3_Drought_Experiment_1
This is an early experiment in the APPL facility at ORNL looking at the effect of drought on various Populus genotypes. Nisqually-1, WV-94, BESC-394, BESC-198, BESC-24, BESC-375
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This is an early experiment in the APPL facility at ORNL looking at the effect of drought on various Populus genotypes. Nisqually-1, WV-94, BESC-394, BESC-198, BESC-24, BESC-375
This is very early commissioning data (2019) from the newly established APPL facility at ORNL. Instruments, and technologies are in active development at this stage.
Here, this study presents a novel reduced-order modeling framework, Time-Dependent Bases with Local CUR decomposition (TDB-L-CUR), designed to efficiently and accurately approximate the species transport equations in reacting flow simulations. The method extends the existing TDB-CUR approach for chemically reacting flows (Jung et al. Comput. Methods Appl. Mech. Engrg. 437 (2025) 117758), which leverages matrix decomposition techniques to form a global-in-space, time-dependent low-dimensional manifold. While TDB-CUR performs well in homogeneous systems, it may be less well-suited to spatially heterogeneous systems such as turbulent flames, where higher-rank approximations are typically required. The proposed TDB-L-CUR framework introduces two methodological extensions to the baseline approach. First, it applies unsupervised clustering to partition the physical domain into distinct regions, enabling spatially localized manifold construction, thereby reducing the rank required for the reduced-order representation. Second, it incorporates a computational singular perturbation (CSP)-based scheme for identifying and penalizing fast species, allowing for spatio-temporally adaptive mitigation of chemical stiffness. The proposed framework is validated on a hierarchy of test cases, including a one-dimensional premixed flame, a two-dimensional nonpremixed ignition case with vortex interaction, and a three-dimensional turbulent premixed flame. TDB-L-CUR significantly improves accuracy over TDB-CUR while further reducing computational cost. The fully on-the-fly formulation of TDB-L-CUR (i.e., requiring no offline training or prior knowledge) makes it a robust and scalable tool for reduced-order modeling of reactive flows.
Drying processes are among the most energy-consuming operations in industrial and manufacturing settings, demanding strategic selection, design, and control for enhanced efficiency. Advancing drying technologies is critical for improving sustainability, lowering energy use, reducing carbon emissions, and minimizing waste. This study explores two innovative strategies aimed at transforming drying processes into sustainable, low-carbon systems by reducing energy consumption, minimizing waste, and maintaining a strong emphasis on preserving product quality. The first strategy showcases a sub-pilot scale hybrid ultrasonic-convective dryer for agrifood products. This technology, powered by electricity (process electrification), integrates non-thermal ultrasonic dehydration with convective heating and is presented as a sustainable and energy-efficient solution that enhances eco-friendly practices. The second strategy involves introducing and implementing a novel, multiobjective, mixed integer dynamic optimization technique to determine the optimal time-dependent process parameter values for the drying operation. This optimization technique yields operating conditions that are piecewise constant in time aiming to maximize the energy efficiency of the hybrid ultrasonic-convective dryer while ensuring strict adherence to product quality constraints. By adopting the hybrid ultrasonic-convective dryer, a notable 35% improvement in energy efficiency was achieved compared to conventional hot-air drying systems for drying apple slices. The proposed optimization framework further enhanced energy efficiency by nearly 14% over the most efficient process on the identical testbed, under static operating conditions. The reported enhancements have been experimentally validated. Regarding drying time (thereby improving production yield), the developed hybrid ultrasonic-convective dryer demonstrates as much as a 41% reduction in total processing time, which is further optimized by an additional 10% using our proposed optimization framework. The research outcomes have profound implications for the design and operation of drying systems, encompassing crucial aspects such as process electrification, cost-effectiveness, energy savings, time efficiency, product yield, product quality, and process automation.
Abstract Single-particle imaging (SPI) using X-ray free-electron Lasers (XFELs) offers the potential to determine protein structures at high spatial and temporal resolutions without the need for crystallization or vitrification. However, the technique faces challenges due to weak diffraction signals from single proteins and significant background scattering from gases used for sample delivery. A recent observation of a diffraction pattern from an isolated GroEL protein complex Ekeberg T et al. (Light Sci Appl 13:15, 2024.https://doi.org/10.1038/274s41377-023-01352-7) had similar numbers of signal and background photons. Ongoing efforts aim to reduce the background created by sample delivery, with one approach replacing most of the used gas with helium Yenupuri T et al. (Sci Rep 14:4401, 2024.https://doi.org/10.1038/s41598-024-54605-9). In this study, we investigate the effects of a reduced background on the resolution limits for SPI of isolated proteins under different experiment conditions. As a test case, we used GroEL, and we used experimentally derived parameters for our simulations. We observe that background significantly impacts the achievable resolution, particularly when the signal strength is comparable to the background. This is best exemplified at 6.0 keV, where a background reduction by a factor of 10 leads to a resolution improvement from 1.9 to 1.2 nm, for a dataset of$$10^4$$patterns.
Continuum shock mixture models are reviewed and applied to determine the equations of state for five different compositions of Ni x Al y , as well as bulk Ni+Al reactive multilayers, by combining the fundamental property data for elemental nickel and aluminum. From the literature, we down-select and evaluate two analytical models for the mixture Hugoniot, i.e., the well-known method of kinetic energy averaging (KEA) and a recent model proposed by Jordan and Baer [J. Appl. Phys. 111, 083516 (2012)]. Fundamentally, the former method assumes pressure equilibrium, whereas the latter assumes a common particle velocity and mixture sound speed from compressible two-phase cavitating flows. Additionally, we construct thermodynamically complete equations of state by fitting Einstein oscillator series models for the specific heat at constant volume. Finally, the solid solution approximation is invoked for intermetallic compositions, which are not strictly physical mixtures. Overall, the KEA model provides a better fit to the available Ni x Al y and Ni+Al multilayer shock compression data; however, there are combinations of material properties where the performance of these two models is thought to be reversed. Moreover, the results of this work include the first analytical solution of Jordan–Baer that does not require numerical root finding, as well as proposed modifications to the Einstein oscillator series to incorporate some effects of local pressure–temperature equilibrium and reaction–diffusion. Future work is planned that will use these equations of state in mesoscale simulations to study shock-induced reaction in Ni+Al multilayers, and the intended application is illustrated with a brief 2D hydrocode example.
The survivability of final optics is expected to be a major challenge for all future inertial fusion energy concepts. Due to their higher damage threshold, gaseous optics have been identified as a promising solution to this problem. Gaseous optics can be created through the photoabsorption of spatially modulated UV light, which induces various chemical processes that heat the gas. This heating leads to a pressure perturbation, which in turn launches a density perturbation that can imprint a refractive index modulation such as a grating. In this article, we introduce a parallel C/C++ code to simulate gaseous optics. PIAFS2D is a high-order conservative finite-difference code to solve the compressible Navier–Stokes equations along with the photochemical heating sources on Cartesian grids. The simulations are validated by the linear theory derived in a previous paper [Michel et al., Phys. Rev. Appl. 22, 024014 (2024)]. For larger perturbations, the behavior of the system—particularly the evolution of the generated acoustic wave—demonstrates strong nonlinearity. PIAFS2D allows the study of nonlinear behaviors and can be used for the design of high-efficiency gaseous optics elements in realistic experimental conditions.
This study presents a novel physics-informed neural network (PINN) framework for modeling poroelasticity in heterogeneous media with material interfaces. The approach introduces a composite neural network (CoNN) where separate neural networks predict displacement and pressure variables for each material. While sharing identical activation functions, these networks are independently trained for all other parameters. To address challenges posed by heterogeneous material interfaces, the CoNN is integrated with the Interface-PINNs (I-PINNs) framework (Sarma et al., Comput. Methods Appl. Mech. Eng. 429: 117135, 2024), allowing different activation functions across material interfaces. Further, this ensures accurate approximation of discontinuous solution fields and gradients. Performance and accuracy of this combined architecture were evaluated against the conventional PINNs approach, a single neural network (SNN) architecture, and the eXtended PINNs (XPINNs) framework through two one-dimensional benchmark examples with discontinuous material properties. The results show that the proposed CoNN with I-PINNs architecture achieves an RMSE that is two orders of magnitude better than the conventional PINNs approach and is at least 40 times faster than the SNN framework. Compared to XPINNs, the proposed method achieves an RMSE at least one order of magnitude better and is 40% faster.
In ab initio studies of carrier-capture processes in defective semiconductor materials, the single-effective-mode formalism and the static-coupling approximation have become the predominant theoretical approaches for determining carrier-capture coefficients. The single-mode formalism relies on accurate nonequilibrium defect energies obtained from density-functional theory (DFT), where required inputs are a series of configurationally displaced, defect-containing supercells obtained using an interpolative ansatz, and where the DFT outputs are corresponding total energies that have traditionally been postprocessed using a long-established ground-state formulation of finite-size corrections and defect-formation energies. This formulation remains commonly used even though the defects that form a configuration-coordinate (CC) diagram typically exist as structures that are displaced from the ground state. To remedy this inconsistency, Kumagai has recently proposed novel methods for implementing finite-size corrections specifically intended for DFT calculations of the defect energies used to construct CC diagrams and implement the single-mode formalism [Y. Kumagai, Phys. Rev. B 107, L220101 (2023)]. Kumagai's approach builds on the latest finite-size-correction methods introduced to describe vertical charge-state transitions for charge-localizing point defects in semiconductors and insulators [T. Gake et al., Phys. Rev. B 101, 020102 (2020); S. Falletta et al., Phys. Rev. B 102, 041115 (2020)]. The newly identified finite-size artifact treated in these studies is the polarization charge induced on a configurationally frozen defect and its subsequent interaction with a vertical transition in charge state. In this work, we evaluate Kumagai's proposed methodology by applying it in a high-precision DFT study of carrier capture by substitutional C N in GaN, a well-characterized and technologically relevant defect and material. We have rigorously calculated C N defect energies across various supercell sizes for each defect configuration and charge state on the hole-capture CC diagram of C N (𝑞=−1), enabling a direct comparison of the slopes of the defect energies versus inverse cell size with those predicted by Kumagai. The most consequential prediction of Kumagai's method is that these slopes distinctly vary as the square of the linear-interpolation parameter used to construct the nonequilibrium defect configurations. Our results quantitatively support this prediction. Moreover, with these new finite-size corrections and multiple-cell-size DFT calculations in place, we find that the classical energy barrier for hole capture by C N (𝑞=−1) in GaN decreases to 0.092–0.127 eV. This finding confirms the recent ≈ 0.1 eV prediction of Reshchikov based on the weak temperature dependence for hole capture observed in photoluminescence experiments [M. A. Reshchikov, J. Appl. Phys. 129, 121101 (2021)]. These results stand in stark contrast to previously calculated barriers of 0.486 and 0.73 eV, which also used the single-mode formalism but were obtained by instead using ground-state-based finite-size corrections. Our reduced classical barrier for capture increases the temperature-dependent hole-capture coefficient of a C N (𝑞=−1) defect by more than two to four orders of magnitude for temperatures of 100–600 K, compared to the previous 0.486 eV results. While other defects may not be as dramatically affected as here, we suggest that incorporating proper finite-size corrections for the vertical-transition-like states embedded within CC diagrams is an essential, yet previously unrecognized, component of accurate modeling of carrier-capture when using the single-effective-mode formalism.
High-quality quantum communications that enable important capabilities, such as distributed quantum computing and sensing, will require quantum repeaters for providing high-quality entanglement. To realize high-rate heralded entanglement for quantum repeaters, Chen et al . [Phys. Rev. Appl. 19 , 054029 (2023)] proposed a scheme for heralded-multiplexed generation of quasideterministic entangled photon pairs, called zero-added-loss multiplexing (ZALM). Here, we propose a design of the ZALM source using time-bin entanglement and spectral shearing. Additionally, we provide an analysis of experimentally relevant spectral-shearing parameters to optimize the spectral multiplexing. Moreover, we experimentally verify the compatibility of time-bin pulses and spectral shearing, as supported by observation of no appreciable phase shift when the same shearing is applied to both time bins. These results expand the benefits of applying a ZALM source to time-bin entanglement use cases. Moreover, more fully demonstrating time-bin and spectral shearing compatibility clears a path toward a broader use of spectral shearing that provides a deterministic frequency shift of high utility.
The spectral emission characteristics of a proof-of-concept hybrid metallized diamond(001) photocathode are presented. The quantum efficiency (QE) is shown to be determined by the photoinjection efficiency across the ohmic contact at the back metallized face, whereas the mean transverse energy (MTE) of the photoemitted electrons is consistent with an (optical)phonon-assisted and momentum-resonant Franck-Condon mechanism [Franck-Condon electron emission from polar semiconductor photocathodes, Phys. Rev. Appl. 23, 054065 (2025)] following electron drift transport to the untreated diamond(001) front emission face. Emission is observed from both the lower and upper conduction bands of diamond with positive and negative electron affinity, respectively. A potential route to the realization of a red-visible photocathode based on this concept with a sub-50 meV MTE and a QE greater than 0.1% is discussed.
An analytical formulation of (optical-)phonon-mediated and momentum-resonant Franck-Condon emission of photoexcited electrons from polar semiconductors is shown to be very consistent with (i) the observed emission properties of a cesiated GaAs(001) photocathode at 808 nm [J. Phys. D: Appl. Phys. 54, 205301 (2021)] and (ii) the measured spectral emission properties of a GaN(0001) photocathode from just below its bandgap energy to 5 eV. The theoretical analysis in the parabolic band approximation predicts the form of both the quantum efficiency and mean transverse energy of photoemission as a function of the photocathode’s electron affinity and the electron temperature in the vicinity of its emission face. The good agreement between theory and experimental data also suggests that sub-10-nm rms surface roughness effects are not significant for polar semiconductor photocathodes.
Ziti is a NOODLES client application for RealityKit-powered devices (specifically the Apple Vision Pro). NOODLES is a cross-platform/device/tool protocol for collaborative visualization. NOODLES was Developed at the National Renewable Energy Laboratory (NREL) as a capability of the Insight Center https://www.nrel.gov/computational-science/insight-center.html
This dataset contains DFT input and output files supporting the theoretical modeling in the associated publication (ACS Appl. Mater. Interfaces 2026, 18, 15654-15664). The calculations model the interfacial energetics of two MnTe polymorphs — NiAs-MnTe (hexagonal, alpha phase) and ZnS-MnTe (cubic, gamma phase) — on InP(111) substrates with two surface terminations: In-terminated InP(111)A and P-terminated InP(111)B. This gives four interface configurations: NiAs on In-terminated (experimentally observed), NiAs on P-terminated (computed for comparison), ZnS on In-terminated (computed for comparison), and ZnS on P-terminated (experimentally observed). The dataset is organized into four calculation types, each covering all four polymorph/termination combinations: (i) Slabs: Pristine MnTe/InP heterostructure slabs used to compute total energies and interface energy densities (Eint) for all four configurations, as reported in Fig. 6 of the main text. (ii) Disorder: Same slab geometries with a P_Te + Te_P antisite defect pair introduced near the interface, used to assess chemical intermixing effects on interface stability (Fig. S8, SI). (iii) Strain: Pristine slab calculations with in-plane lattice parameters strained by -1% and +1% relative to the InP lattice constant, used to evaluate strain-dependent interface energetics (Fig. S9, SI). (iv) Charge_Density: Single-point calculations on the full heterostructure, the isolated InP slab, and the isolated MnTe slab at fixed geometry, used to compute differential charge density plots showing interfacial charge accumulation and depletion as a function of surface termination (Fig. S10, SI). Each calculation folder contains INCAR, KPOINTS, POSCAR, CONTCAR, OUTCAR, and POTCAR_info.txt (PAW potential information, excluding the full POTCAR due to VASP licensing restrictions). The calculations were performed using VASP 6.4.3 with PBE exchange-correlation, PAW potentials, a Hubbard correction of Ueff = 5 eV on Mn d-states, and A-type AFM spin initialization.
Coded aperture imaging is a form of lensless aperture imaging that projects multiple overlapping images of the source onto the detector, enhancing signal strength, which is advantageous for low-flux sources or high-resolution imaging. This technique requires decoding of the detector signal to reconstruct the original source, which involves convolving the detector data with the aperture pattern. When the signal is from a centered point source, the reconstructed source image is known as the point spread function (PSF). A clean PSF without artifacts is a Dirac delta function [Appl. Opt. 20, 1858 (1981)]. This paper examines the robustness of the decoding process against variations in experimental tolerances by analyzing artifact growth in the reconstructed PSF. We illustrate the effects of incorrect magnification, rotation, and detector size and find that aperture–detector rotational misalignment about the imaging axis is the most sensitive parameter, with significant artifact generation occurring with angular offsets of less than one degree. We discuss compensation methods for imperfect aperture placement, finding that small detector sizes produce uncompensatable artifact generation, and compare theoretical predictions with experimental PSF measurements of a rank , 6.8 mm thick (less than one mean free path) coded aperture with a 3.5 mm cell size, conducted at the MegaJOuLe Neutron Imaging Radiography dense plasma focus [IEEE Trans. Plasma Sci. 49, 3299 (2021)] using a 2.45 MeV neutron source. Based on our findings, we recommend using magnified coded apertures in the under-sampled regime, which allows for the inclusion of fiducial markers to characterize aperture–detector rotational offsets and the addition of mechanical coupling, where possible, to constrain rotational and magnification offsets.
This dataset contains surface soil temperature measurements from five urban parks in Knoxville: Cumberland Estates Park (CE), Socially Equal Energy Efficient Development (SD), West View Park (WV), Victor Ashe Park (VA), and West Hills Park (WH). The dataset comprises 29 Excel (.xlsx) and Comma-Separated Values (.csv) files documenting soil temperature recorded by six HOBO Pendant MX Water Temperature Data Loggers at each site, except for CE, which has five sensors. Each logger was installed at a depth of 10 inches and positioned approximately 3 to 6 feet from the weather station at each site. To open both csv and xlsx files, users can utilize spreadsheet applications such as Microsoft Excel, Google Sheets, LibreOffice Calc, and Apple Numbers. This dataset is part of a broader study examining the effects of soil moisture and plant evapotranspiration on ambient temperature and relative humidity across multiple urban parks in Knoxville, Tennessee.
The two major outcomes from this DOE supported collaboration between UbiQD and NREL were: 1) an expert analysis/modeling of the expected performance and cost of luminescent solar concentrating windows with quantum dot coatings, and 2) critical R&D characterization of materials and device performance analysis using equipment and processes that are too expensive for UbiQD to perform in-house. The latter also included third-party validation of the device performance with an NREL-certified conversion efficiency that was ultimately published. (see ACS Energy Lett. 2018 and recently ACS Appl. Energy Mater. 2020).
Apps that run on mobile devices are one of critical components of the electric vehicle (EV) ecosystem and pose possible threat actor points of entry that may impact the trust and security of EV charging systems in the future. Mobile apps often rely on communication between cloud servers and users, thereby creating potential points of entry for cyberattacks. Although app stores such as Apple App Store or Google Play Store generally test the security of apps, the cyber aspects may not be sufficient for many entities including DOD, federal fleets, and commercial entities. A more thorough inspection and the ability to influence developers is imminently needed. This research studies security attributes and vulnerabilities of a sample of mobile applications that support key user functions in the EV ecosystem. The study shows that all analyzed apps have security risks, categorized as either high or medium or both and a comprehensive cybersecurity guideline for developing mobile apps is necessary.