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A Field Survey of Rare Earth Element Concentrations in Process Streams Produced by Coal Preparation Plants in the Eastern USA
I this work, a field study was undertaken to experimentally measure the concentrations of rare earth elements (REEs) contained in the process streams generated by a group of 20 coal preparation plants located in the eastern USA. For each site, representative samples of clean coal product, coarse refuse, and fine refuse were collected. Each sample was then partitioned into preselected size and density classes by wet screening/sieving and float-sink testing. The resultant products were dried and subjected to laboratory analyses to determine ash contents and rare earth element concentrations including Yttrium and Scandium. A detailed analysis of the database generated by this exercise showed that coal-based products from these preparation plants contained significant quantities of rare earth elements. In particular, the coarse refuse streams currently discarded by the 20 plants examined were found to contain a sufficient tonnage of REEs to satisfy the current domestic demand for these important elements. The data also showed a strong positive correlation between ash content and REE concentration, which suggested that the primary association of REEs in eastern USA bituminous coal sources is likely within fractions containing inorganic impurities. This association was well described using a simple power equation relating ash content and REE concentration. The ratio of heavy-to-light rare earth elements was discovered to be significantly higher in organically rich fractions of clean coal, suggesting that mineral impurities intimately associated with carbonaceous matter have elevated concentrations of heavy rare earth elements. A similar trend was observed for a grouping of rare earth elements (Y, Nd, Eu, Tb, and Dy) that are likely subject to near-term supply shortages. Finally, the database showed that a linear correlation existed between La for many REEs of interest, although there were several notable exceptions for some high-value REEs (Lu, Pr, and Tb).
Physics-informed machine learning for building performance simulation-A review of a nascent field
Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing the performance of the built environment, optimizing energy efficiency, improving demand flexibility, and enhancing building resilience. However, conducting BPS is not trivial. Traditional BPS relies on accurate building energy models, which are primarily physics-based and heavily dependent on detailed building information, expert knowledge, and case-by-case model calibrations, significantly limiting their scalability. With the development of sensing technology and the increased availability of data, there is growing attention and interest in data-driven BPS. However, purely data-driven models often suffer from limited generalization ability and a lack of physical consistency, resulting in poor performance in real-world applications. To address these limitations, recent studies have begun integrating physics priors into data-driven models, a methodology known as physics-informed machine learning (PIML). PIML is an emerging field where its definitions, methodologies, evaluation criteria, application scenarios, and future directions remain open. To bridge those gaps, this study systematically reviews the state-of-the-art PIML for BPS, offering a comprehensive definition of PIML and comparing it to traditional BPS approaches regarding data requirements, modeling effort, performance, and computational cost. We also summarize the commonly used methodologies, validation approaches, application domains, available data sources, open-source packages, and testbeds. In addition, this study provides a general guideline for selecting appropriate PIML models based on BPS applications. Finally, this study identifies key challenges and outlines future research directions, providing a solid foundation and valuable insights to advance R&D of PIML in BPS.
Field evaluation of advanced controls for the retrofit of packaged air conditioners and heat pumps
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Molecular dynamics simulation of sodium aluminosilicate glass structures and glass surface-water reactions using the reactive force field (ReaxFF)
Reactive potentials are increasingly used to study the properties of glasses and glass water reactions in a reactive molecular dynamics (MD) framework. In this study, we have simulated a ternary sodium aluminosilicate glass and investigated the initial stages of the glass surface-water reactions at 300 K using reactive force field (ReaxFF). On comparison of the simulated glass structures generated using ReaxFF and classical Buckingham potentials, our results show that the atomic density profiles calculated for the surface glass structures indicate a bond-angle distribution dependency. The atomic density profiles also show higher concentrations of non-bridging oxygens (NBOs) and sodium ions at the glass surface. Additionally, we present our results of formation of silanol species and the diffusion of water molecules at the glass surface using ReaxFF.
Kinetic-j : A computational kernel for solving the linearized Vlasov equation applied to calculations of the kinetic, configuration space plasma current for time harmonic wave electric fields
We present the Kinetic-j code, a computational kernel for evaluating the linearized Vlasov equation withapplication to calculating the kinetic plasma response (current) to an applied time harmonic wave electricfield. This code addresses the need for a configuration space evaluation of the plasma current to enablekinetic full-wave solvers for waves in hot plasmas to move beyond the limitations of the traditional Fourierspectral methods. We benchmark the kernel via comparison with the standard k-space forms of the hotplasma conductivity tensor.
Experimental study on the effect of nozzle hole-to-hole angle on the near-field spray of diesel injector using fast X-ray phase-contrast imaging
Fuel atomization and vaporization process play a critical role in determining the engine combustion and emission. The primary near-nozzle breakup is the vital link between the fuel emerging from the nozzle and the fully atomized spray. In this study, the near-nozzle spray characteristics of diesel injector with different umbrella angle (UA) were investigated using high-speed X-ray phase-contrast imaging and quantitative image processing. A classic ‘dumbbell’ profile of spray width (SW) composed of three stages: opening stage, semisteady stage and closing stage. The SW peak of two-hole injectors was more than twice of that of single-hole injector at the opening and closing stages, corresponding to the hollow-cone spray. This indicated the vortex flow was formed with the increase of the UA. The higher injection pressure had little influence on the SW while led to earlier breakup closer to the nozzle. Significant fuel effect on the SW at higher needle lift was found. However, this effect could be neglect at lower needle lift due to the leading role of internal flow and cavitation on the near-field spray characteristics. In addition, the morphology-based breakup process was observed, which highlighted the important effect of internal flow on the spray development. The possibility of using hollow-cone spray in diesel injector was also discussed.
Giant low-field magnetocaloric effect and refrigerant capacity in reduced dimensionality EuTiO 3 multiferroics
Engineering magnetic materials into a thin film form while preserving its excellent magnetocaloric response is essential in the development of miniature magnetic coolers. We demonstrate how this can be achieved in the case of EuTiO 3 - an emerging multiferroic material. Unlike conventional cases where reduced dimensionality considerably decreased the magnetic entropy change (ΔS M ) and hence the refrigerant capacity (RC), we show the large low-field enhancements of ΔS M and RC in a ~100 nm thick nanocrystalline EuTiO 3 film (ΔS M ~ 24 J kg -1 K -1 and RC = 152 J kg -1 for μ 0 ΔH = 2T) relative to its single crystal counterpart (ΔS M ~ 17 J kg -1 K -1 and RC ~ 107 J kg -1 for μ 0 ΔH = 2T). The nanocrystalline EuTiO 3 film is an excellent candidate for cryogenic magnetic refrigeration. From our study, a new approach for improving both MCE and RC in magnetic nanomaterials is proposed, which will stimulate further research on magnetocaloric thin films and related cooling devices.
Structure-function relationships in photosynthetic membranes: Challenges and emerging fields
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Design principles and field performance of a solar spectral irradiance meter
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Soiling, cleaning, and abrasion: The results of the 5-year photovoltaic glass coating field study
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Developing the Pressure-Temperature-Magnetic Field Phase Diagram of Multiferroic [(CH3)2NH2]Mn(HCOO)3
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Time-Dependent Complete Active Space Embedded in Polarizable Force Field
Electron correlation and environmental effects play important roles in electron dynamics and spectroscopic observables of chemical systems in condensed phase. In this paper, we present a time-dependent complete active space configuration interaction (TD-CASCI) approach embedded in a polaraizable force filed, MMPol. The present implementation of TD-CASCI/MMPol utilizes a direct matrix-vector contraction, allowing studies of large systems. This scheme is used to study the solvatochromic shift of coumarin 153 in methanol. The TD-CASCI/MMPol approach captures the double excitation character in the excited state wave function and accurately predicts the solvatochromic red-shift of coumarin 153 dye within the experimental range, outperforming linear response time-dependent density functional theory. The effect of using different reference orbitals for the TD-CASCI/MMPol simulation is also investigated, highlighting the need for an unbiased treatment of all electronic states in the energy range of interest.
Using Neural Network Force Fields to Ascertain the Quality of Ab Initio Simulations of Liquid Water
Accurately simulating the properties of bulk water, despite the apparent simplicity of the molecule, is still a challenge. In order to fully understand and reproduce its complex phase diagram, it is necessary to perform simulations at the ab initio level, including quantum mechanical effects both for electrons and nuclei. This comes at a high computational cost, given that the structural and dynamical properties tend to require long timescales and large simulation cells. In this work, we evaluate the errors that density functional theory (DFT)-based simulations routinely incur into due time- and size-scale limitations. These errors are evaluated using neural-network-trained force fields that are accurate at the level of DFT methods. We compare different exchange and correlation potentials for properties of bulk water that require large timescales. Here we show that structural properties are less dependent on the system size and that dynamical properties such as the diffusion coefficient have a strong dependence on the simulation size and timescale. Our results facilitate comparisons of DFT-based simulation results with experiments and offer a path to discriminate between model and convergence errors in these simulations.
Clar’s Goblet on Graphene: Field-Modulated Charge Transfer in a Hydrocarbon Heterostructure
In certain configurations, the aromatic properties of benzene ring structured molecules allow for unpaired, reactive valence electrons (known as radicals). Clar’s goblets are such molecules. With an even number of unpaired radicals, these nanographenes are topologically frustrated hydrocarbons in which π-bonding network and topology of edges give rise to the magnetism. Clar’s goblets are therefore valued as prospective qubits provided they can be modulated between magnetic states. Here, using first-principles DFT, we demonstrate the effects of adsorption on both molecule and substrate in a graphene–Clar’s goblet heterostructure. We look at the energy difference bewteen FM and AFM states of the system and discuss underlying physical and chemical mechanisms in reference to the highest occupied molecular orbital (HOMO) and second HOMO (HOMO–1). We find that the HOMO of the molecule in the FM state is right at the Fermi surface, which leads to the hybridization between molecular state and the graphene state near the Dirac point. Furthermore, we investigate qualitative changes in charge realignment and magnetic state under a variable electric field. Transitions from FM to AFM and back to FM states are observed.
Diffractive Imaging of Conical Intersections Amplified by Resonant Infrared Fields
The fate of virtually all photochemical reactions is determined by conical intersections. These are energetically degenerate regions of molecular potential energy surfaces that strongly couple electronic states, thereby enabling fast relaxation channels. Their direct spectroscopic detection relies on weak features that are often buried beneath stronger, less interesting contributions. For azobenzene photoisomerization, a textbook photochemical reaction, we demonstrate how a resonant infrared field can be employed during the conical intersection passage to significantly enhance its coherence signatures in time-resolved Xray diffraction while leaving the product yield intact. Furthermore, this transition-state amplification holds promise to bring signals of conical intersections above the detection threshold.
Inferring Geothermal Reservoir Processes at the Raft River Geothermal Field, Idaho, USA, Through Modeling InSAR-Measured Surface Deformation
Ground surface deformations detected with Interferometric Synthetic Aperture Radar (InSAR) provide valuable information for inferring subsurface reservoir processes that are difficult to observe directly. This study aims at building a reservoir model that honors the available geological, hydrological and geo-mechanical data and also produces ground surface deformation consistent with InSAR measurements at the Raft River Geothermal Field. In the thermo-hydro-mechanical (THM) coupled model developed, the reservoir deforms as a result of the rock’s poroelastic response to changes in hydrologic pressure and thermal expansion/contraction. The results indicate that the observed deformation is the result of pressure decrease in the deep production reservoir and pressure increase in a shallower reservoir that accommodates the injected fluid (likely in the Salt Lake Formation). The combination of the uplift around injection wells with subsidence around the production wells, affected by the Bridge Fault as a flow barrier, creates a complex pattern of surface deformation in which the center of subtle subsidence significantly deviates from the location of the production wells. A parametric study suggests that (1) the Bridge Fault Zone is likely a flow barrier, (2) the surface deformation appears to be insensitive to the presence of the Narrows Structure, and (3) additional flow barriers likely exist to shape the flow system. This case study demonstrates the utility of a high-fidelity forward model that honors available known information and THM coupled processes in understanding geothermal reservoir characteristics.