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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

AI-assisted optimization of the ECCE tracking system at the Electron Ion Collider

The Electron-Ion Collider (EIC) is a cutting-edge accelerator facility that will study the nature of the “glue” that binds the building blocks of the visible matter in the universe. The proposed experiment will be realized at Brookhaven National Laboratory in approximately 10 years from now, with detector design and R&D currently ongoing. Notably, EIC is one of the first large-scale facilities to leverage Artificial Intelligence (AI) already starting from the design and R&D phases. The EIC Comprehensive Chromodynamics Experiment (ECCE) is a consortium that proposed a detector design based on a 1.5 T solenoid. The EIC detector proposal review concluded that the ECCE design will serve as the reference design for an EIC detector. Herein we describe a comprehensive optimization of the ECCE tracker using AI. The work required a complex parametrization of the simulated detector system. Herein our approach dealt with an optimization problem in a multidimensional design space driven by multiple objectives that encode the detector performance, while satisfying several mechanical constraints. We describe our strategy and show results obtained for the ECCE tracking system. The AI-assisted design is agnostic to the simulation framework and can be extended to other sub-detectors or to a system of sub-detectors to further optimize the performance of the EIC detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Oxygen redox chemistry: A new approach to high energy density world

Sodium-ion batteries (SIBs) have been considered as promising candidates for large scale energy storage systems due to the great abundance of sodium resources. For sodium layered transition metal oxide cathode materials, oxygen redox can increase the energy density by enabling extra capacity and delivering high voltage. Here we provide a comprehensive overview of oxygen redox in SIBs from the perspectives of mechanism, challenges, and solutions. The previous studies on voltage hysteresis, capacity decay and oxygen release induced by oxygen redox as well as the effectiveness of different strategies including superlattice engineering, elemental substitution, and surface modification on the electrochemical performances of cathode materials with oxygen redox are comprehensively summarized with typical examples. Finally, the remaining challenges and the future research direction are discussed.

25 ENERGY STORAGE↗
DOE OSTI2023

Aerodynamic characterization of two tandem wind turbines under yaw misalignment control using actuator line model

Yaw control has proven to be promising in alleviating the wake effects that plague the efficiency of wind farms. In this work, the actuator line modeling (ALM) method is adopted to simulate the flows over two tandem turbines distanced by 3–7 rotor diameters, with the yaw angle of the upstream rotor varying from γ 1 = 0° to 50°. The aim is to provide a comprehensive aerodynamic characterization of this simple wind farm under yaw misalignment control. With increasing yaw angle, the power generated by the downstream rotor increases, compensating the power loss in the upstream rotor, and resulting in significantly higher total power of the two turbines than that without yaw control. The maximum power output is achieved as the upstream wake of the yawed rotor is redirected away from the downstream rotor plane. Behind the downstream rotor, the secondary steering phenomenon is observed, where the wake is also redirected from the centerline. The use of the actuator line model also reveal unsteady aerodynamic characteristics that cannot be captured by lower-fidelity models. For the upstream rotor, the yaw misalignment results in time-varying change in the local angle of attack on the blade, giving rise to unsteady loading. The downstream rotor is partially submerged in the deflected wake incurred by the yawed upstream rotor. As the blade revolves into and out of the wake deficit, the blade experiences cyclic loading, leading to even stronger fluctuations in the aerodynamic loads than the upstream rotor. These analysis provides a comprehensive understanding of the yaw control effects on the two tandem rotors from the perspectives of aerodynamic performance, wake profiles, and unsteady characteristics. In conclusion, the insights gained from the present study can aid the design of collective yaw control strategies of wind farms, and lay the foundation for assessing the fatigue damage associated with yaw misalignment.

17 WIND ENERGY↗
DOE OSTI2024

Annotation of DOM metabolomes with an ultrahigh resolution mass spectrometry molecular formula library

Current approaches to analyzing metabolomic data often rely on matching MS/MS fragmentation data to sparse libraries or databases. This approach results in limited identification of features, often with less than 10% of the dataset being annotated. A complementary approach is to assign molecular formula to features based on accurate mass measurements, but the platforms commonly used for metabolomics do not have the needed accuracy or resolving power to do this robustly, particularly for larger molecules. Using our newly modified analysis tool, CoreMS, we generated a library of molecular formula from pooled samples analyzed with LC-21T FT-ICR MS. This library successfully annotated approximately 53.2% of features identified from the exometabolome of marine diatom Phaeodactylum tricornutum – a nearly ten-fold increase over the 5.9% annotation rate achieved using a conventional MS/MS library matching approach. Using this FT-ICR MS library approach, we were able to differentiate differences in the exometabolome of P. tricornutum in iron replete and iron limited conditions, with 668 metabolites being differentially expressed (p < 0.05, 2 x intensity difference) under these conditions. The traditional MS/MS fragmentation-based annotation approach only annotated 61 of these metabolites, while our novel pipeline annotated 450 metabolites and revealed 12 metabolites that were significantly more abundant under low iron conditions. Our results demonstrate the utility of ultrahigh resolution mass spectrometry for generating more comprehensive and confident molecular annotations.

21T-FTICR-MS, CoreMS↗
DOE OSTI2024

Particle-based high-temperature thermochemical energy storage reactors

Solar and other renewable energy driven gas-solid thermochemical energy storage (TCES) technology is a promising solution for the next generation energy storage systems due to its high operating temperature, efficient energy conversion, ultra-long storage duration, and potential high energy density. Experimental and theoretical studies suggest that the respective gravimetric and volumetric TCES energy storage densities vary from 200 to 3000 kJ kg –1 and 1–3 GJ m –3 . Solar radiation or heat generated from electric furnaces powered by renewable electricity can be stored in the form of chemical energy through endothermic reactions, while the stored chemical energy can be converted to thermal energy via an exothermic reaction when needed. The design of highly effective reactors requires a deep understanding of materials, thermodynamics, chemical kinetics, and transport phenomena. At time of writing, TCES reactors are yet to be deployed at commercially relevant scales, leaving a substantial gap between development efforts and commercial feasibility. Therefore, this review aims to examine the state-of-the-art design and performance of particle-based TCES reactors with different reactive materials. Fundamentals related to TCES reactive materials, reaction conditions, thermodynamics and kinetics, and transport phenomena are reviewed in detail to provide a comprehensive understanding of the reactor design and operation. Five major types of TCES reactors have been comprehensively reviewed and compared, including fixed, moving, rotary, fluidized, and entrained bed reactors. Most reported prototype reactors in the literature operate at lab scale with thermal inputs below 40 kW, and scaled TCES reactors (e.g., at megawatt level) are yet to be demonstrated. The nominal reactor operating temperatures range from 300 to 1500 °C, depending on the selected chemistry, reactive material, and heat sources. To evaluate their designs, the reactors are assessed in aspects of performance, cost, and durability. Discrepancies in performance indicators of energy storage density, extent of reaction, and various energy efficiencies are highlighted. The scale-up of reactors and power block integration, which hold the key to the successful commercialization of TCES systems, are critically analyzed. Furthermore, advanced materials (both reactive materials and ceramic reactor housing materials), effective particle flow control, advanced modeling tools, and novel system design may bring significant improvement to the energy efficiency, storage density and cost competitiveness of particle-based TCES reactors.

25 ENERGY STORAGE↗
DOE OSTI2021

Structure of high-lying levels populated in the 96 Y → 96 Zr β decay

The nature of the high-lying final levels of the 96 Y gs β decay, one of the three most important contributors to the high-energy reactor antineutrino spectrum, has been investigated in high-resolution γ-ray spectroscopy following the β decay as well as in a campaign of inelastic photon scattering experiments. The comprehensive approach establishes 1 - levels associated with the Pygmy Dipole Resonance as high-lying final levels in the β decay. Branching ratios extracted from β decay complement photon scattering and allow the absolute E1 excitation strength to be determined for levels populated in both reactions. The combined data represents a comprehensive approach to the wavefunction of the 1 - levels below the Qβ value, which are investigated in the Quasiparticle Phonon Model. The calculations reveal that the components populated in β decay contribute only with small amplitudes to the complex wavefunction of these 1 - levels. A comparison of the β decay results to data from total absorption γ -ray spectroscopy demonstrates a good agreement between both measurements.

Pygmy dipole resonance↗
DOE OSTI2025

Exploring nuclear structure with multiparticle azimuthal correlations at the LHC

Details of the nuclear structure of Xe, such as the quadrupole deformation and the nuclear diffuseness, are studied by extensive measurements of anisotropic-flow-related observables in Xe–Xe collisions at a centre-of-mass energy per nucleon pair $\sqrt{s_{NN}}$ = 5.44 TeV with the ALICE detector at the LHC. The results are compared with those from Pb–Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV for a baseline, given that the 208 Pb nucleus exhibits a very weak deformation. Furthermore, comprehensive comparisons are performed with a state-of-the-art hybrid model using IP-Glasma+MUSIC+UrQMD. It is found that among various IP-Glasma+MUSIC+UrQMD calculations with different values of nuclear parameters, the one using a nuclear diffuseness parameter of α 0 = 0.492 and a nuclear quadrupole deformation parameter of β 2 = 0.207 provides a better description of the presented flow measurements. These studies represent the first systematic exploration of nuclear structure at TeV energies, utilizing a comprehensive set of anisotropic flow observables. The measurements serve as a critical experimental benchmark for rigorously testing the interplay between nuclear structure inputs and heavy-ion theoretical models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Nuclear data uncertainty propagation and modeling uncertainty impact evaluation in neutronics core simulation

Uncertainty analysis is a critical requirement in reactor simulation as it is used to quantify the reliability of best-estimate calculation. A comprehensive uncertainty analysis should characterize all sources of uncertainties in a computationally-feasible and scientifically-defendable manner. Here we employ a well-established reduced order modeling (ROM) based uncertainty quantification methodology to propagate uncertainties throughout neutronic calculations. ROM relies on recent advances in randomized data mining techniques applied to large data streams. In our proposed implementation, the nuclear data uncertainties are first propagated from multi-group level through lattice physics calculation to generate few-group parameter uncertainties, described using a vector of mean values and a covariance matrix. Employing an ROM-based compression of the covariance matrix, the few-group uncertainties are then propagated through downstream core simulation in a computationally efficient manner. This straightforward approach, albeit efficient as compared to brute force forward and/or adjoint-based methods, often employs a number of assumptions that have been unquestioned in the literature of neutronic uncertainty analysis. This manuscript argues that these assumptions could introduce another source of uncertainty referred to as modeling uncertainties, whose magnitude needs to be quantified in tandem with nuclear data uncertainties. Thus, our primary goal is to explore the interactions between these two uncertainty sources in order to assess whether modeling uncertainties have an impact on parameter uncertainties. To explore this endeavor, the impact of a number of modeling assumptions on core attributes uncertainties is quantified. The study employs a CANDU reactor model, with Serpent and NEWT as lattice physics solvers and NESTLE-C as core simulator. The modeling assumptions investigated include those related with the uncertainty propagation method employed, e.g., deterministic vs. stochastic, the few-group energy structure employed to represent the cross-sections, the resonance treatment in lattice physics calculation, the reference values for the cross-section, and the number of samples employed to render ROM compression. Results indicate that some of the modeling assumptions could have a non-negligible impact on the core responses propagated uncertainties, highlighting the need for a more comprehensive approach to combine parameter and modeling uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Parton distributions and lattice-QCD calculations: Toward 3D structure

The strong force which binds hadrons is described by the theory of quantum chromodynamics (QCD). Determining the character and manifestations of QCD is one of the most important and challenging outstanding issues necessary for a comprehensive understanding of the structure of hadrons. Within the context of the QCD parton picture, the parton distribution functions (PDFs) have been remarkably successful in describing a wide variety of processes. However, these PDFs have generally been confined to the description of collinear partons within the hadron. New experiments and facilities provide the opportunity to additionally explore the transverse structure of hadrons which is described by generalized parton distributions (GPDs) and transverse-momentum-dependent parton distribution functions (TMD PDFs). In our previous report Lin et al. (2018), we compared and contrasted the two main approaches used to determine the collinear PDFs: the first based on perturbative QCD factorization theorems, and the second based on lattice-QCD calculations. In the present report, we provide an update of recent progress on the collinear PDFs, and also expand the scope to encompass the generalized PDFs (GPDs and TMD PDFs). We review the current state of the various calculations, and consider what new data might be available in the near future. We also examine how a shared effort can foster dialog between the PDF and lattice-QCD communities, and yield improvements for these generalized PDFs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Progress and opportunities in corrosion mitigation in heat transfer fluids for next-generation concentrating solar power

Concentrating solar power (CSP) systems have gained considerable eminence in converting solar thermal energy into electrical power in recent years. According to the U.S. Department of Energy's Gen3 roadmap, the CSP system should operate > 700 °C, as its efficiency depends directly on the operating temperature of the heat transfer fluids (HTFs). A significant challenge, however, is the corrosion of containment materials by the HTFs that is exacerbated at the higher temperatures. A comprehensive review of the high temperature stable HTFs, their properties, corrosion mechanisms on different alloys, and corrosion mitigation measures is of much importance for directing a concerted research and development in the field, which forms the motivation for this compendium. First, molten salt HTFs and their thermophysical properties, along with liquid metals, are introduced. Corrosion of structural materials in different HTFs including molten salts, liquid metals, and supercritical carbon-di-oxide at various temperatures and the corrosion mechanisms are comprehensively reviewed. In addition, several corrosion mitigation methods are discussed. Finally, future directions for HTFs and corrosion mitigation methods in molten salts are proposed. As a result, the holistic review presented here will serve as the foundation for further research addressing relevant challenges and enabling the promise of achieving cost-competitive CSP.

14 SOLAR ENERGY↗
DOE OSTI2024

Review of data-driven models for quantifying load shed by non-residential buildings in the United States

Shifting and shedding power demand in buildings can be cost-effective techniques for grids to function reliably and for end users to earn compensation. Grid operators reimburse customers in proportion to the quantity of load shed. Simple data-driven methods are used to quantify this shed, which is the difference between a measured load during the event and modeled "baseline" that would have occurred in absence of the event. These methods have evolved over the years and in many cases have been integrated with building physics, to make them a hybrid between physics based and empirical models. However, there is no comprehensive analysis that provides guidance to building operators, grid operators and researchers in selecting appropriate models based on their specific needs and available data. Here, this work aims to fill this gap by critically assessing the performance of baseline models put forward from the year 2000 through 2023. The literature reviewed includes reports generated by grid operators, reports from national laboratories and academic journal articles. The work outlines modeling features like the inputs, training period, estimation method, adjustments to fine tune the predictions and metrics to evaluate the performance. A comprehensive list of 50 models has been provided. For each model, the study explores the applicability of the model to weather sensitive buildings, variability in the building profile, timing of the event, and whether the building reduces energy consumption before an event. The work identifies the situations in which a particular model works and draws lessons based on evidence of performance. Finally, recommendations to aid in model selection are given.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Implications of stop-and-go traffic on training learning-based car-following control

Learning-based car-following control (LCC) of connected and autonomous vehicles (CAVs) is gaining significant attention with the advancement of computing power and data accessibility. While the flexibility and large model capacity of model-free architecture enable LCC to potentially outperform the model-based car-following (CF) model in improving traffic efficiency and mitigating congestion, the generalizability of LCC for traffic conditions different from the training environment/dataset is not well-understood. Herein, this study seeks to explore the impact of stop-and-go traffic in the training dataset on the generalizability of LCC. It uses the characteristics of lead vehicle trajectories to describe stop-and-go traffic, and links the theory of identifiability (i.e., obtaining a unique parameter estimation result using sensor measurements) to the generalizability of behavior cloning (BC) and policy-based deep reinforcement learning (DRL). Correspondingly, the study shows theoretically that: (i) stop-and-go traffic can enable the property of identifiability and enhance the control performance of BC-based LCC in different traffic conditions; (ii) stop-and-go traffic is not necessary for DRL-based LCC to generalize to different traffic conditions; (iii) DRL-based LCC trained with only constant-speed lead vehicle trajectories (not sufficient to ensure identifiability) can be generalized to different traffic conditions; and (iv) stop-and-go traffic increases variance in the training dataset, which improves the convergence of parameter estimation while negatively impacting the convergence of DRL to the optimal control policy. Numerical experiments validate the above findings, illustrating that BC-based LCC entails comprehensive training datasets for generalizing to different traffic conditions, while DRL-based LCC can achieve generalization with simple free-flow traffic training environments. This further suggests DRL as a more promising and cost-effective LCC approach to reduce operational costs, mitigate traffic congestion, and enhance safety and mobility, which can accelerate the deployment and acceptance of CAVs.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

sMicroRNA-28-5p acts as a metastasis suppressor in gastric cancer by targeting Nrf2

The transcription factor nuclear factor (erythroid-2)-related factor 2 (Nrf2) can principally serve a mode of protection for both the normal cells and cancer cells from cellular stress, and elevates cancer cell survival. microRNA-28 (miR-28) has been involved in the regulation of Nrf2 expression in breast epithelial cells. However, no comprehensive analysis has been conducted regarding the function of miR-28-5p regulating Nrf2 in gastric cancer (GC). In this study, we aimed to evaluate their interaction and biological roles in the migration and invasion of GC cells. The expression of Nrf2 in the cancer tissues harvested from 42 patients with GC was examined by an array of molecular techniques comprising of Immunohistochemical staining, RT-qPCR and Western blot analysis. Kaplan-Meier method was adopted for analysis of the correlation of Nrf2 with the prognosis of GC patients. Interaction between miR-28-5p and Nrf2 was determined using the bioinformatics analysis and dual luciferase reporter gene assay. Gain- and loss-of-function studies of miR-28-5p and Nrf2 were conducted to elucidate their effects on GC cell migration, invasion and metastasis, as well as expression pattern of several epithelial-mesenchymal transition (EMT)-related proteins. Results indicated that the expression pattern of Nrf2 was significantly upregulated in GC tissues and indicative of poor prognosis of GC patients. miR-28-5p was verified to target Nrf2 and downregulate its expression. GC cells with overexpression of miR-28-5p or Nrf2 knockdown exhibited a marked reduction in the migrated and invasive abilities, along with the N-cadherin expression yet an increase of E-cadherin expression. Furthermore, miR-28-5p exerted an inhibitory function on the metastatic and tumorigenicity of GC cells. In conclusion, miR-28-5p is a comprehensive tumor suppressor that inhibits GC cell migration and invasion through repressing the Nrf2 expression. Therefore, miR-28-5p may serve as a potential biomarker for the prognosis of GC and a novel therapeutic target in advanced GC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Defending Weapons Inspections from the Effects of Disinformation

The intentional spread of disinformation is not a new challenge for the scientific world. We have seen it perpetuate the idea of a flat earth, convince communities that vaccines are more dangerous than helpful, and even suggest a connection between the “5G” communication infrastructure and COVID-19. Nor is disinformation a new phenomenon in the weapons inspection arena. Weapons inspectors themselves are often forced to sift through alternative narratives of events and inconsistent reporting, and they regularly see their credibility and conclusions questioned in the face of government politics or public biases. But certain recent disinformation campaigns have become so overwhelmingly comprehensive and effective that they constitute a new kind of threat. By preventing accountability for clear violations of international law, these campaigns have created a challenge to the survival of arms control treaties themselves. If weapons inspectors cannot regain the trust of the international community in the face of this challenge, it will be increasingly difficult to ensure compliance with arms control and disarmament treaties going forward. In this essay, I will briefly discuss one of the most comprehensive disinformation efforts of the past decade: the disinformation campaign used to prevent accountability for Syria's repeated use of chemical weapons. After this discussion, I will propose one possible approach to help protect the credibility of disarmament experts and weapons inspectors in the face of pervasive disinformation. This approach will require a concerted effort to connect and support compliance experts and to understand and explain their expertise across cultural, political, national, economic, and religious divides.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Bimetallic-Derived Catalytic Structures for CO 2 -Assisted Ethane Activation

In recent years, the simultaneous upgrading of CO 2 and ethane has emerged as a promising approach for generating valuable gaseous (CO, H 2 , and ethylene) and liquid (aromatics and C 3 oxygenates) chemicals from the greenhouse gas CO 2 and large-reserved shale gas. The key challenges for controlling product selectivity lie in the selective C-H and C-C bond cleavage of ethane with the assistance of CO 2 . Bimetallic-derived catalysts likely undergo alloying or oxygen-induced segregation under reaction conditions, thus providing diverse types of interfacial sites, e.g., metal/support (M/M'O x ) interface and metal oxide/metal (M'O x /M) inverse interface, that are beneficial for selective CO 2 -assisted ethane upgrading. The alloying extent can be initially predicted by cohesive energy and atomic radius (or Wigner-Seitz radius), while the preference for segregation to form the on-top suboxide can be approximated using the work function, electronegativity, and binding strength of adsorbed oxygen. Furthermore, bimetallic-derived catalysts are typically supported on high surface area oxides. Modifying the reducibility and acidity/basicity of the oxide supports and introducing surface defects facilitate CO 2 activation and oxygen supplies for ethane activation. Using in situ synchrotron characterization and density functional theory (DFT) calculations, we found that the electronic properties of oxygen species influence the selective cleavage of C-H/C-C bonds in ethane, with electron-deficient oxygen over the metal (or alloy) surface promoting nonselective bond scission to produce syngas and electron-enriched oxygen over the metal oxide/metal interface enhancing selective C-H scission to yield ethylene. Here, we further demonstrate that the preferred structures of the catalyst surfaces, either alloy surfaces or metal oxide/metal inverse interfaces, can be controlled through the appropriate choice of metal combinations and their atomic ratios. Through a comprehensive comparison of experimental results and DFT calculations, the selectivity of C-C/C-H bond scission is correlated with the thermodynamically favorable bimetallic-derived structures (i.e., alloy surfaces or metal oxide/metal inverse interfaces) under reaction conditions over a wide range of bimetallic catalysts. These findings not only offer structural and mechanistic insights into bimetallic-derived catalysts but also provide design principles for selective catalysts for CO 2 -assisted activation of ethane and other light alkanes. This Account concludes by discussing challenges and opportunities in designing advanced bimetallic-derived catalysts, incorporating new reaction chemistries for other products, employing precise synthesis strategies for well-defined structures with optimized site densities, and leveraging time/spatial/energy-resolved in situ spectroscopy/scattering/microscopy techniques for comprehensive structural analysis. The research methodologies established here are helpful for the investigation of dynamic alloy and interfacial structures and should inspire more efforts toward the simultaneous upgrading of CO 2 and shale gas.

03 NATURAL GAS↗
DOE OSTI2020

Identification and Quantification of Technetium Species in Hanford Waste Tank AN-102

Technetium-99 (Tc) generated from the fission of 235U and 239Pu in high yields is one of the most difficult contaminants to be addressed at the U.S. Department of Energy Hanford Site. In strongly alkaline solutions typifying Hanford tank waste, Tc exists as pertechnetate (TcO4-) (oxidation state VII) as well as in reduced forms (oxidation state < VII) collectively known as non-pertechnetate species. Designing strategies for effective Tc management, including separation and immobilization, necessitates understanding the molecular structure of the non- pertechnetate species and their identification in the actual tank waste samples, which would facilitate development of new treatment technologies effective for dissimilar Tc species. Toward this objective, a spectroscopic library of the Tc(I) [fac-Tc(CO)3]+ and Tc(IV, VII) compounds was generated using a range of techniques and applied to the characterization of the actual tank waste supernatant collected from the tank 241-AN-102 at Hanford, WA. A sample of the 241-AN-102 tank waste supernatant was processed to adjust Na concentration to about 5.6 M and remove 137Cs by spherical resorcinol-formaldehyde (sRF) ion exchange resin. Cesium-loaded sRF column was eluted with 0.5 M HNO3. As received AN-102, Cs-depleted AN-102 effluent, and sRF eluate fractions were comprehensively characterized for chemical composition and speciation of Tc using 99Tc nuclear magnetic resonance spectroscopy and X-ray absorption spectroscopy. It was demonstrated for the first time that non-pertechnetate Tc present in the 241-AN-102 tank waste is composed of several low-valent Tc species, including the Tc(I) [fac-Tc(CO)3]+ and Tc(IV) compounds. This is the second experimental observation of the [fac-Tc(CO)3]+ species in the Hanford tank waste and the first demonstration of multiple forms of non-pertechnetate species existing simultaneously in the waste, cumulatively highlighting their importance for the waste processing.

Low Activity Waste (LAW), High Level Waste, nuclea↗
DOE OSTI2024

Beyond the Charge Transfer Mechanism for 2D Materials-Assisted Surface Enhanced Raman Scattering

Two-dimensional (2D) materials have been extensively implemented as surface-enhanced Raman scattering (SERS) substrates, enabling trace-molecule detection for broad applications. However, the accurate understanding of the mechanism remains elusive because most theoretical explanations are still phenomenological or qualitative based on simplified models and rough assumptions. To advance the development of 2D material-assisted SERS, it is vital to attain a comprehensive understanding of the enhancement mechanism and a quantitative assessment of the enhancement performance. Here, the microscopic chemical mechanism of 2D material-assisted SERS is quantitatively investigated. The frequency-dependent Raman scattering cross sections suggest that the 2D materials’ SERS performance is strongly dependent on the excitation wavelengths and the molecule types. By analysis of the microscopic Raman scattering processes, the comprehensive contributions of SERS can be revealed. Beyond the widely postulated charge transfer mechanisms, the quantitative results conclusively demonstrate that the resonant transitions within 2D materials alone are also capable of enhancing the molecular Raman scattering through the diffusive scattering of phonons. Furthermore, all of these scattering routines will interfere with each other and determine the final SERS performance. Our results not only provide a complete picture of the SERS mechanisms but also demonstrate a systematic and quantitative approach to theoretically understand, predict, and promote the 2D materials SERS toward analytical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗