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At least 847 records · Page 47

Development of a Universal Canister for Disposal of High-Level Waste in Deep Boreholes - 16482

The mission of the United States Department of Energy's (DOE's) Office of Environmental Management is to complete the safe cleanup of the environmental legacy brought about from five decades of nuclear weapons development and government-sponsored nuclear energy research. Some of the wastes that must be managed have been identified as good candidates for disposal in a deep borehole in crystalline rock. In particular, wastes that can be disposed of in a small package are good candidates for this disposal concept. A canister-based system that can be used for handling these wastes during the disposition process (i.e., storage, transfer, transportation, and disposal) could facilitate the eventual disposal of these wastes. Development of specifications for the universal canister system will consider the regulatory requirements that apply to storage, transportation, and disposal of the capsules, as well as operational requirements and limits that could affect the design of the canister (e.g., deep borehole diameter). In addition, there are risks and technical challenges that need to be recognized and addressed as Universal Canister system specifications are developed. This paper provides an approach to developing specifications for such a canister system that is integrated with the overall efforts of the DOE's Used Fuel Disposition Campaign's Deep Borehole Field Test and compatible with planned storage of potential borehole candidate wastes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Radionuclide Transport Simulations Supporting Proposed Borehole Waste Disposal in Israel

A scientific collaboration between the U.S. and Israel is underway to assess the suitability of a potential site for subsurface radioactive waste disposal in the Negev Desert, Israel. The Negev Desert has several favorable attributes for geologic disposal, including an arid climate, a deep vadose zone, interlayered low-permeability lithologies, and carbonate rocks with high uranium-sorption potential. These features may provide a robust natural barrier to radionuclide migration. Geologic and laboratory characterization data from the Negev Desert are incorporated into multiphase flow and transport models, solved using PFLOTRAN, to aid in site characterization and risk analysis that will support decision-making for waste disposal in an intermediate-depth borehole design. The lithology with the greatest uranium sorption potential at the site is phosphorite. We use modeling to evaluate the ability of this layer to impact uranium transport around a proposed disposal borehole. The current objective of the simulations is focused on characterizing hypothetical leakage from waste canisters and subsequent uranium migration under three infiltration scenarios. Here, we describe a hydrogeologic model based on data from a local exploratory borehole and present results for uranium flow and transport simulations under varying infiltration scenarios. We find that under the current climate conditions, it is likely that uranium will remain in the near-field of the borehole for thousands of years. However, under a hypothesized extreme climate scenario representing an increase in infiltration by a factor of 300x above present-day values, uranium may break through the phosphorite layer and exit the base of the model domain (~200 m above the water table) within 1000 years. Simulation results have direct implications for the planning of nuclear waste disposal in the Negev Desert, and specifically in intermediate-depth boreholes.

58 GEOSCIENCES↗

Active sulfur cycling in the terrestrial deep subsurface

The deep terrestrial subsurface remains an environment where there is limited understanding of the extant microbial metabolisms. At Olkiluoto, Finland, a deep geological repository is under construction for the final storage of spent nuclear fuel. It is therefore critical to evaluate the potential impact microbial metabolism, including sulfide generation, could have upon the safety of the repository. As such, we investigated a deep groundwater where sulfate is present, but groundwater geochemistry suggests limited microbial sulfate-reducing activity. Examination of the microbial community at the genome-level revealed microorganisms with the metabolic capacity for both oxidative and reductive sulfur transformations. Deltaproteobacteria are shown to have the genetic capacity for sulfate reduction and possibly sulfur disproportionation, while Rhizobiaceae, Rhodocyclaceae, Sideroxydans, and Sulfurimonas oxidize reduced sulfur compounds. Further examination of the proteome confirmed an active sulfur cycle, serving for microbial energy generation and growth. Our results reveal that this sulfide-poor groundwater harbors an active microbial community of sulfate-reducing and sulfide-oxidizing bacteria, together mediating a sulfur cycle that remained undetected by geochemical monitoring alone. The ability of sulfide-oxidizing bacteria to limit the accumulation of sulfide was further demonstrated in groundwater incubations and highlights a potential sink for sulfide that could be beneficial for geological repository safety.

58 GEOSCIENCES↗

Analytical-HZETRN Model for Rapid Assessment of Active Magnetic Radiation Shielding

The use of active radiation shielding designs has the potential to reduce the radiation exposure received by astronauts on deep-space missions at a significantly lower mass penalty than designs utilizing only passive shielding. Unfortunately, the determination of the radiation exposure inside these shielded environments often involves lengthy and computationally intensive Monte Carlo analysis. In order to evaluate the large trade space of design parameters associated with a magnetic radiation shield design, an analytical model was developed for the determination of flux inside a solenoid magnetic field due to the Galactic Cosmic Radiation (GCR) radiation environment. This analytical model was then coupled with NASA's radiation transport code, HZETRN, to account for the effects of passive/structural shielding mass. The resulting model can rapidly obtain results for a given configuration and can therefore be used to analyze an entire trade space of potential variables in less time than is required for even a single Monte Carlo run. Analyzing this trade space for a solenoid magnetic shield design indicates that active shield bending powers greater than 15 Tm and passive/structural shielding thicknesses greater than 40 g/cm2 have a limited impact on reducing dose equivalent values. Also, it is shown that higher magnetic field strengths are more effective than thicker magnetic fields at reducing dose equivalent.

Washburn, S. A.↗

Feasibility of an earth-to-space rail launcher system

The feasibility of earth-to-space electromagnetic (railgun) launchers (ESRL) is considered, in order to determine their technical practicality and economic viability. The potential applications of the launcher include nuclear waste disposal into space, deep space probe launches, and atmospheric research. Examples of performance requirements of the ESRL system are a maximum acceleration of 10,000 g's for nuclear waste disposal in space (NWDS) missions and 2,500 g's for earth orbital missions, a 20 km/sec launch velocity for NWDS missions, and a launch azimuth of 90 degrees E. A brief configuration description is given, and test results indicate that for the 2020-2050 time period, as much as 3.0 MT per day of bulk material could be launched, and about 0.5 MT per day of high-level nuclear waste could be launched. For earth orbital missions, a significant projectile mass was approximately 6.5 MT, and an integral distributed energy store launch system demonstrated a good potential performance. ESRL prove to be economically and environmentally feasible, but an operational ESRL of the proposed size is not considered achievable before the year 2020.

Rice, E. E.↗

Beamed-Energy Propulsion (BEP) Study

The scope of this study was to (1) review and analyze the state-of-art in beamed-energy propulsion (BEP) by identifying potential game-changing applications, (2) formulate a roadmap of technology development, and (3) identify key near-term technology demonstrations to rapidly advance elements of BEP technology to Technology Readiness Level (TRL) 6. The two major areas of interest were launching payloads and space propulsion. More generally, the study was requested and structured to address basic mission feasibility. The attraction of beamed-energy propulsion (BEP) is the potential for high specific impulse while removing the power-generation mass. The rapid advancements in high-energy beamed-power systems and optics over the past 20 years warranted a fresh look at the technology. For launching payloads, the study concluded that using BEP to propel vehicles into space is technically feasible if a commitment to develop new technologies and large investments can be made over long periods of time. From a commercial competitive standpoint, if an advantage of beamed energy for Earth-to-orbit (ETO) is to be found, it will rest with smaller, frequently launched payloads. For space propulsion, the study concluded that using beamed energy to propel vehicles from low Earth orbit to geosynchronous Earth orbit (LEO-GEO) and into deep space is definitely feasible and showed distinct advantages and greater potential over current propulsion technologies. However, this conclusion also assumes that upfront infrastructure investments and commitments to critical technologies will be made over long periods of time. The chief issue, similar to that for payloads, is high infrastructure costs.

Patrick George↗

Data fusion in predicting internal heat gains for office buildings through a deep learning approach

Heating, Ventilation, and Air Conditioning (HVAC) is a major energy consumer in buildings. The predictive control has demonstrated a potential to reduce HVAC energy use. To facilitate predictive HVAC control, internal heat gains prediction is required. Here, we applied Long Short-Term Memory Networks, a special form of deep neural network, to predict miscellaneous electric loads, lighting loads, occupant counts and internal heat gains in two United States office buildings. Compared with the predetermined schedules used in American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) standard 90.1, the Long Short-Term Memory Networks method could reduce the prediction errors of internal heat gains from 12% to 8% in Building A, and from 26% to 16% in Building B. It was also found that for internal heat gains prediction, miscellaneous electric loads is a more important feature than occupant counts for two reasons. First, miscellaneous electric loads is the best proxy variable for internal heat gains, as it is the major component of and has the highest correlation coefficient with the internal heat gains. Second, miscellaneous electric loads contain valuable information to predict occupant count, while occupant count could not help improve miscellaneous electric loads prediction. Lastly, these findings could help researchers and practitioners select the most relevant features to more accurately predict internal heat gains for the implementation of predictive HVAC control in buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Performance Analysis of Magnetohydrodynamic Drag Modulation for Actively Controlled Aerocapture at Neptune

While the Ice Giants are a top priority for flagship missions in the NASA’s near-term future, current technologies limit the scientific payload and mission timeline for future Uranian and Neptunian missions due to the need for fuel for orbit insertion maneuvers. Thus, to maximize the scientific potential of future missions, atmospheric aerocapture has been heavily researched. While atmospheric aerocapture simulations have proven enabling for capturing around Neptune, its deep atmospheric pass requires an aeroshell with robust thermal protection systems (TPS). Magnetohydrodynamically-controlled aerocapture serves as a potential solution to the limitations of both fully propulsive orbit insertion and aerodynamically controlled aerocapture. Through NASA Langley’s high-fidelity flight dynamics simulation, the Program to Optimize Simulated Trajectories II, both the aerodynamic-only and magnetohydrodynamic aerocapture methods were simulated and compared for identical missions to Neptune. After applying an optimized numerical predictor-corrector guidance algorithm for both methods, the results showed that magnetohydrodynamics has not only the control authority to successfully capture around Neptune, but also the unique advantage of a shallower atmospheric pass, decreasing the maximum heat load and the required TPS mass.

Danny N. Nguyen↗

Identification and genome reconstruction of abundant distinct taxa in microbiomes from one thermophilic and three mesophilic production-scale biogas plants

Biofuel production from conversion of biomass is indispensable in the portfolio of renewable energies. Complex microbial communities are involved in the anaerobic digestion process of plant material, agricultural residual products and food wastes. Analysis of the genetic potential and microbiology of communities degrading biomass to biofuels is considered to be the key to develop process optimisation strategies. Hence, due to the still incomplete taxonomic and functional characterisation of corresponding communities, new and unknown species are of special interest. Three mesophilic and one thermophilic production-scale biogas plants (BGPs) were taxonomically profiled using high-throughput 16S rRNA gene amplicon sequencing. All BGPs shared a core microbiome with the thermophilic BGP featuring the lowest diversity. However, the phyla Cloacimonetes and Spirochaetes were unique to BGPs 2 and 3, Fusobacteria were only found in BGP3 and members of the phylum Thermotogae were present only in the thermophilic BGP4. Taxonomic analyses revealed that these distinctive taxa mostly represent so far unknown species. The only exception is the dominant Thermotogae OTU featuring 16S rRNA gene sequence identity to Defluviitoga tunisiensis L3, a sequenced and characterised strain. To further investigate the genetic potential of the biogas communities, corresponding metagenomes were sequenced in a deepness of 347.5 Gbp in total. A combined assembly comprised 80.3 % of all reads and resulted in the prediction of 1.59 million genes on assembled contigs. Genome binning yielded genome bins comprising the prevalent distinctive phyla Cloacimonetes, Spirochaetes, Fusobacteria and Thermotogae. Comparative genome analyses between the most dominant Thermotogae bin and the very closely related Defluviitoga tunisiensis L3 genome originating from the same BGP revealed high genetic similarity. This finding confirmed applicability and reliability of the binning approach. The four highly covered genome bins of the other three distinct phyla showed low or very low genetic similarities to their closest phylogenetic relatives, and therefore indicated their novelty. In this study, the 16S rRNA gene sequencing approach and a combined metagenome assembly and binning approach were used for the first time on different production-scale biogas plants and revealed insights into the genetic potential and functional role of so far unknown species.

60 APPLIED LIFE SCIENCES↗

Genetically engineered poplar wood effectively enhances the efficiency of deep eutectic solvent-mediated one-pot processing

Although lignocellulosic biomass is a renewable resource with the potential to replace fossil-derived fuels and chemicals, its recalcitrance, largely due to lignin, limits its utilization. Recent advancements in genetic engineering have produced transgenic trees with reduced lignin content and/or modified lignin structure without compromising growth traits. Here, three engineered poplar varieties are evaluated as feedstocks using a biocompatible one-pot deep eutectic solvent-mediated process that integrates biomass fractionation and enzymatic saccharification within a single reactor, eliminating water washing and reconditioning. All transgenic poplars exhibit higher fermentable sugar yields than wild-type (WT) trees. Notably, QsuB poplar, incorporating 3,4-dihydroxybenzoate in lignin, achieves the highest glucose conversion yield of 91.3% (vs. 73.0% from WT). AT5 and MdCHS3 poplars, incorporating ferulate esters and naringenin, also demonstrate improved glucose yields (86.7 and 84.7%, respectively), confirming reduced biomass recalcitrance. Additionally, residual lignins are valorized via hydrogenolysis into phenolic compounds, with comparable alkylphenol production across all lines. These findings demonstrate that the transgenic poplar lines not only serve as superior feedstocks for sugar conversion but also provide a rich resource for phenolic compound production, enhancing the operational and economic viability of integrated biorefinery processes.

biomasses↗

Automated classification of big X-ray diffraction data using deep learning models

Abstract In current in situ X-ray diffraction (XRD) techniques, data generation surpasses human analytical capabilities, potentially leading to the loss of insights. Automated techniques require human intervention, and lack the performance and adaptability required for material exploration. Given the critical need for high-throughput automated XRD pattern analysis, we present a generalized deep learning model to classify a diverse set of materials’ crystal systems and space groups. In our approach, we generate training data with a holistic representation of patterns that emerge from varying experimental conditions and crystal properties. We also employ an expedited learning technique to refine our model’s expertise to experimental conditions. In addition, we optimize model architecture to elicit classification based on Bragg’s Law and use evaluation data to interpret our model’s decision-making. We evaluate our models using experimental data, materials unseen in training, and altered cubic crystals, where we observe state-of-the-art performance and even greater advances in space group classification.

Chemistry↗

Neurovascular Responses to Simulated Deep Space Radiation in a Human Organ-on-a-Chip Model

A major health risk for human deep space exploration is central nervous system (CNS) damage by galactic cosmic ray radiation. Simulated galactic cosmic rays or their components, especially the high-linear energy transfer (LET) particles such as 56Fe ions, have been shown to cause CNS damage, neuroinflammation and cognitive dysfunction in rodent models, but their effects on human CNS remain to be investigated. CNS damage from any insult, including ionizing radiation, is partially mediated by the blood-brain barrier (BBB), which regulates interactions between CNS and the rest of the body. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuroinflammation. However, there have been few studies on BBB and astrocyte functions in regulating CNS responses, especially in human tissue analogs. Therefore, we utilized a high-throughput 3D organ-on-a-chip system, seeded with human induced pluripotent stem cell-derived astrocytes and brain endothelial cells, or brain endothelial cells alone, to study human neurovascular responses to simulated deep space radiation. We investigated the permeability and morphology of vascular structures formed by endothelial cells, as well as oxidative stress and secreted cytokines and chemokine levels over 1-7 days after irradiation with 0.25 – 0.5 Gy 5-ion simplified simulated galactic cosmic rays or 0.3 – 0.8 Gy high-LET 600 MeV/n 56Fe particles, and compared the outcomes to low-LET X-ray irradiation. We observed that simulated deep space radiation caused delayed astrocyte activation in a pattern resembling CNS responses to brain injury, caused oxidative stress and the production of inflammatory cytokines, and compromised BBB integrity by damaging tight junctions, thus increasing vascular permeability. Furthermore, our results indicate that astrocytes have a dual role in regulating radiation responses: they exacerbate blood-brain barrier permeability early after irradiation, followed by switching to a more protective scar-like phenotype by reducing oxidative stress and pro-inflammatory cytokine and chemokine secretion. In a follow-up study using the same platform, we investigated the dose-rate effects of ionizing radiation, by exposing our model to chronic, low dose-rate, gamma radiation. Our model was significantly improved by adding additional cell types composing the BBB, modelling immune cell infiltration into the brain, and studying the effect of an antioxidant, to measure more complex outcomes and model more closely the effect of deep space radiation on the human BBB. In summary, our results present a human neurovascular model for space radiation studies and potential future automated payload adaptation, and suggest astrocyte regulatory mechanisms as targets for countermeasures to mitigate human neurovascular impairments during deep space exploration.

Ionizing radiation↗

Geochemistry Sampling for Traditional and Multicomponent Equilibrium Geothermometry in Southeast Idaho

The Eastern Snake River Plain (ESRP) is an area of high regional heat flux due the movement of the North American Plate over the Yellowstone Hotspot beginning ca.16 Ma. Temperature gradients between 45-60 °C/km (up to double the global average) have been calculated from deep wells that penetrate the upper aquifer system (Blackwell 1989). Despite the high geothermal potential, thermal signatures from hot springs and wells are effectively masked by the rapid flow of cold groundwater through the highly permeable basalts of the Eastern Snake River Plain aquifer (ESRPA) (up to 500+ m thick). This preliminary study is part of an effort to more accurately predict temperatures of the ESRP deep thermal reservoir while accounting for the effects of the prolific cold water aquifer system above. This study combines the use of traditional geothermometry, mixing models, and a multicomponent equilibrium geothermometry (MEG) tool to investigate the geothermal potential of the ESRP. In March, 2014, a collaborative team including members of the University of Idaho, the Idaho National Laboratory, and the Lawrence Berkeley National Laboratory collected 14 thermal water samples from and adjacent to the Eastern Snake River Plain. The preliminary results of chemical analyses and geothermometry applied to these samples are presented herein.

15 GEOTHERMAL ENERGY↗

A Deep Multimodal Representation Learning Framework for Accurate Molecular Properties Prediction

Drug discovery is a complex and challenging process, requiring the optimization of candidate compounds to identify those with the potential to become safe and effective drugs. Predicting molecular properties is an indispensable step in the drug discovery pipeline. Traditionally, this process is costly and time-intensive, involving multiple rounds of experiments and clinical trials, rendering it impractical for every candidate compound. Deep learning techniques have emerged as a promising approach to drug discovery to reduce the cost and time required to identify novel drugs. However, prevalent research in deep learning models focused on predicting molecular properties has primarily fixated on single-modal models, which utilize a single modality of data, neglecting the potential benefits of combining different data modalities. To overcome this limitation, we introduce MRL-Mol: a deep \textbf{M}ultimodal \textbf{R}epresentation \textbf{L}earning framework for accurate \textbf{Mol}ecular properties prediction. MRL-Mol harnesses three data modalities: sequence, graph, and image, augmenting the depth of comprehension. Leveraging a large-scale unlabeled dataset~($\sim$1M unique molecules), we pretrain MRL-Mol to extract inter- and intra-modal information. Our study demonstrates the superior performance of MRL-Mol in predicting molecular properties across six benchmark datasets, including both classification and regression tasks. Notably, MRL-Mol outperforms other state-of-the-art molecular properties prediction models. These findings suggest that by combining information from multiple data modalities, MRL-Mol can comprehend molecules better than single-modal deep learning models and identify molecular properties with better accuracy.

Yang, Yuxin↗

DLIO: A DATA-CENTRIC BENCHMARK FOR DEEP LEARNING APPLICATIONS

SF-22-136 Deep learning has been shown as a successful method for various tasks, and its popularity results in numerous open-source deep learning software tools. Deep learning has been applied to a broad spectrum of scientific domains such as cosmology, particle physics, computer vision, fusion, and astrophysics. Scientists have performed a great deal of work to optimize the computational performance of deep learning frameworks. However, the same cannot be said for I/O performance. As deep learning algorithms rely on big-data volume and variety to effectively train neural networks accurately, I/O is a significant bottleneck on large-scale distributed deep learning training. DLIO, is a novel representative benchmark suite built based on the I/O profiling of the selected workloads. DLIO can be utilized to accurately emulate the I/O behavior of modern deep learning applications. Using DLIO, application developers and system software solution architects can identify potential I/O bottlenecks in their applications and guide optimizations to boost the I/O performance leading to lower training times. The storage vendor can also use DLIO as a guide for designing and optimize the storage and filesystem targeting at deep learning application.

ZHENG, HUIHUO↗

Effects of low temperature periodic annealing on the deep-level defects in 200 keV proton irradiated AlGaAs-GaAs solar cells

The GaAs solar cell has shown good potential for space applications. However, degradation in performance occurred when the cells were irradiated by high energy electrons and protons in the space environment. The considered investigation is concerned with the effect of periodic thermal annealing on the deep-level defects induced by the 200 keV protons in the AlGaAs-GaAs solar cells. Protons at a fluence of 10 to the 11th P/sq cm were used in the irradiation cycle, while annealing temperatures of 200 C (for 24 hours), 300 C (six hours), and 400 C (six hours) were employed. The most likely candidate for the E(c) -0.71 eV electron trap observed in the 200 keV proton irradiated samples may be due to GaAs antisite, while the observed E(v) +0.18 eV hole trap has been attributed to the gallium vacancy related defect. The obtained results show that periodic annealing in the considered case does not offer any advantages over the one time annealing process.

Li, S. S.↗

Electrophysiology of the mammillary complex in vitro. I. Tuberomammillary and lateral mammillary neurons

1. The electrophysiological properties of the tuberomammillary and lateral mammillary neurons in the guinea pig mammillary body were studied using an in vitro brain slice preparation. 2. Tuberomammillary (n = 79) neurons were recorded mainly ventral to the lateral mammillary body as well as ventromedially to the fornix within the rostral part of the medial mammillary nucleus. Intracellular staining with horseradish peroxidase (n = 9) and Lucifer yellow (n = 3) revealed that these cells have several thick, long, spiny dendrites emerging from large (20-35 microns) fusiform somata. 3. Most tuberomammillary neurons (66%) fired spontaneously at a relatively low frequency (0.5-10 Hz) at the resting membrane potential. The action potentials were broad (2.3 ms) with a prominent Ca(2+)-dependent shoulder on the falling phase. Deep (17.8 mV), long-lasting spike afterhyperpolarizations were largely Ca(2+)-independent. 4. All tuberomammillary neurons recorded displayed pronounced delayed firing when the cells were activated from a potential negative to the resting level. The cells also displayed a delayed return to the baseline at the break of hyperpolarizing pulses applied from a membrane potential level close to firing threshold. Analysis of the voltage- and time dependence of this delayed rectification suggested the presence of a transient outward current similar to the A current (IA). These were not completely blocked by high concentrations of 4-aminopyridine, whereas the delayed onset of firing was always abolished when voltage-dependent Ca2+ conductances were blocked by superfusion with Cd2+. 5. Tuberomammillary neurons also displayed inward rectification in the hyperpolarizing and, primarily, depolarizing range. Block of voltage-gated Na(+)-dependent conductances with tetrodotoxin (TTX) selectively abolished inward rectification in the depolarizing range, indicating the presence of a persistent low-threshold sodium-dependent conductance (gNap). In fact, persistent TTX-sensitive, plateau potentials were always elicited following Ca2+ block with Cd2+ when K+ currents were reduced by superfusion with tetraethylammonium. 6. The gNap in tuberomammillary neurons may subserve the pacemaker current underlying the spontaneous firing of these cells. The large-amplitude spike afterhyperpolarization of these neurons sets the availability of the transient outward rectifier, which, in conjunction with the pacemaker current, establishes the rate at which membrane potential approaches spike threshold. 7. Repetitive firing elicited by direct depolarization enhanced the spike shoulder of tuberomammillary neurons. Spike trains were followed by a Ca(2+)-dependent, apamine-sensitive, slow afterhyperpolarization. 8. Lateral mammillary neurons were morphologically and electrophysiologically different from tuberomammillary neurons. All lateral mammillary neurons neurons recorded (n = 44) were silent at rest (-60 mV).(ABSTRACT TRUNCATED AT 400 WORDS).

Non-NASA Center↗

Fabrication Method for LOBSTER-Eye Optics in <110> Silicon

Soft x-ray optics can use narrow slots to direct x-rays into a desirable pattern on a focal plane. While square-pack, square-pore, slumped optics exist for this purpose, they are costly. Silicon (Si) is being examined as a possible low-cost replacement. A fabrication method was developed for narrow slots in <110> Si demonstrating the feasibility of stacked slot optics to replace micropores. Current micropore optics exist that have 20-micron-square pores on 26-micron pitch in glass with a depth of 1 mm and an extent of several square centimeters. Among several proposals to emulate the square pore optics are stacked slot chips with etched vertical slots. When the slots in the stack are positioned orthogonally to each other, the component will approach the soft x-ray focusing observed in the micropore optics. A specific improvement Si provides is that it can have narrower sidewalls between slots to permit greater throughput of x-rays through the optics. In general, Si can have more variation in slot geometry (width, length). Further, the sidewalls can be coated with high-Z materials to enhance reflection and potentially reduce the surface roughness of the reflecting surface. Narrow, close-packed deep slots in <110> Si have been produced using potassium hydroxide (KOH) etching and a patterned silicon nitride (SiN) mask. The achieved slot geometries have sufficient wall smoothness, as observed through scanning electron microscope (SEM) imaging, to enable evaluation of these slot plates as an optical element for soft x-rays. Etches of different angles to the crystal plane of Si were evaluated to identify a specific range of etch angles that will enable low undercut slots in the Si <110> material. These slots with the narrow sidewalls are demonstrated to several hundred microns in depth, and a technical path to 500-micron deep slots in a precision geometry of narrow, closepacked slots is feasible. Although intrinsic stress in ultrathin wall Si is observed, slots with walls approaching 1.5 microns can be achieved (a significant improvement over the 6-micron walls in micro - pore optics). The major advantages of this technique are the potential for higher x-ray throughout (due to narrow slot walls) and lower cost over the existing slumped micropore glass plates. KOH etching of smooth sidewalls has been demonstrated for many applications, suggesting its feasibility for implementation in x-ray optics. Si cannot be slumped like the micropore optics, so the focusing will be achieved with millimeter-scale slot plates that populate a spherical dome. The possibility for large-scale production exists for Si parts that is more difficult to achieve in micropore parts.

Chervenak, James↗