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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Full Counting Statistics of Charge in Chaotic Many-Body Quantum Systems

We investigate the full counting statistics of charge transport in U(1)-symmetric random unitary circuits. We consider an initial mixed state prepared with a chemical potential imbalance between the left and right halves of the system and study the fluctuations of the charge transferred across the central bond in typical circuits. Using an effective replica statistical mechanics model and a mapping onto an emergent classical stochastic process valid at large on-site Hilbert space dimension, we show that charge transfer fluctuations approach those of the symmetric exclusion process at long times, with subleading t –1/2 quantum corrections. Here, we discuss our results in the context of fluctuating hydrodynamics and macroscopic fluctuation theory of classical nonequilibrium systems and check our predictions against direct matrix-product state calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Haze Mitigation in High-Resolution Satellite Imagery using Enhanced Style-Transfer Neural Network and Normalization Across Multiple GPUs

Despite recent advances in deep learning approaches, haze mitigation in large satellite images is still a challenging problem. Due to amorphous nature of haze, object detection or image segmentation approaches are not applicable. Also it is practically infeasible to obtain ground truths for training. Bounded memory capacity of GPUs is another constraint that limits the size of image to be processed. In this paper, we propose a style transfer based neural network approach to mitigate haze in a large overhead imagery. The network is trained without paired ground truths; further, perception loss is added to restore vivid colors, enhance contrast and minimize artifacts. The paper also illustrates our use of multiple GPUs in a collective way to produce a single coherent clear image where each GPU dehazes different portions of a large hazy image.

Park, Byung↗
DOE OSTI2024

Endothermic Charge Separation Occurs Spontaneously in Non–Fullerene Acceptor/Polymer Bulk Heterojunction

Organic photovoltaics (OPVs) based on non-fullerene acceptors (NFAs) have achieved a power conversion efficiency close to 20%. These NFA OPVs can generate free carriers efficiently despite a very small energy level offset at the donor/acceptor interface. Why these NFAs can enable efficient charge separation (CS) with low energy losses remains an open question. Here, the CS process in the PM6:Y6 bulk heterojunction is probed by time-resolved two-photon photoemission spectroscopy. It is found that the CS, the conversion from bound charge transfer (CT) excitons to free carriers, is an endothermic process with an enthalpy barrier of 0.15 eV. The CS can occur spontaneously despite being an endothermic process, which implies that it is driven by entropy. It is further argued that the morphology of the PM6:Y6 film and the anisotropic electron delocalization restrict the electron and hole wavefunctions within the CT exciton such that they can primarily contact each other through point-like junctions. Furthermore, this configuration can maximize the entropic driving force.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Investigation of Ga 2 O 3 as a new transparent conductive oxide for photovoltaics applications

This small innovation project intended to leverage recent activity and advances in ultrawide-bandgap oxide power electronics toward the investigation of Ga 2 O 3 as a transparent conductive oxide (TCO) for use in photovoltaics (PV). Ga 2 O 3 ’s theoretical advantage over incumbent TCOs is its very large bandgap of 4.8 eV, ensuring optical transparency of photons with λ ≥ 260 nm, effectively the full terrestrial solar spectrum. At the time of proposal writing, literature on Ga 2 O 3 as a TCO/optical material was relatively sparse — what little existed was focused on for UV sensors and/or emitters, with none related to PV. As such, this project was intended to help determine the potential of Ga 2 O 3 as a PV-oriented TCO by investigating its deposition using tools common to the PV and electronics industries — atomic layer deposition (ALD) and RF sputtering (RS), both of which are already used in PV manufacturing — and its resultant optical and electronic properties. Final project goals were to test its application to Si and III-V solar cells. Controllable film thickness and excellent uniformity was established for both methods deposition methods, with ALD providing higher precision for thinner films and RS more effective for growing thicker films. The as-deposited films were found to be amorphous in nature. Spectroscopic ellipsometry (SE) confirmed bandgaps of at least 4.8 eV and non-parasitic absorption across both AM0 and AM1.5G spectra; a refractive index approaching the expected value of 1.8 was also observed, with some degree of tunability based on process parameters. Using this initial optical data, a transfer matrix model, which interfaces with in-house EQE and LIV models, was developed to simulate Ga 2 O 3 optical effects on various solar cells, included potential in antireflection coatings (ARCs). Despite promising optical properties, the resultant resistivity / conductivity metrics did not meet expectations, regardless of deposition process. Although thick RS-deposited films, using both undoped and 1 at% Ge (n-type) doped sintered targets — demonstrated high net carrier concentrations (via C-V), and low specific resistance Ohmic contacts were demonstrated, transmission line measurements (TLM) showed very high resistivity. Further analysis indicated high vertical film conductivity, but very low lateral conductivity. Deeper characterization revealed a relatively high density of nano/microcrystalline inclusions that were ostensibly the source of the vertical conductivity, with the amorphous matrix serving as an effective insulator (likely due to high concentrations of electronic trap states). Despite extensive work to increase film polycrystallinity — demonstrated via high temperature annealing — sufficient lateral conductivity for TCO use was not achieved. The final phase of the project shifted focus toward investigation of ALD-deposited Ga 2 O 3 ’s potential as a passivant and/or passivating contact for both Si and III-V solar cells, with expectation of performance similar to Al 2 O 3 . However, initial rounds of testing using our baseline ALD process yielded minimal (but not quite zero) passivation of both GaInP and Si surfaces. Dielectric passivation is well-known to be highly process sensitive; given the unoptimized nature of the process used, this work was deemed inconclusive. The final outlook with respect to feasibility of Ga 2 O 3 as a PV-oriented TCO is, ultimately, still uncertain. The work performed in this project confirmed the optical properties and deposition methods, but the achieved electrical properties do not meet technological needs; literature reports in recent years are somewhat inconsistent and potentially untrustworthy, but generally appear to be in line with our results. At the very least it is clear that, should Ga 2 O 3 still be under consideration for PV TCO and/or selective contact applications, a significant amount of optimization and study is still needed.

14 SOLAR ENERGY↗
DOE OSTI2020

Improving collaborations between empiricists and modelers to advance grassland community dynamics in ecosystem models

Climate change, increasing atmospheric CO 2 , and land use change have altered biogeochemical and hydrologic cycles world-wide, with grassland systems being particularly vulnerable to resulting vegetation shifts (Komatsu et al., 2019). Therefore, incorporating plant community dynamics into ecosystem models is critical for accurate forecasting of ecosystem responses to global change (Levine, 2016). Process-based ecosystem models, which simulate the biogeochemical transfers of mass and energy among biota, the subsurface, and atmosphere, require representation of dynamic composition of organisms within ecosystems. For example, these models simulate leaf and plant-level characteristics, such as electron transport rate and allometry of carbon (C) allocation, to predict how net primary productivity and other ecosystem processes respond to abiotic drivers. These models are particularly useful in scaling from organismal to ecosystem levels but are still underdeveloped in their ability to capture community change, especially in grassland ecosystems. To represent compositional changes, these models must simulate competition, mortality, establishment, and reproduction of plant populations within communities. Yet, current ecosystem modeling approaches to forecast plant community change have derived from studies of forested systems and are either too coarse to capture fine-scale community dynamics (e.g. dynamic global vegetation models (DGVMs)) or too complex to be used at large spatial scales (e.g. forest gap models).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Unraveling Triplet Formation Mechanisms in Acenothiophene Chromophores

The evolution of molecular platforms for singlet fission (SF) chromophores has fueled the quest for new compounds capable of generating triplets quantitatively at fast time scales. As the exploration of molecular motifs for SF has diversified, a key challenge has emerged in identifying when the criteria for SF have been satisfied. Here, we show how covalently bound molecular dimers uniquely provide a set of characteristic optical markers that can be used to distinguish triplet pair formation from processes that generate an individual triplet. These markers are contained within (i) triplet charge-transfer excited state absorption features, (ii) kinetic signatures of triplet-triplet annihilation processes, and (iii) the modulation of triplet formation rates using bridging moieties between chromophores. Our assignments are verified by time-resolved electron paramagnetic resonance (EPR) measurements, which directly identify triplet pairs by their electron spin and polarization patterns. Here we apply these diagnostic criteria to dimers of acenothiophene derivatives in solution that were recently reported to undergo efficient intermolecular SF in condensed media. While the electronic structure of these heteroatom-containing chromophores can be broadly tuned, the effect of their enhanced spin-orbit coupling and low-energy nonbonding orbitals on their SF dynamics has not been fully determined. We find that SF is fast and efficient in tetracenothiophene but that anthradithiophene exhibits fast intersystem crossing due to modifications of the singlet and triplet excited state energies upon functionalization of the heterocycle. We conclude that it is not sufficient to assign SF based on comparisons of the triplet formation kinetics between monomer and multichromophore systems.

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

Degradable Biocomposite Thermoplastic Polyurethanes

In this project, the team developed tough and degradable biocomposite thermoplastic polyurethanes (TPUs) by incorporating bacterial spores into TPUs as a biofunctional living filler. The team screened various bacteria and selected the Bacillus subtilis ATCC 6633 strain as the final candidate, primarily due to its genomic availability, sporulation ability and TPU assimilation activity. The heat-shock tolerance of ATCC 6633 spores was further improved through evolutionary engineering via Adaptive Laboratory Evolution (ALE), demonstrating a 17.7-fold enhanced germination efficiency post heat-shock treatment compared to the wild-type strain (WT). The team fabricated biocomposite TPUs by incorporating lyophilized powder of heat-shock tolerized (HST) spores during the hot melt extrusion (HME) of TPU at 135 °C. The baseline TPU used in this project is a commercially available soft-grade TPU (BCF45) manufactured by BASF. Colony forming unit (CFU) assays quantified that WT and HST spores in the TPU matrix retained approximately 20% and 100% survivability, respectively, after HME. Tensile testing demonstrated that the spores behaved as a polymer-reinforcing filler, positively affecting the overall tensile properties of the biocomposite TPU. For example, biocomposite TPU with WT and HST spores (BC TPU WT and BC TPU HST , respectively) exhibited up to 25% and 37% improved toughness, respectively, compared to TPU without spores. BC TPU HST showed remarkably improved disintegration in autoclaved compost (92% mass loss in 5 months), which simulated a microbially poor environment for TPU degradation. When compared to TPU without spores (44% mass loss in 5 months) the acceleration of degradation is marked. Respirometry confirmed that 72% of BC TPU HST was biomineralized into CO2 within 6 months, indicating that spores in the biocomposite TPU were germinated by utilizing nutrients in the autoclaved compost, facilitating TPU degradation at the end of the material's life. The team demonstrated the scale-up of biocomposite TPU fabrication using continuous extrusion and injection molding techniques. Processing conditions optimized in a lab-scale microcompounder were successfully transferred to a continuous extruder with a 30-fold increased throughput. Biocomposite TPUs prepared using these industry-relevant processes showed comparable toughness improvements to samples prepared in the lab-scale extruder. Excitingly, following compounding in the pilot-extruder the composite material could be injection molded, while retaining high spore viability and similar toughness improvements. The team also found that spores in biocomposite TPU served as antioxidants, preventing toughness decay during the recycled extrusion of BC TPU HST . Long-term storage tests over one year showed that the addition of spores had no negative effect on the longevity of the TPU. Furthermore, the team demonstrated the fabrication of spore-bearing biocomposite polymers with other polyesters such as PBAT, PLA, and PCL. We obtained promising preliminary data that showed overall toughness improvements for all polymers with spore addition. Finally, life cycle assessment (LCA) and techno-economic analysis (TEA) were carried out, which indicated minimal additional cost of fabrication. Overall, a tough and degradable biocomposite thermoplastic was successfully developed through this project, with all tasks completed successfully, achieving >100% of the objectives.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Power System Event Identification with Transfer Learning Using Large-scale Real-world Synchrophasor Data in the United States

The lack of sufficient labeled events and long training time limit the applicability of deep neural network-based power system event identification using synchrophasor data. In this paper, we propose to leverage transfer learning technique to boost the reliability and reduce the required training time of neural classifier for power system event identification. We use the weights of a neural classifier trained on one transmission system as the initial parameters of another neural classifier for a different transmission system. Numerical tests with real-world synchrophasor data from the Eastern and Western Interconnections of the United States show that the proposed transfer learning approach is very effective in not only improving the training reliability but also reducing the training time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Controlled Dedoping and Redoping of N‐Doped Poly(benzodifurandione) (n‐PBDF)

Abstract The doping levels of conjugated polymers significantly influence their conductivity, energetics, and optical properties. Recently, a highly conductive n‐doped polymer called poly (3,7‐dihydrobenzo[1,2‐b:4,5‐b′]difuran‐2,6‐dione) (poly(benzodifurandione), n‐PBDF) is discovered, opening new possibilities for n‐type conducting polymers in printed electronics and other fields. Controlling the doping level of n‐PBDF is of great interest due to its wide range of potential applications. Here controlled dedoping and redoping of n‐PBDF is reported and a mechanistic understating of such a process is provided. Dedoping occurs through electron transfer and proton capture, wherein the ionic dopants, tris(4‐bromophenyl)ammoniumyl hexachloroantimonate (Magic Blue), exhibit efficient proton capture ability and stronger interaction with n‐PBDF, resulting in high dedoping efficiency. Moreover, chemically dedoped PBDF can be redoped using various proton‐coupled electron transfer agents. By manipulating the doping levels of n‐PBDF thin films, ranging from highly doped to dedoped states, the system demonstrates controllable conductivity in five orders of magnitude, adjustable optical properties, and energetics. As a result, these characteristics demonstrate the potential applications of n‐PBDF in organic electrochemical transistors and thermoelectrics.

Chemistry↗
DOE OSTI2024

Interfacially Enhanced Superconductivity in Fe(Te,Se)/Bi 4 Te 3 Heterostructures

Realizing topological superconductivity by integrating high-transition-temperature (T C ) superconductors with topological insulators can open new paths for quantum computing applications. Here, a new approach is reported for increasing the superconducting transition temperature $T^{onset}_C$ by interfacing the unconventional superconductor Fe(Te,Se) with the topological insulator Bi–Te system in the low-Se doping regime, near where superconductivity vanishes in the bulk. The critical finding is that the $T^{onset}_C$ of Fe(Te,Se) increases from nominally non-superconducting to as high as 12.5 K when Bi 2 Te3 is replaced with the topological phase Bi 4 Te 3 . Interfacing Fe(Te,Se) with Bi4Te3 is also found to be critical for stabilizing superconductivity in monolayer films where $T^{onset}_C$ can be as high as 6 K. Measurements of the electronic and crystalline structure of the Bi 4 Te 3 layer reveal that a large electron transfer, epitaxial strain, and novel chemical reduction processes are critical factors for the enhancement of superconductivity. This novel route for enhancing T C in an important epitaxial system provides new insight on the nature of interfacial superconductivity and a platform to identify and utilize new electronic phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A Computational Information Criterion for Particle-Tracking with Sparse or Noisy Data

Traditional probabilistic methods for the simulation of advection-diffusion equations (ADEs) often overlook the entropic contribution of the discretization, e.g., the number of particles, within associated numerical methods. Many times, the gain in accuracy of a highly discretized numerical model is outweighed by its associated computational costs or the noise within the data. Herein, we address the question of how many particles are needed in a simulation to best approximate and estimate parameters in one-dimensional advective-diffusive transport. To do so, we use the well-known Akaike Information Criterion (AIC) and a recently-developed correction called the Computational Information Criterion (COMIC) to guide the model selection process. Random-walk and mass-transfer particle tracking methods are employed to solve the model equations at various levels of discretization. Numerical results demonstrate that the COMIC provides an optimal number of particles that can describe a more efficient model in terms of parameter estimation and model prediction compared to the model selected by the AIC even when the data is sparse or noisy, the sampling volume is not uniform throughout the physical domain, or the error distribution of the data is non-IID Gaussian.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A novel lung-inspired 3D-printed desiccant-coated heat exchanger for high-performance humidity management in buildings

Offering an independent humidity management method for buildings, desiccant-coated heat exchangers (DCHXs) are deemed a promising approach to improve the overall energy efficiency of air conditioning (AC) systems. State-of-the-art DCHXs, however, are bound with conventional HX topologies either providing limited desiccant-air interfacial areas or introducing excessive pressure drop penalties. In this paper a novel 3D-printed DCHX concept inspired by the bronchi arrangement of a human lung is introduced to address the shortcomings inherent in existing DCHX designs. The proposed lung-inspired DCHX utilizes two intertwined bicontinuous flow networks enabling highly efficient heat and mass transfer characteristics for augmented adsorption and regeneration processes at low pressure drop penalties. While the first network evenly distributes an incoming air stream through the entire volume of the lung-inspired DCHX, the second network volumetrically splits a cooling water stream within and through the first network. Effects of various parameters including air flow rate, outdoor air humidity ratio, and regeneration temperature on dehumidification performance and energy efficiency of the proposed lung-inspired DCHX were investigated. Experimental results indicated the proposed lung-inspired 3D-printed DCHX outperforms existing DCHX systems by demonstrating an excellent balance between a high volumetric adsorption rate and a low pressure drop penalty. The volumetric adsorption rate of the proposed lung-inspired DCHX technology is 54.8 g/m 3 -s, a more than two-fold improvement compared with state-of-the-art DCHX systems. Additionally, the lung-inspired DCHX offers high thermal energy efficiency of 56% at a low regeneration temperature of 40 °C. Therefore, the proposed lung-inspired 3D-printed DCHX offers a new solid-desiccant-based air dehumidification pathway for next-generation high-performance AC systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Quantitative and three-dimensional assessment of holdup material

Nuclear material deposited in equipment, transfer lines, and ventilation systems of a processing facility is usually referred to as holdup. Operators need to know the location and amount of holdup in their facility for radiation safety and material accountability. In this work, we propose to use an array of detectors co-axial to the inspected pipe to measure the holdup material. This method is implementable into an automated system capable of crawling on surfaces and pipes of various curvatures, which would enable faster, easier, and more accurate holdup safeguards measurements. We first demonstrated that the current holdup assay procedure could lead to a non-negligible bias in the estimate of special nuclear material mass, due to the simplified assumption of deposited geometry introduced by the Generalized Geometry Holdup (GGH) model. The new approach consists of imaging the inner holdup material by characterizing the detector array’s response and unfolding it from the measured light output. Our experimental proof of principle consists of three NaI(Tl) detectors surrounding an aluminum pipe containing two cesium-137 ( 137 Cs) sources. We derived the source distribution inside the pipe by first calculating the detector response matrix using a method adaptive to the surface geometry of the object containing the measured holdup material. Creating a matrix of the detector array’s measured counts, we then proceed to solve an inverse problem, resulting in an accurately located source position and activity distribution within the response matrix’s spatial resolution. Furthermore, we then developed a simulated model of the envisioned experimental setup, which accurately described both the activity and position of the source in 2D. Finally, we extended our model onto a discretized three-dimensional model of the system, encompassing 36 detectors. The model was simulated to measure the source distribution and activity of multiple sources in pipes of varied geometries, which could then be conveniently translated to a real-time holdup measurement protocol. For the 3D simulation of four different source geometries, the model accurately localized the source position in 3D, while the activity retained a maximum relative error of ±5.32%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Aqueous Interfaces in Chemical Separations

Chemical separations play a vital role in refinery and reprocessing of critical materials, such as platinum group metals, rare earths, and actinides. The choice of separation system─whether it is liquid–liquid extraction (LLE), sorbents, or membranes─depends on specific needs and applications. In almost all separation processes, the desired metal ions adsorb or transfer across an aqueous interface, such as the solid/liquid interface in sorbents or oil/water interfaces in LLE. Despite these separation technologies being extensively used for decades, our understanding of the molecular-scale mechanisms governing ion adsorption and transport at interfaces remains limited. This knowledge gap presents a significant challenge in meeting the increasing demands for these critical materials due to their growing use in advanced technologies. Fortunately, recent advancements in surface-specific experimental and computational techniques offer promising avenues to bridge this gap and facilitate the development of next-generation separation systems. Interestingly, unanswered questions regarding interfacial phenomena in chemical separations hold great relevance to various fields, including energy storage, geochemistry, and atmospheric chemistry. Therefore, the model interfacial systems developed for studying chemical separations, such as amphiphilic molecules assembled at a solid/water, air/water, or oil/water interface, may have far-reaching implications, extending beyond separations and opening doors to addressing a wide range of scientific inquiries. This perspective discusses recent interfacial studies elucidating amphiphile–ion interactions in chemical separations of metal ions. Finally, these studies provide direct, molecular-scale information about solute and solvent behavior at aqueous interfaces, including multivalent and complex ions in highly concentrated solutions, which play key roles in LLE of critical materials.

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

Spatiotemporal dynamics of fast electron heating in solid-density matter via XFEL

Abstract High-intensity, short-pulse lasers are crucial for generating energetic electrons that produce high-energy-density (HED) states in matter, offering potential applications in igniting dense fusion fuels for fast ignition laser fusion. High-density targets heated by these electrons exhibit spatially non-uniform and highly transient conditions, which have been challenging to characterize due to limitations in diagnostics that provide simultaneous high spatial and temporal resolution. Here, we employ an X-ray Free Electron Laser (XFEL) to achieve spatiotemporally resolved measurements at sub-micron and femtosecond scales on a solid-density copper foil heated by laser-driven fast electrons. Our X-ray transmission imaging reveals the formation of a solid-density hot plasma localized to the laser spot size, surrounded by Fermi degenerate, warm dense matter within a picosecond, and the energy relaxation occurring within the hot plasma over tens of picoseconds. These results validate 2D particle-in-cell simulations incorporating atomic processes and provide insights into the energy transfer mechanisms beyond current simulation capabilities. This work significantly advances our understanding of rapid fast electron heating and energy relaxation in solid-density matter, serving as a key stepping stone towards efficient high-density plasma heating and furthering the fields of HED science and inertial fusion energy research using intense, short-pulse lasers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

AtomSets as a hierarchical transfer learning framework for small and large materials datasets

Abstract Predicting properties from a material’s composition or structure is of great interest for materials design. Deep learning has recently garnered considerable interest in materials predictive tasks with low model errors when dealing with large materials data. However, deep learning models suffer in the small data regime that is common in materials science. Here we develop the AtomSets framework, which utilizes universal compositional and structural descriptors extracted from pre-trained graph network deep learning models with standard multi-layer perceptrons to achieve consistently high model accuracy for both small compositional data (<400) and large structural data (>130,000). The AtomSets models show lower errors than the graph network models at small data limits and other non-deep-learning models at large data limits. They also transfer better in a simulated materials discovery process where the targeted materials have property values out of the training data limits. The models require minimal domain knowledge inputs and are free from feature engineering. The presented AtomSets model framework can potentially accelerate machine learning-assisted materials design and discovery with less data restriction.

Chen, Chi (ORCID:0000000180087043)↗
DOE OSTI2022

Broadband Wide-Angle VElocity Selector (BWAVES) neutron spectrometer designed for the SNS Second Target Station

A recently proposed wide-angle velocity selector (WAVES) device for choosing the velocity of detected neutrons after they have been scattered by the sample paves the way for inverted geometry neutron spectrometers with continuously adjustable final neutron wavelength. BWAVES broadband inverted geometry spectrometer proposed for the Second Target Station at the Spallation Neutron Source at Oak Ridge National Laboratory is designed using WAVES to simultaneously probe dynamic processes spanning 4.5 decades in time (energy transfer). This makes BWAVES a uniquely flexible instrument which can be viewed as either a quasielasitc neutron scattering (QENS) spectrometer with a practically unlimited (overlapping with the vibrational excitations) range of energy transfers, or a broadband inelastic vibrational neutron spectrometer with QENS capabilities, including a range of accessible momentum transfer (Q) and a sufficiently high energy resolution at the elastic line. The new capabilities offered by BWAVES will expand the application of neutron scattering in ways not possible with existing neutron spectrometers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Shewanella oneidensis MR-1 respires CdSe quantum dots for photocatalytic hydrogen evolution

Living bio-nano systems for artificial photosynthesis are of growing interest. Typically, these systems use photoinduced charge transfer to provide electrons for microbial metabolic processes, yielding a biosynthetic solar fuel. Here, we demonstrate an entirely different approach to constructing a living bio-nano system, in which electrogenic bacteria respire semiconductor nanoparticles to support nanoparticle photocatalysis. Semiconductor nanocrystals are highly active and robust photocatalysts for hydrogen (H 2 ) evolution, but their use is hindered by the oxidative side of the reaction. In this system, Shewanella oneidensis MR-1 provides electrons to a CdSe nanocrystalline photocatalyst, enabling visible light-driven H 2 production. Unlike microbial electrolysis cells, this system requires no external potential. Illuminating this system at 530 nm yields continuous H 2 generation for 168 h, which can be lengthened further by replenishing bacterial nutrients.

Science & Technology - Other Topics↗