamond as the heat spreader has gained significant momentum since device self-heating limits GaN’s performance. However, one of the significant challenges in integrating polycrystalline diamond on GaN devices is maintaining the device performance while achieving a low diamond/GaN channel thermal boundary resistance. In this study, we achieved a record-low thermal boundary resistance of around 3.1 ± 0.7 m 2 K/GW at the diamond/Si 3 N 4 /GaN interface, which is the closest to theoretical prediction to date. The diamond was integrated within ~1 nm of the GaN channel layer without degrading the channel’s electrical behavior. Furthermore, we successfully minimized the residual stress in the diamond layer, enabling more isotropic polycrystalline diamond growth on GaN with thicknesses >2 μm and a ~1.9 μm lateral grain size. More isotropic grains can spread the heat in both vertical and lateral directions efficiently. Using transient thermoreflectance, the thermal conductivity of the grains was measured to be 638 ± 48 W/m K, which when combined with the record-low thermal boundary resistance makes it a leading-edge achievement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Joint impedance and facies inversion of time-lapse seismic data for improving monitoring of CO 2 incidentally stored from CO 2 EOR

Time-lapse seismic monitoring is an effective and proven technology for mapping the distribution of CO 2 in a subsurface reservoir. When injected CO 2 displaces other reservoir fluids, porous-medium properties are changed and thus the seismic impedance changes, causing time-lapse seismic amplitude differences in the injection zones. The analysis and interpretation of images created from these amplitude differences can provide information about reservoir architecture and the CO 2 migration within the reservoir. Incorporating seismic inversion and rock physics into the interpretation of time-lapse seismic data can considerably improve the modeling and monitoring to detect and assess the location of CO 2 over time. The joint inversion method presented in this paper has an integral representation of the geology in the inversion algorithm using elastic facies, which provides information about the spatial distribution of the geologic heterogeneities controlling the movement of fluids in the reservoir. The method was successfully applied to time-lapse seismic data from a mature oil field undergoing CO 2 enhanced oil recovery. The estimated seismic acoustic impedances and facies reflect the characteristics of individual geologic facies and fluid conditions of the reservoir subject to CO 2 injection. Finally, the probabilities estimated by the joint impedance and facies inversion for the reservoir's litho-fluid facies can be used for forecasting CO 2 saturation and pressure changes within the target reservoir.

4D seismic↗
DOE OSTI2026

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗
DOE OSTI2024

Electrochemical Conversion of CO 2 to Methyl Formate in a Flow Electrolyzer with Mixed Propylene Carbonate/Methanol Catholyte

Despite the promise of electrochemical carbon dioxide reduction as a technology for the production of clean fuels and decarbonization of the chemical industry, research has mostly focused on aqueous systems with a relatively limited set of products that have been achieved via electrosynthesis. Increasingly, CO 2 electroreduction in nonaqueous solvents is being pursued to develop new avenues for expanding the suite of products that can be made with high selectivity. CO 2 reduction in alcohols coupled with in situ esterification to produce esters is one such route that utilizes nonaqueous electrolyte. To be practical, such electrochemical syntheses need to be translated to a high-performance reactor such as a flow electrolyzer. However, many organic solvents, such as alcohols, wet and flood porous electrodes, thus impeding reactor performance. In this work, methanol was mixed with propylene carbonate as a catholyte for a gas-fed CO 2 flow electrolyzer that avoided cathode flooding. Simultaneously, a dual aqueous anolyte was used for water oxidation as a scalable and sustainable anodic half-reaction. The performance effect of methanol concentration, catholyte acidity, CO 2 flow rate, and dilute water in the catholyte were investigated. With 10 vol % methanol in 90 vol % propylene carbonate, 63% faradaic efficiency for methyl formate ester product was sustained without cathode flooding. However, improvements are still needed to lower the cell resistance and further increase the operating current density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

High-throughput printing of combinatorial materials from aerosols

The development of new materials and their compositional and microstructural optimization are essential in regard to next-generation technologies such as clean energy and environmental sustainability. However, materials discovery and optimization have been a frustratingly slow process. The Edisonian trial-and-error process is time consuming and resource inefficient, particularly when contrasted with vast materials design spaces 1 . Whereas traditional combinatorial deposition methods can generate material libraries 2,3 , these suffer from limited material options and inability to leverage major breakthroughs in nanomaterial synthesis. Here we report a high-throughput combinatorial printing method capable of fabricating materials with compositional gradients at microscale spatial resolution. In situ mixing and printing in the aerosol phase allows instantaneous tuning of the mixing ratio of a broad range of materials on the fly, which is an important feature unobtainable in conventional multimaterials printing using feedstocks in liquid–liquid or solid–solid phases 4–6 . We demonstrate a variety of high-throughput printing strategies and applications in combinatorial doping, functional grading and chemical reaction, enabling materials exploration of doped chalcogenides and compositionally graded materials with gradient properties. The ability to combine the top-down design freedom of additive manufacturing with bottom-up control over local material compositions promises the development of compositionally complex materials inaccessible via conventional manufacturing approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Sensitive Electrochemical Cholinesterase-Inhibiting Biosensor for Organophosphorus Pesticides Based on Ti 3 C 2 TX MXene Quantum Dots

Organophosphorus pesticides (OPs) pose significant environmental and health risks due to their widespread use and toxicity, primarily by inhibiting acetylcholinesterase. Traditional detection methods are often slow and costly, highlighting the urgent need for advanced, sensitive, and accessible technologies. This study developed a highly sensitive electrochemical cholinesterase-inhibiting biosensor for OP pesticides, utilizing Ti 3 C 2 T x MXene Quantum Dots (MQDs), which was synthesized via a hydrothermal method. The biosensor’s performance was characterized using electrochemical impedance spectroscopy, differential pulse voltammetry (DPV), and cyclic voltammetry. DPV proved to be the optimal technique, exhibiting an ultralow detection limit of 1 × 10 −17 M and a wide linear range (10 −14 –10 −8 M) for chlorpyrifos (a model OP) with an estimated inhibition constant of 62 nM. The biosensor demonstrated high selectivity for OPs (chlorpyrifos, acephate, glyphosate) over a non-target pyrethroid (permethrin), confirmed by distinct electrochemical signatures and compared to in vitro cholinergic activity assays in bean beetle homogenates. The enhanced performance is attributed to the high surface-to-volume ratio, quantum confinement effects, and superior conductivity of the MQDs, as well as the robust enzyme immobilization facilitated by glutaraldehyde cross-linking and a chitosan matrix. This work presents a promising platform for rapid, sensitive, and selective detection of OP pesticides, with potential applications in environmental monitoring and public health protection.

Chemistry↗
DOE OSTI2024

Future of plasma etching for microelectronics: Challenges and opportunities

Plasma etching is an essential semiconductor manufacturing technology required to enable the current microelectronics industry. Along with lithographic patterning, thin-film formation methods, and others, plasma etching has dynamically evolved to meet the exponentially growing demands of the microelectronics industry that enables modern society. At this time, plasma etching faces a period of unprecedented changes owing to numerous factors, including aggressive transition to three-dimensional (3D) device architectures, process precision approaching atomic-scale critical dimensions, introduction of new materials, fundamental silicon device limits, and parallel evolution of post-CMOS approaches. The vast growth of the microelectronics industry has emphasized its role in addressing major societal challenges, including questions on the sustainability of the associated energy use, semiconductor manufacturing related emissions of greenhouse gases, and others. The goal of this article is to help both define the challenges for plasma etching and point out effective plasma etching technology options that may play essential roles in defining microelectronics manufacturing in the future. The challenges are accompanied by significant new opportunities, including integrating experiments with various computational approaches such as machine learning/artificial intelligence and progress in computational approaches, including the realization of digital twins of physical etch chambers through hybrid/coupled models. These prospects can enable innovative solutions to problems that were not available during the past 50 years of plasma etch development in the microelectronics industry. To elaborate on these perspectives, the present article brings together the views of various experts on the different topics that will shape plasma etching for microelectronics manufacturing of the future.

Engineering↗
DOE OSTI2023

Performance of methods for SARS-CoV-2 variant detection and abundance estimation within mixed population samples

The accurate identification of SARS-CoV-2 (SC2) variants and estimation of their abundance in mixed population samples (e.g., air or wastewater) is imperative for successful surveillance of community level trends. Assessing the performance of SC2 variant composition estimators (VCEs) should improve our confidence in public health decision making. Here, we introduce a linear regression based VCE and compare its performance to four other VCEs: two re-purposed DNA sequence read classifiers (Kallisto and Kraken2), a maximum-likelihood based method (Lineage deComposition for Sars-Cov-2 pooled samples (LCS)), and a regression based method (Freyja). We simulated DNA sequence datasets of known variant composition from both Illumina and Oxford Nanopore Technologies (ONT) platforms and assessed the performance of each VCE. We also evaluated VCEs performance using publicly available empirical wastewater samples collected for SC2 surveillance efforts. Bioinformatic analyses were performed with a custom NextFlow workflow (C-WAP, CFSAN Wastewater Analysis Pipeline). Relative root mean squared error (RRMSE) was used as a measure of performance with respect to the known abundance and concordance correlation coefficient (CCC) was used to measure agreement between pairs of estimators. Based on our results from simulated data, Kallisto was the most accurate estimator as it had the lowest RRMSE, followed by Freyja. Kallisto and Freyja had the most similar predictions, reflected by the highest CCC metrics. We also found that accuracy was platform and amplicon panel dependent. For example, the accuracy of Freyja was significantly higher with Illumina data compared to ONT data; performance of Kallisto was best with ARTICv4. However, when analyzing empirical data there was poor agreement among methods and variations in the number of variants detected (e.g., Freyja ARTICv4 had a mean of 2.2 variants while Kallisto ARTICv4 had a mean of 10.1 variants). This work provides an understanding of the differences in performance of a number of VCEs and how accurate they are in capturing the relative abundance of SC2 variants within a mixed sample (e.g., wastewater). Such information should help officials gauge the confidence they can have in such data for informing public health decisions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Melt Processing Pretreatment Effects on Enzymatic Depolymerization of Poly(ethylene terephthalate)

Poly(ethylene terephthalate) (PET) is a common thermoplastic material, used in a wide variety of applications (i.e., bottles, fabrics, packaging, electronics, and automotive components). Increasing demand for PET has precipitated a need for improved recycling technology, especially for single-use PET waste. Recently, enzymatic depolymerization has shown promise as an environmentally responsible alternative for PET chemical recycling that yields economically useful products (e.g., terephthalic acid, adipic acid, and ethylene glycol). However, the depolymerization system still suffers from low rates on crystalline PET substrates, and effects of realistic waste streams are not known. In our work, PET waste is pretreated using an ultra-high-speed twin-screw extruder system. PET substrates were modified by various processing pretreatments to allow enzymes better access to depolymerize substrate materials. The effect of varying throughput and mechanical shear on structural properties of the PET waste was analyzed using molecular weight and thermal characterizations. These pretreated samples exhibit modifications in molecular weight, glass transition temperature, crystallinity, and specific surface area. The unpurified leaf-branch compost cutinase enzyme produced from the fed-batch fermentation of Escherichia coli BL21(DE3) was used in enzymatic depolymerization, where a faster reaction was observed as crystallinity was decreased and the specific surface area was increased. The rate of terephthalic acid production was also significantly higher for samples processed at lower mechanical shear with higher throughputs. As a result, this work demonstrates the potential for tailoring pretreatments in pursuit of faster and more energy efficient PET recycling using enzymes, with facile adaptation to the industrial scale for the circular economy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Shock-induced chemical decomposition and overdriven detonation in hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) single crystals

Understanding the differences in the shock compression and detonation response of insensitive high explosives (IHEs) and conventional HEs (CHEs) is a long-standing need in HE science and technology. Having previously examined 1,1-diamino-2,2-dinitroethene (FOX-7) IHE single crystals, the shock and detonation response of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX)—a widely used CHE—was determined using wave profile measurements in ~250 μm thick single crystals shock compressed to 63 GPa. In marked contrast to FOX-7, RDX single crystals shocked along the [100] and [111] orientations showed wave profile features consistent with chemical decomposition onset at 15 GPa. These features were more pronounced for [100] RDX, suggesting a higher decomposition rate compared to [111] RDX. At 51 GPa and above, flat-topped single waves were observed for both orientations, showing the classic Chapman–Jouget (C–J) detonation response in which the decomposition is completed within the detonation front. The Hugoniot states and sound speeds determined for the detonation products were similar for both [100] and [111] orientations, showing that the overdriven detonation response for RDX does not depend on crystal orientation. The C–J pressure for RDX single crystals (35 GPa)—determined experimentally—is comparable to that of FOX-7. However, compared to FOX-7, chemical decomposition onset for RDX occurs at much lower pressures and the overdriven C–J detonation response occurs at higher pressures. Lastly, the present findings constitute the first experimental comparison of the shock and detonation response of conventional and insensitive HE single crystals over a broad pressure range below and above the C–J pressure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Machine learning the electric field response of condensed phase systems using perturbed neural network potentials

Abstract The interaction of condensed phase systems with external electric fields is of major importance in a myriad of processes in nature and technology, ranging from the field-directed motion of cells (galvanotaxis), to geochemistry and the formation of ice phases on planets, to field-directed chemical catalysis and energy storage and conversion systems including supercapacitors, batteries and solar cells. Molecular simulation in the presence of electric fields would give important atomistic insight into these processes but applications of the most accurate methods such as ab-initio molecular dynamics (AIMD) are limited in scope by their computational expense. Here we introduce Perturbed Neural Network Potential Molecular Dynamics (PNNP MD) to push back the accessible time and length scales of such simulations. We demonstrate that important dielectric properties of liquid water including the field-induced relaxation dynamics, the dielectric constant and the field-dependent IR spectrum can be machine learned up to surprisingly high field strengths of about 0.2 V Å −1 without loss in accuracy when compared to ab-initio molecular dynamics. This is remarkable because, in contrast to most previous approaches, the two neural networks on which PNNP MD is based are exclusively trained on molecular configurations sampled from zero-field MD simulations, demonstrating that the networks not only interpolate but also reliably extrapolate the field response. PNNP MD is based on rigorous theory yet it is simple, general, modular, and systematically improvable allowing us to obtain atomistic insight into the interaction of a wide range of condensed phase systems with external electric fields.

Science & Technology - Other Topics↗
DOE OSTI2021

UiO-66 Metal–Organic Framework as an Anode for a Potassium-Ion Battery: Quantum Mechanical Analysis

The natural abundance of potassium in the earth’s crust is 1000 times higher than that of lithium, so energy technologies built on potassium are more sustainable. Potassium-ion batteries have attracted considerable attention because of their relatively low cost and high operating potential, but questions remain about the best anode material for such batteries. Here, in this paper, we report first-principles computations based on density functional theory to investigate the performance of the UiO-66 metal–organic framework as an anode material for potassium-ion batteries; the goal is to provide a fundamental understanding of metal–organic framework (MOF)-based electrodes to guide the design and development of high-performance potassium-ion batteries. Our study includes the stability and electronic properties of potassiated structures and the mechanisms of potassium intercalation and diffusion in the framework. The results indicate that UiO-66 has a maximum specific capacity of 644 mAh/g as the anode of a potassium-ion battery. During potassiation, we observe charge transfer from potassium to carbon or oxygen of UiO-66 near the intercalated K. During K diffusion, the K migrates along the UiO-66 framework with a maximal migration energy barrier of 0.377 eV in the optimal pathway, which is much lower than the barriers for Li and Na diffusion in UiO-66. The diffusion coefficient of K in the anode is several orders of magnitude larger than those of Li and Na. This favors potassium ions over lithium ions or sodium ions when UiO-66 is the anode.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Discovery and characterization of an acridine radical photoreductant

Not provided.Photoinduced electron transfer (PET) is a phenomenon whereby the absorption of light by a chemical species provides an energetic driving force for an electron-transfer reaction. This mechanism is relevant in many areas of chemistry, including the study of natural and artificial photosynthesis, photovoltaics and photosensitive materials. In recent years, research in the area of photoredox catalysis has enabled the use of PET for the catalytic generation of both neutral and charged organic free-radical species. These technologies have enabled previously inaccessible chemical transformations and have been widely used in both academic and industrial settings. Such reactions are often catalysed by visible-light-absorbing organic molecules or transition-metal complexes of ruthenium, iridium, chromium or copper. Although various closed-shell organic molecules have been shown to behave as competent electron-transfer catalysts in photoredox reactions, there are only limited reports of PET reactions involving neutral organic radicals as excited-state donors or acceptors. This is unsurprising because the lifetimes of doublet excited states of neutral organic radicals are typically several orders of magnitude shorter than the singlet lifetimes of known transition-metal photoredox catalysts. Here we document the discovery, characterization and reactivity of a neutral acridine radical with a maximum excited-state oxidation potential of -3.36 volts versus a saturated calomel electrode, which is similarly reducing to elemental lithium, making this radical one of the most potent chemical reductants reported. Spectroscopic, computational and chemical studies indicate that the formation of a twisted intramolecular charge-transfer species enables the population of higher-energy doublet excited states, leading to the observed potent photoreducing behaviour. Finally, we demonstrate that this catalytically generated PET catalyst facilitates several chemical reactions that typically require alkali metal reductants and can be used in other organic transformations that require dissolving metal reductants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Tritium generation, release, and retention from in-core fluoride salt irradiations

Further understanding of tritium transport mechanisms in the combined molten fluoride salt and graphite environment is necessary for the design and licensing of a Fluoride-Salt-Cooled High-Temperature Reactor (FHR). The three in-core fluoride salt irradiations completed at the Massachusetts Institute of Technology Reactor (MITR) are a useful parallel for studying transport phenomena expected in a FHR environment. During the irradiations, evolution of tritium from the flibe salt was monitored and compared to the calculated total generation rate. A difference of 22 ± 10% between the integrated calculated tritium generation rate and the total release was measured for the third MITR irradiation (FS-3). The fraction of tritium which was not released from the salt could be explained by tritium retention in graphite. Additionally, for post irradiation examination, a thermal desorption furnace was used to heat nuclear graphite samples in order to release and measure retained tritium. The desorption analysis in this work utilized seven subsections of graphite from the second salt irradiation (FS-2); three from a disc of IG-110U and four from ARB matrix graphite. Observed desorption versus temperature as well as total tritium content in the samples after irradiation indicate that the graphites were not volumetrically saturated with tritium, but rather tritium retention was likely limited to the near-surface region. Measurements of the samples resulted in 2.90 ± 0.29 μCi/mm 2 of tritium retained by IG-110U and 1.83 ± 0.31 μCi/mm 2 for ARB during the 300 h FS-2 in-core irradiation. Based on the desorption measurements, the estimated total tritium retention in graphite from the FS-2 samples is consistent with the tritium release measurements from the FS-3 experiment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Harvesting electrons and holes from photodriven symmetry-breaking charge separation within a perylenediimide photosynthetic model dimer

Understanding how to utilize symmetry-breaking charge separation (SB-CS) offers a path toward increasingly efficient light-harvesting technologies. This process plays a central role in the first step of photosynthesis, in which the dimeric “special pair” of the photosynthetic reaction center enters a coherent SB-CS state after photoexcitation. Previous research on SB-CS in both biological and synthetic chromophore dimers has focused on increasing the efficiency of light-driven processes. In a chromophore dimer undergoing SB-CS, the energy of the radical ion pair product is nearly isoenergetic with that of the lowest excited singlet (S 1 ) state of the dimer. This means that very little energy is lost from the absorbed photon. In principle, the relatively high energy electron and hole generated by SB-CS within the chromophore dimer can each be transferred to adjacent charge acceptors to extend the lifetime of the electron–hole pair, which can increase the efficiency of solar energy conversion. To investigate this possibility, we have designed a bis-perylenediimide cyclophane (mPDI 2 ) covalently linked to a secondary electron donor, peri-xanthenoxanthene (PXX) and a secondary electron acceptor, partially fluorinated naphthalenediimide (FNDI). Upon selective photoexcitation of mPDI 2 , transient absorption spectroscopy shows that mPDI 2 undergoes SB-CS, followed by two secondary charge transfer reactions to generate a PXX •+ -mPDI 2 -FNDI •– radical ion pair having a nearly 3 µs lifetime. In conclusion, this strategy has the potential to increase the efficiency of molecular systems for artificial photosynthesis and photovoltaics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗