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At least 1,045 records · Page 58

Solid–liquid separation of lignocellulosic sugars from biomass by rotating ceramic disc filtration

In many biomass conversion processes, the separation of cellulosic sugars from residual, lignin-rich solids is a critical step, and achieving high recovery yields of sugars by conventional tangential crossflow and vacuum filtration is challenged by the presence of biomass solids, which rapidly foul filters, resulting in decreased throughput. Considering the performance limitations of traditional filtration methods, dynamic filtration, which generates high shear at the membrane surface to decrease fouling, is emerging as a viable alternative for demanding solid–liquid separations. For high solids separations, there is little available information regarding the performance, limitations, and energy consumption of dynamic filtration. To that end, here we characterized the performance of a dynamic filtration module, specifically a rotating ceramic disc (RCD) filter, for the aseptic recovery of cellulosic sugars from biomass solids following pretreatment and enzymatic hydrolysis. We show how RCD rotational velocity and percent biomass solids impact the filter throughput. Additionally, we used computational fluid dynamics (CFD) simulations to estimate the shear rate at the membrane surface and to visualize hydrodynamic profiles within the module. With the combined CFD simulations and experimental results, we estimated the energy demand and operating expenses for a viable dynamic filtration system operating with a lignocellulosic feed slurry. Our results indicate that an RCD filter can achieve ≥95% recovery of sugars and produce a retentate slurry containing 12 wt% insoluble solids with low energy consumption (a 2.2-fold improvement over cross-flow filtration) and low operating costs ($\$$0.06 per kg sugars). These results show a viable path towards operationally reliable, energy efficient, and cost-effective separations of sterilized cellulosic sugars from biomass solids and highlight the potential of dynamic filtration systems for challenging solid–liquid separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large-scale experimental validation of thermochemical water-splitting oxides discovered by defect graph neural networks

Thermochemical water-splitting (TCH) based on 2-step thermal redox cycles in metal oxides is a promising approach to generating H 2 , but state-of-the-art (SOTA) CeO 2 has several practical limitations, which has motivated continued materials discovery efforts in this field. Here, in this study, we improve upon a SOTA defect graph neural network (dGNN) surrogate model's oxygen vacancy predictions and combine them with materials project phase diagrams to down-select and discover structurally diverse, experimentally known metal oxides whose TCH performance was previously unknown. Amongst twelve candidates selected based on our high-throughput screening and down-selection criteria, we achieved ∼80% accuracy in identifying materials with stable redox cycling and hydrogen production in stagnation flow reactor water-splitting experiments. Closer to 100% accuracy can be achieved if higher-accuracy, hybrid DFT-predicted vacancy formation energies were computed and used in lieu of the most uncertain dGNN-based screening predictions, as they correct false positives to true negatives. Notably, two discovered candidates, Sr 3 PrMn 2 O 8 and Ba 2 Fe 2 O 5 , display hydrogen yields greater than CeO 2 under specific redox conditions. In conclusion, these results demonstrate our ability to computationally predict and experimentally validate promising candidate TCH materials that have the potential to compete with CeO 2 .

08 HYDROGEN↗

Delving into the depths of NGC 3783 with XRISM II. Cross-calibration of X-ray instruments used in the large, multi-mission observational campaign

Context. Accurate X-ray spectroscopic measurements are fundamental for deriving basic physical parameters of the most abundant baryon components in the Universe. The plethora of X-ray observatories currently operational enables a panchromatic view of the high-energy emission of celestial sources. However, uncertainties in the energy-dependent calibration of the instrument transfer functions (e.g. the effective area, energy redistribution, or gain) can limit - and historically, did limit - the accuracy of X-ray spectroscopic measurements. Aims. We revised the status of the cross-calibration among the scientific payload on board four operation missions: Chandra, NuSTAR, XMM-Newton, and the recently launched XRISM. XRISM carries the micro-calorimeter Resolve, which yields the best energy resolution at energies ≥2 keV. For this purpose, we used the data from a 10-day-long observational campaign targeting the nearby active galactic nucleus NGC 3783, carried out in July 2024. Methods. We present a novel model-independent method for assessing the cross-calibration status that is based on a multi-node spline of the spectra with the highest-resolving power (XRISM/Resolve in our campaign). We also estimated the impact of the intrinsic variability of NGC 3783 on the cross-calibration status due to the different time coverages of participating observatories and performed an empirical reassessment of the Resolve throughput at low energies. Results. Based on this analysis, we derived a set of energy-dependent correction factors of the observed responses, enabling a statistically robust analysis of the whole spectral dataset. They will be employed in subsequent papers describing the astrophysical results of the campaign. Aims. We revised the status of the cross-calibration among the scientific payload on board four operation missions: Chandra, NuSTAR, XMM-Newton, and the recently launched XRISM. XRISM carries the micro-calorimeter Resolve, which yields the best energy resolution at energies ≥2 keV. For this purpose, we used the data from a 10-day-long observational campaign targeting the nearby active galactic nucleus NGC 3783, carried out in July 2024. Methods. We present a novel model-independent method for assessing the cross-calibration status that is based on a multi-node spline of the spectra with the highest-resolving power (XRISM/Resolve in our campaign). We also estimated the impact of the intrinsic variability of NGC 3783 on the cross-calibration status due to the different time coverages of participating observatories and performed an empirical reassessment of the Resolve throughput at low energies. Results. Based on this analysis, we derived a set of energy-dependent correction factors of the observed responses, enabling a statistically robust analysis of the whole spectral dataset. They will be employed in subsequent papers describing the astrophysical results of the campaign.

Active Galactic Nuclei, individual: NGC 3783↗

Structured illumination with thermal imaging (SI-TI): A dynamically reconfigurable metrology for parallelized thermal transport characterization

The recent push for the “materials by design” paradigm requires synergistic integration of scalable computation, synthesis, and characterization. Among these, techniques for efficient measurement of thermal transport can be a bottleneck limiting the experimental database size, especially for diverse materials with a range of roughness, porosity, and anisotropy. Traditional contact thermal measurements have challenges with throughput and the lack of spatially resolvable property mapping, while non-contact pump-probe laser methods generally need mirror smooth sample surfaces and also require serial raster scanning to achieve property mapping. Here, we present structured illumination with thermal imaging (SI-TI), a new thermal characterization tool based on parallelized all-optical heating and thermometry. Experiments on representative dense and porous bulk materials as well as a 3D printed thermoelectric thick film (~50 μm) demonstrate that SI-TI (1) enables paralleled measurement of multiple regions and samples without raster scanning; (2) can dynamically adjust the heating pattern purely in software, to optimize the measurement sensitivity in different directions for anisotropic materials; and (3) can tolerate rough (~3 μm) and scratched sample surfaces. Here, this work highlights a new avenue in adaptivity and throughput for thermal characterization of diverse materials.

42 ENGINEERING↗

Design study of an edge current density diagnostic using new high-performance single-channel beam emission spectrometers at DIII-D

A novel Motional Stark Effect spectroscopy system has been designed for application at the DIII-D tokamak. The system is optimized for studies of the poloidal and toroidal magnetic field in the plasma pedestal region with frame rates of up to 10 kHz. Further, light from an existing high-photon-throughput collection lens is analyzed using four single-channel f/2.8 Czerny–Turner spectrometers that use custom-made lens systems instead of mirrors. Each spectrometer has two separate outgoing legs and is operated in a positive grating order, which allows for simultaneous observations of D-alpha and D-beta spectra. Forward modeling using the code FIDASIM shows a radial resolution of the system close to 0.6 cm and sufficiently good spectral resolution when masking the high throughput light collection lens in the horizontal direction to avoid overly strong Doppler broadening of beam emission lines. Moreover, a detailed sensitivity study considering realistic levels of readout and photon noise shows that the poloidal and toroidal magnetic field strengths can be inferred with an uncertainty of less than 1%, which will allow the inference of changes of the plasma current during transient events.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A new class of variable-radii diffraction optics for high-resolution x-ray spectroscopy at the National Ignition Facility (invited)

A new class of crystal shapes has been developed for x-ray spectroscopy of point-like or small (a few mm) emission sources. These optics allow for dramatic improvement in both achievable energy resolution and total throughput of the spectrometer as compared with traditional designs. This class of crystal shapes, collectively referred to as the Variable-Radii Spiral (VR-Spiral), utilize crystal shapes in which both the major and minor radii are variable. A crystal using this novel VR-Spiral shape has now been fabricated for high-resolution Extended X-ray Absorption Fine Structure (EXAFS) experiments targeting the Pb-L 3 (13.0 keV) absorption edge at the National Ignition Facility. The performance of this crystal has been characterized in the laboratory using a microfocus x-ray source, showing that high-resolution high-throughput EXAFS spectra can be acquired using this geometry. Importantly, these successful tests show that the complex three-dimensional crystal shape is manufacturable with the required precision needed to realize the expected performance of better than 5 eV energy resolution while using a 30 mm high crystal. An improved generalized mathematical form for VR-Spiral shapes is also presented allowing improved optimization as compared to the first sinusoidal-spiral based design. Finally, this new formulation allows VR-Spiral spectrometers to be designed at any magnification with optimized energy resolution at all energies within the spectrometer bandwidth.

47 OTHER INSTRUMENTATION↗

A coded aperture with sub-mean-free-path thickness for implosion geometry imaging on ICF and IFE experiments

Inertial confinement fusion and inertial fusion energy experiments diagnose the geometry of the fusion region through imaging of the neutrons released through fusion reactions. Pinhole arrays typically used for such imaging require thick substrates to obtain high contrast along with a small pinhole diameter to obtain high resolution capability, resulting in pinholes that have large aspect ratios. This leads to expensive pinhole arrays that have small solid angles and are difficult to align. Here, we propose a coded aperture with scatter and partial attenuation (CASPA) for fusion neutron imaging that relaxes the thick substrate requirement for good image contrast. These coded apertures are expected to scale to larger solid angles and are easier to align without sacrificing imaging resolution or throughput. We use Monte Carlo simulations (Geant4) to explore a coded aperture design to measure neutron implosion asymmetries on fusion experiments at the National Ignition Facility (NIF) and discuss the viability of this technique, matching the current nominal resolution of 10 µm. The results show that a 10 mm thick tungsten CASPA can image NIF implosions with neutron yields above 10 14 with quality comparable to unprocessed data from a current NIF neutron imaging aperture. Furthermore, this CASPA substrate is 20 times thinner than the current aperture arrays for fusion neutron imaging and less than one mean free-path of 14.1 MeV neutrons through the substrate. Since the resolution, solid angle, and throughput are decoupled in coded aperture imaging, the resolution and solid angle achievable with future designs will be limited primarily by manufacturing capability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Unraveling H2 chemisorption and physisorption on metal decorated graphene using quantum Monte Carlo

Molecular hydrogen has the potential to significantly reduce the use of carbon dioxide emitting energy processes. However, hydrogen gas storage is a major bottleneck for its large-scale use as current storage methods are energy intensive. Among different storage methods, physisorbing molecular hydrogen at ambient pressure and temperatures is a promising alternative—particularly in light of the advancements in tunable lightweight nanomaterials and high throughput screening methods. Nonetheless, understanding hydrogen adsorption in well-defined nanomaterials remains experimentally challenging and reference information is scarce despite the proliferation of works predicting hydrogen adsorption. We focus on Li, Na, Ca, and K, decorated graphene sheets as substrates for molecular hydrogen adsorption, and compute the most accurate adsorption energies available to date using quantum diffusion Monte Carlo (DMC). Building on our previous insights at the density functional theory (DFT) level, we find that a weak covalent chemisorption of molecular hydrogen, known as Kubas interaction, is feasible on Ca decorated graphene according to DMC, in agreement with DFT. This finding is in contrast to previous DMC predictions of the 4H2/Ca+ gas cluster (without graphene) where chemisorption is not favored. However, we find that the adsorption energy of hydrogen on metal decorated graphene according to a widely used DFT method is not fully consistent with DMC. The reference adsorption energies reported herein can be used to find better work-horse methods for application in large-scale modeling of hydrogen adsorption. Furthermore, the implications of this work affect strategies for finding suitable hydrogen storage materials and high-throughput methods.

Chemistry↗

Designing ITER motional Stark effect line shift (MSE-LS) spectrometers

As a part of ITER beam aided diagnostics, the design of Motional Stark Effect (MSE) diagnostic observing the emission from the Balmer-α line is underway. The physics of Stark splitting shows that the Stark manifold is polarization dependent, and the energy splitting results in a line shift proportional to the electric field. Due to the challenges of maintaining the calibration of the plasma facing mirrors in ITER, the conventional MSE polarimetry measurement technique is replaced with a spectral approach that is deemed more favorable in the ITER environment. The MSE line shift (LS) diagnostic is designed to quantify the Lorentz electric field magnitude by measuring the Stark manifold using visible spectroscopy. In the presence of large magnetic fields and high energy heating beams of 1 MeV, the expected Stark splitting is much larger than in typical devices. The MSE-LS design has unique challenges requiring careful consideration and modeling of its viewing geometry and photon budget. The MSE-LS approach on ITER is promising but has stringent demands on the allowable errors for the statistical and systematic fitting uncertainties. In this study, a full system model and numerical simulations of data for each sightline are completed. For a range of optical transmission fractions, photon noise analysis is conducted to determine the statistical uncertainties. This provides guidance on the spectrometer throughput, dispersion at the detector, optics, and other design choices. A conceptual design of a high throughput spectrometer with a volume phase transmission grating is presented.

Instruments & Instrumentation↗

Electronic structure simulations in the cloud computing environment

The transformative impact of modern computational paradigms and technologies, such as high-performance computing, quantum computing, and cloud computing, has opened up profound new opportunities for scientific simulations. Scalable computational chemistry is one beneficiary of this technological progress. The main focus of this paper is on the performance of various quantum chemical formulations, ranging from low-order methods to high-accuracy approaches, implemented in different computational chemistry packages, such as NWChem, NWChemEx, SPEC, ExaChem, and FLOSIC codes on the Azure Quantum Element (AQE) Microsoft cloud services. We pay particular attention to the intricate workflows for performing composite chemistry simulations, associated data curation, and mechanisms for accuracy assessment, as defined by the enabling cloud Computational Chemistry as a Service (CCaaS). Our focus also extends to Arrows' automated workflow for high throughput simulations. Finally, we provide a perspective on the role of cloud computing in supporting the mission of leadership computational facilities (LCFs).

computational chemistry, electronic structure, Clo↗

Terahertz near-field imaging of sidewall-induced losses in superconducting qubits

Correlating superconducting qubit performance with advanced materials analysis is a key strategy for improving coherence. Existing diagnostics for key properties, such as dielectric loss, structural discontinuity, and interface heterogeneity, often rely on destructive electron microscopy or low-throughput millikelvin measurements. Here, in this study, we demonstrate noninvasive terahertz (THz) nano-imaging/spectroscopy of encapsulated niobium transmon qubits as a high-throughput proxy for performance evaluation. We identify large variations in sidewall near-field signals, implicating sidewall loss and discontinuity as major coherence limiters, and also use THz hyperspectral line scans to probe dielectric responses and field participation at Al junction interfaces.

Kim, Richard H. J. [Ames Laboratory (AMES), Ames, ↗

A hybrid neural architecture: Online attosecond x-ray characterization

The emergence of high-repetition-rate x-ray free-electron lasers (XFELs), such as SLAC’s LCLS-II, serves as our canonical example for autonomous controls that necessitate high-throughput diagnostics paired with streaming computational pipelines capable of single-shot analysis with extremely low latency. We present the deterministic characterization with an integrated parallelizable hybrid resolver architecture, a hybrid machine learning framework designed for fast, accurate analysis of XFEL diagnostics using angular streaking-based sinogram images. This architecture integrates convolutional neural networks and bidirectional long short-term memory models to denoise input, identify x-ray sub-spike features, and extract sub-spike relative delays with sub-30 attosecond temporal resolution. Deployed on low-latency hardware, it achieves over 10 kHz throughput with 168.3 μs inference latency, indicating scalability to 14 kHz with field-programmable gate array integration. By transforming regression tasks into classification problems and leveraging optimized error encoding, we achieve high precision with low-latency performance that is critical for real-time streaming event selection and experimental control feedback signals. This represents a key development in real-time control pipelines for next-generation autonomous science, generally, and high repetition-rate x-ray experiments in particular.

Accelerator Physics (physics.acc-ph)↗

Energy storage emerging: A perspective from the Joint Center for Energy Storage Research

Energy storage is an integral part of modern society. A contemporary example is the lithium (Li)-ion battery, which enabled the launch of the personal electronics revolution in 1991 and the first commercial electric vehicles in 2010. Most recently, Li-ion batteries have expanded into the electricity grid to firm variable renewable generation, increasing the efficiency and effectiveness of transmission and distribution. Important applications continue to emerge including decarbonization of heavy-duty vehicles, rail, maritime shipping, and aviation and the growth of renewable electricity and storage on the grid. This perspective compares energy storage needs and priorities in 2010 with those now and those emerging over the next few decades. The diversity of demands for energy storage requires a diversity of purpose-built batteries designed to meet disparate applications. Advances in the frontier of battery research to achieve transformative performance spanning energy and power density, capacity, charge/discharge times, cost, lifetime, and safety are highlighted, along with strategic research refinements made by the Joint Center for Energy Storage Research (JCESR) and the broader community to accommodate the changing storage needs and priorities. Innovative experimental tools with higher spatial and temporal resolution, in situ and operando characterization, first-principles simulation, high throughput computation, machine learning, and artificial intelligence work collectively to reveal the origins of the electrochemical phenomena that enable new means of energy storage. This knowledge allows a constructionist approach to materials, chemistries, and architectures, where each atom or molecule plays a prescribed role in realizing batteries with unique performance profiles suitable for emergent demands.

Trahey, Lynn↗

Discovery of complex oxides via automated experiments and data science

Significance Automation is accelerating the discovery of useful materials, yet testing even a small fraction of the billions of possible materials for a desired property is beyond the reach of workflows involving resource-intensive property measurements. Due to relationships among composition, structure, and properties, identifying a complex material with one interesting property makes it the proverbial needle in a haystack that merits testing for additional properties. We accelerate materials synthesis and optical characterization by employing physics-aware data science to identify materials for further investigation. With this approach, one does not need high-throughput methods for measuring every material property of interest since a single ultra-high–throughput workflow can guide material selection for other properties, which is a new paradigm for accelerated materials discovery.

36 MATERIALS SCIENCE↗

Sorting for secreted molecule production using a biosensor-in-microdroplet approach

Significance The design–build–test cycle of metabolic engineering is swiftly becoming test limited owing to advances in DNA synthesis and library design. At the same time, improving extracellular production requires high-throughput studies to detect extracellular (not intracellular) content. Traditional approaches that utilize chromatography-based analysis or plate-based fluorescence assays are relatively throughput limited and require a high degree of liquid handling. These limitations are avoided here by creating a generalizable approach for small molecule production screening. Namely, this paradigm combines “off-the-shelf” biosensors with large library screening from producing cells in a cell-type agnostic manner.

Bowman, Emily K.↗

Using 2.5D super-resolution to improve flaw detection in metal additive manufacturing parts

Industrial X-ray computed tomography (XCT) enables non-destructive inspection of additively manufactured (AM) parts, but high-resolution scanning requires long acquisition times and significant computational resources, limiting throughput in production environments. Super-resolution techniques can recover high-resolution information from low-resolution scans, but existing methods face a trade-off between 2D approaches that ignore inter-slice information and 3D methods that are computationally prohibitive for practical deployment. To address this trade-off, we propose a 2.5D deep learning-based super-resolution approach that uses seven neighbouring low-resolution slices to super-resolve the centre slice. This work evaluates the method on real XCT scans of steel AM parts, comparing reconstruction quality and flaw detection performance of 2D, 2.5D, and 3D ESRGAN-based super-resolution methods. Results demonstrate that 2.5D super-resolution significantly improves detection of small, process-induced flaws (e.g. porosity) compared to 2D methods, while avoiding the prohibitive computational burden of full 3D approaches. These findings provide initial evidence of 2.5D super-resolution as a practical, deployable solution for improving flaw detection in high-throughput industrial XCT inspection.

X-ray CT↗

Issues in Formation of Cryogenic Pellets for Fusion Applications

Cryogenic pellets are used for injection into fusion plasmas to add fuel to build up density and replace the ions lost from fusion reactions and imperfect confinement in the plasma. These pellets are formed at cryogenic temperatures with pure hydrogenic isotopes or mixtures of the isotopes. Technology to make these pellets and inject them into plasmas has been under development for many years, and various methods using freezing or desublimation have been shown to produce high-quality solid pellets suitable for injection. The throughput needed and possible impurity content from the necessary recirculation of fusion exhaust gases are two of the key issues to overcome for fusion pellet fueling systems in long-pulse burning plasmas. Here, we describe the technical challenges associated with these issues and the capability of pellet formation extruders to overcome them.Cryogenic pellets of deuterium, neon, and argon are also used in fusion tokamak devices for disruption mitigation in the form of large pellets that can be injected on demand to quickly dissipate the plasma thermal energy through radiation and add significant density in order to prevent runaway electron formation. Here, the issue is not throughput as with the fueling pellets but rather is the time it takes to form pellets of the size needed and the ability to dislodge them immediately on demand when needed to mitigate a disruption. The method used to make these pellets by desublimation is described, and examples related to how pellet size and input gas parameters affect the formation time are provided.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Bifurcation-like transition of divertor conditions induced by X-point radiation in KSTAR L-mode plasmas *

Abstract Density ramps with ion grad B drift directed into lower single null KSTAR L-mode plasmas are associated with a simultaneous and abrupt reduction of the divertor particle flux on both low- and high-field-side targets when the mid-plane line averaged electron density reaches a given level. Target embedded Langmuir probe signals show a clear ‘cliff edge’ behavior similar to that observed in the divertor target electron temperature in DIII-D H-mode plasmas (Eldon et al 2017 Nucl. Fusion 57 066039; McLean et al 2015 J. Nucl. Mater. 463 533–6). The collapse of the particle flux is observed along the whole divertor target area (from private flux region to the far scrape-off layer (SOL)). The critical upstream density of this target flux cliff is invariant under fuel gas throughput modulation. The transition along the cliff occurs in tens of milliseconds. With the cliff, carbon impurities and deuterium neutrals transported through the X-point to the core produce a strong radiation spot near the X-point, seen on bolometric signals, and increase the upstream density. The experimental observations are consistent with time-dependent SOLPS-ITER simulations, which also demonstrate an abrupt transition of the target flux and upstream density with the increase in X-point radiation. The timescale of the cliff predicted by SOLPS-ITER is consistent with the experiment, although, it is influenced by gas throughput or time-dependent numerical methods. In the L-mode phase space of separatrix electron density and temperature, branches are divided based on target temperature, because the latter is strongly coupled to the radiation front and ionization front due to the monotonic characteristic of the parallel electron temperature distribution. Since the H-mode condition operates at a much higher upstream density and electron temperature in phase space, dissipation from sputtered carbon alone leads to the density limit before reaching the X-point radiation condition. This is therefore consistent with the fact that cliffs have never been observed in H-mode KSTAR experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗