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DOE OSTI2023

SAS4A/SASSYS-1 Verification Testing for Sodium Fast Reactor Applications: Acceptance Testing Report

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

SAS4A/SASSYS-1 Verification Testing for Sodium Fast Reactor Applications (Acceptance Testing Report)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Status of Multiple Channel Fuel Performance Capabilities Within the SAS4A/SASSYS-1 Safety Analysis Software

SAS4A/SASSYS-1 (SAS) is a fast-running simulation tool used to perform deterministic analysis of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. It is a critical element of safety analysis capabilities for the U.S. Department of Energy and is utilized within industry to perform the transient safety analyses required to support the licensing of Liquid Metal-cooled Fast Reactors (LMFRs). Although SAS is exceptionally fast for most transient scenarios, fuel performance calculations, along with the associated pre-transient characterization of the fuel pin, may be required for transient scenarios where fuel pin failure is hypothesized. Both the pre-transient characterization and the transient fuel performance calculation are necessary to properly quantify margins to potential fuel failure and assess the time spent potentially exceeding such margins during events. While safety analysis calculations with fuel performance models provide a more detailed characterization of the reactor during a transient, the pre-transient characterization can be time-consuming and computationally expensive. Often, large numbers of fuel pins have been exposed to similar pre-transient irradiation conditions. Similarly, the same pre-transient fuel characterization may be applicable to numerous transient conditions. This provides an opportunity to optimize the SAS computational framework such that pre-transient fuel characterization can be shared across multiple channels (fuel pins) and across multiple simulations, thus dramatically reducing overall computational costs. This report summarizes progress toward enhancing the SAS computational framework to support shared, multiple channel fuel performance characterizations intended to significantly reduce computational costs. Preliminary testing has shown that the computational time saved by using the pre-transient sharing capability is approximately equal to the time it takes to perform the pre-transient characterization.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

SAS4A/SASSYS-1 Verification Testing for Sodium Fast Reactor Application: Acceptance Testing Report

AS4A/SASSYS-1 (SAS) is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. With its origin as SAS1A in the late 1960s, the SAS series of codes has been under continuous use and development for over sixty years and represents a critical investment in safety analysis capabilities for the U.S. Department of Energy. To support the dedication effort, this report has been generated to provide a detailed description of the available verification testing. The verification testing presented in this report captures functionality testing, focusing mainly on the testing of specific functions and algorithms for accuracy and precision of output, and interface testing, focusing mainly on the testing of critical input parameters and their valid ranges. Although SAS was developed to support the analysis of any liquid-metal-cooled nuclear reactor, the testing described in this document primarily focuses on the verification of SAS capabilities as they relate to a generic pool-type Sodium Fast Reactor (SFR).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Development and Implementation of a New AI-Based Tool to Support Fast Reactor Software Model Generation and Validation

This report summarizes FY26 work to develop Maggie, an artificial intelligence-based assistant designed to support software model generation and validation activities for fast reactor analysis codes. The project established a modular, code-agnostic software architecture that separates reusable agent capabilities from code-specific knowledge and tools, with initial implementation focused on the FRP-supported fast reactor safety analysis code SAS4A/SASSYS1 (SAS). A curated SAS-specific knowledge base was assembled from the code manual, training materials, historical analysis reports, and representative input files, and was integrated through retrieval-augmented generation to ground Maggie’s responses in authoritative sources. Maggie was deployed on the internal Argonne network, where it demonstrated practical user-facing capability as a chatbot for answering natural language questions about SAS and retrieving relevant technical information. Demonstration cases also showed that Maggie can generate useful snippets of SAS input for selected modeling tasks, while highlighting current limitations in reliability and consistency for more complex input generation tasks. Overall, the FY26 effort established the technical foundation for an AI-assisted capability intended to improve the efficiency, consistency, and accessibility of fast reactor software model development at Argonne and, with further improvements, to support eventual use by the broader fast reactor community, including industry users of FRP-supported analysis tools.

Thomas, Rachel [Argonne National Laboratory (ANL),↗

DOE OSTI2024

SAS4A/SASSYS-1 Modeling Improvements for the Transition to Natural Circulation

SAS4A/SASSYS-1 (SAS) is a simulation tool used to perform deterministic analyses of anticipated events as well as design basis and beyond design basis accidents for advanced liquid-metal-cooled nuclear reactors. With its origin as SAS1A in the late 1960s, the SAS series of codes has been under continuous use and development for over fifty years and represents a critical investment in safety analysis capabilities for the U.S. Department of Energy. In recent years, SAS has undergone a number of improvements to enable improved safety analyses that meet end users’ modernized needs while complying with the current regulatory environment. Improvements made in versions 5.6 and 5.7 released within the last year include the development of anisotropic Reynolds number dependent loss coefficients throughout the core and heat transport systems, the ability to distinguish the transition friction factor from the fully developed laminar and turbulent friction factors, and timedependent direct coolant and wall heating for pipe-like elements in the heat transport systems. While it was possible to capture loss coefficients, friction factors, and heat transfer from an element to a heat sink within SAS in previous versions of the code, users were required to end the simulation and restart it to adjust the input to account for any significant changes to the values during the transient. With these improvements, users can better capture flow reversal, pump heating, and the transition from forced to natural circulation without being limited to constant orifice coefficients, constant heat sinks, or the need to restart the simulation and modify input. In order to demonstrate the application of these improvements, a loss of flow transient is simulated for the Advanced Burner Test Reactor (ABTR).

SAS4A/SASSYS-1↗

DOE OSTI2020

High precision strike point control to support experiments in the DIII-D small angle slot divertor

Improvements in strike point control enabled tests with the new Small Angle Slot (SAS) divertor installed at DIII-D with precision as tight as ±1 mm, barring brief perturbations from ELMs. Aside from being narrower than previous baffle structures in DIII-D, simulations indicate that performance of the SAS divertor should be very sensitive to strike point position, making the improved strike point control essential for experiments with the SAS divertor. Improved control entails regulating more divertor geometry target locations than before and setting higher gain on the strike point target. This is achieved by tasking more poloidal field (PF) shaping coils with divertor topology control, fine tuning of the coil configuration and algorithm gains, and adding regulation of the power supply common rail. Here, the result is that although more variables are controlled, precision is better: high frequency jitter in the strike point position is lower on average compared to related discharges with standard divertor shape control.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

The effectiveness of D 2 pellet and gas injection in reducing intra-ELM tungsten erosion and heat flux in the DIII-D small angle slot divertor

Edge localized modes (ELMs) in H-mode plasmas can melt and erode plasma-facing components (PFCs) and lead to impurities in the core, reducing confinement. This study analyzes the use of D 2 pellet and gas injection for ELM mitigation on the DIII-D tokamak during the 2022 Small Angle Slot V-shaped Tungsten (W) (SAS-VW) divertor campaign, reducing W erosion and heat flux during ELMs. D α (656 nm) and WI (400.9 nm) filterscopes and Langmuir probes provide photon emission and electron density/temperature to estimate W atom erosion using the S/XB method, while surface eroding thermocouples measured ELM peak heat flux at the outer strike point (OSP). Thomson Scattering measurements of pedestal T e and n e provided input to predict W divertor erosion and heat flux during ELMs via the Free-Streaming plus Recycling Model (FSRM). While a greater D 2 mass injection rate decreased the ELM peak heat flux, the impact on W erosion was not monotonic. The average ‘large’ intra-ELM W erosion was lower for plasma shots with D 2 mass injection compared to the plasma shots without any D 2 mass injection in the SAS-VW divertor. However, plasma shots did not see significant changes in ‘large’ intra-ELM W divertor erosion as the D 2 mass injection rate increased. On average, the FSRM overestimated SAS-VW experimental intra-ELM W erosion by a factor of 6.9, but the overestimation is reduced to a factor of 3.6 with the implication of C deposition effects. Generally, experimentally measured and predicted quantities were worse for plasma shots with a lower D 2 mass injection rate and corresponding higher plasma carbon (C) impurity percentage (f C ). The discrepancies are postulated to be due to C/W material mixing, for which a simple analytic mixed-material model is presented. These results highlight the importance of incorporating and improving the robustness of a mixed-material layer model in the analysis of PFC erosion on present and future tokamak devices.

Carbon (C)↗

DOE OSTI2022

A scintillator attenuation spectrometer for intense gamma-rays

A new type of compact high-resolution high-sensitivity gamma-ray spectrometer for short-pulse intense gamma-rays (250 keV to 50 MeV) has been developed by combining the principles of scintillators and attenuation spectrometers. The first prototype of this scintillator attenuation spectrometer (SAS) was tested successfully in Trident laser experiments at LANL. Later versions have been used extensively in the Texas Petawatt laser experiments in Austin, TX, and more recently in OMEGA-EP laser experiments at LLE, Rochester, NY. The SAS is particularly useful for high-repetition-rate laser applications. Furthermore, we give a concise description of the design principles, capabilities, and sample preliminary results of the SAS.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Modeling plasma-induced surface charge effects on CO 2 activation by single atom catalysts supported on reducible and irreducible metal oxides

Abstract The accumulation of negative surface charge on catalytic surfaces in the presence of low-temperature plasma (LTP) could influence catalytic performance. However, it is difficult to disentangle the role of surface charging and other LTP catalytic effects in experiment. Herein, we use density functional theory (DFT) modeling to understand the effect of plasma-induced surface charging on CO 2 activation by atomically dispersed single atom (SA) catalysts on both reducible and irreducible metal oxide supports. We model CO 2 adsorption strength and CO 2 dissociation barriers for Co 1 , Ni 1 , Cu 1 , Rh 1 , Pd 1 , and Ag 1 SAs on both reducible and irreducible supports, namely, CeO 2 (100), TiO 2 (101), and γ -Al 2 O 3 (110), to elucidate trends. We find that accumulated surface charge on the SA increases the CO 2 adsorption strength and decreases the CO 2 dissociation barrier for all studied SA/support combinations. For both charged and uncharged (neutral) systems, SAs on the reducible CeO 2 (100) support generally adsorb CO 2 more weakly compared to when on irreducible supports like γ -Al 2 O 3 (110). SAs on γ -Al 2 O 3 (110) typically have larger barriers for CO 2 dissociation for both charged and uncharged systems compared to TiO 2 (101) and CeO 2 (100). The magnitude of surface charging effects on CO 2 binding energies and dissociation barriers depends sensitively on both the SA and the support. In some cases, the CO 2 activation trends qualitatively change between neutral and charged systems for a fixed SA across different supports. This DFT modeling study demonstrates that surface charging should be considered in strong electric fields because it can have a large effect on molecule adsorption and bond-breaking on catalytic surfaces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

First evidence of dominant influence of E × B drifts on plasma cooling in an advanced slot divertor for tokamak power exhaust

Addressing power exhaust in tokamaks is presently recognized as one of the major remaining open issues for the development of fusion reactors. At the forefront of this endeavor is the effort to develop an advanced divertor by maximizing dissipation of plasma power and momentum inside the divertor. Here, we demonstrate, for the first time, that the electromagnetic (E × B) drifts exert a key influence on plasma and gas dynamics in a new advanced slot divertor in the DIII-D tokamak, named the small angle slot (SAS). SAS leverages the effect of drifts to achieve a highly dissipative divertor with electron temperature T e ≲ 10 eV over a wide range of plasma densities, for ion B × ∇B away from the divertor, as used for advanced tokamak operation on DIII-D. Modeling with the SOLPS-ITER code shows that for this drift direction, the E × B flow carries particles toward the outer common flux region (CFR) via the private flux region (PFR), reinforcing neutral recycling and enhancing divertor dissipation. In contrast, for the opposite field direction, the E × B flow carries particles away from the outer CFR into the PFR, offsetting the anticipated SAS geometric effects. Furthermore, this finding is an important step in the understanding of the behavior of advanced divertors for achieving a power exhaust solution for fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Misalignment of magnetic field in DIII-D assessed by post-mortem analysis of divertor targets

Abstract We assess the toroidal magnetic field B t asymmetry in DIII-D due to a misalignment of the toroidal field coils with respect to the poloidal magnetic field coils and vacuum vessel. The peak-to-peak variation of the divertor strike point (SP) radius is measured to be 1 cm, with an n = 1 toroidal pattern. We use the centre of a narrow carbon deposition band on tungsten-coated divertor tiles just inside the outer strike point (OSP) as a proxy for the divertor SP location. The band occurred in a series of reverse B t discharges with the OSP positioned on the divertor inserts due to strong E × B drift transport of C from the inner to the outer SP through the private flux region. The variation in band radius (and hence the magnetic SP) is a (4.89 ± 0.31) mm shift toward (310 ± 4)° toroidal direction. These measurements agree well with previous measurements of the 3D magnetic field distribution (Luxon 2003 Nucl. Fusion 43 1813), simulations performed by the mafot field line integration code, and recent Langmuir probe measurements in the small-angle-slot (SAS) divertor (Watkins et al 2019 Nucl. Mater. Energy 18 46). Comparison of these measurements in the SAS divertor also indicates that there is the possibility of a tilt (in conjunction with the shift) of the B t coil field of (0.04 ± 0.07)° towards the toroidal angle of (215 ± 25)°. Previous measurements suggested a field misalignment of (4.6 ± 0.3) mm in the 270° toroidal direction, and a tilt of (0.06 ± 0.02)° toward the 114° toroidal direction, which is similar to the results reported here. These studies will be important for better understanding the radial variation of the toroidal strike line in DIII-D, for designing the new generation of SAS divertor, and for developing an understanding of the impact of error fields on tokamaks with tightly baffled slot divertors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Desmearing small-angle scattering data by central moment expansions

This article proposes a robust method for desmearing 1D small-angle scattering (SAS) intensity profiles. Using the central-moment-expansion technique, smearing in SAS intensity profiles is achieved in a model-free manner, eliminating the need for presumptive input during the desmearing. This innovative approach enables data analysis of SAS data without the resolution being convoluted with the structural model, thereby facilitating faster implementation and performance of fitting functions directly from the scattering models.

42 ENGINEERING↗

DOE OSTI2025

Desmearing small-angle scattering data by central moment expansions of instrument resolution

This study introduces an enhanced numerical technique tailored specifically for refining 1D small-angle scattering (SAS) intensity profiles affected by smearing. Our primary objective is to address the resolution blurring commonly encountered in SAS data, particularly in systems with clearly defined correlation peaks whose spread aligns with the width of the resolution function at corresponding Q positions. Unlike previous approaches that expanded the SAS intensity using central moment expansion, the new method focuses on expanding the resolution function itself, thus eliminating artificial oscillations observed in smeared spectra due to limitations inherent in our earlier algorithm. This method is straightforward to implement, computationally efficient and consistently performs well in numerical benchmarking. To illustrate its effectiveness, we present a case study of a lamellar phase characterized by distinct peaks in its small-angle neutron scattering intensities.

central moment expansions↗

DOE OSTI2022

A round-robin approach provides a detailed assessment of biomolecular small-angle scattering data reproducibility and yields consensus curves for benchmarking

Through an expansive international effort that involved data collection on 12 small-angle X-ray scattering (SAXS) and four small-angle neutron scattering (SANS) instruments, 171 SAXS and 76 SANS measurements for five proteins (ribonuclease A, lysozyme, xylanase, urate oxidase and xylose isomerase) were acquired. From these data, the solvent-subtracted protein scattering profiles were shown to be reproducible, with the caveat that an additive constant adjustment was required to account for small errors in solvent subtraction. Further, the major features of the obtained consensus SAXS data over the q measurement range 0–1 Å −1 are consistent with theoretical prediction. The inherently lower statistical precision for SANS limited the reliably measured q -range to <0.5 Å −1 , but within the limits of experimental uncertainties the major features of the consensus SANS data were also consistent with prediction for all five proteins measured in H 2 O and in D 2 O. Thus, a foundation set of consensus SAS profiles has been obtained for benchmarking scattering-profile prediction from atomic coordinates. Additionally, two sets of SAXS data measured at different facilities to q > 2.2 Å −1 showed good mutual agreement, affirming that this region has interpretable features for structural modelling. SAS measurements with inline size-exclusion chromatography (SEC) proved to be generally superior for eliminating sample heterogeneity, but with unavoidable sample dilution during column elution, while batch SAS data collected at higher concentrations and for longer times provided superior statistical precision. Careful merging of data measured using inline SEC and batch modes, or low- and high-concentration data from batch measurements, was successful in eliminating small amounts of aggregate or interparticle interference from the scattering while providing improved statistical precision overall for the benchmarking data set.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Secure mmWave Spectrum Sharing with Autonomous Beam Scheduling for 5G and Beyond

Spectrum Sharing (SS) has seen a renewed set of initiatives in 5G with the availability of shared and unlicensed spectrum bands that can be used by multiple cellular service providers and private cellular networks. Beam based transmission, instead of the traditional sector based transmission in conjunction with the spectrum agility of the 5G New Radio (NR) has brought new opportunities to optimized sharing of spectrum. Currently in the U.S., a centralized Spectrum Access Server (SAS) is used to co-ordinate spectrum sharing among networks sharing the same spectrum band. However, SAS becomes a focal point for security attacks and a performance bottleneck. In addition, SAS relies on an Environmental Sensor Network (ESN), separate from the 5G network. Without trusted spectral occupancy information, false reporting of spectrum sensing data can create sub-optimal and unfair spectrum usage. This paper summarizes our recent research findings in using a decentralized scheme for multiple networks to securely share spectrum with autonomous beam scheduling : 1) A new stochastic network framework based on Lyapunov Optimization approach is developed to optimize scheduling at the base stations; 2) Game theoretic (GT) approach is used to formulate the distributed scheduler; 3) Another distributed scheduler with Q-learning is presented that utilizes the Reinforcement Learning (RL) approach; 4) The performance and convergence rate of these distributed solutions to use shared and unlicensed spectrum are compared with existing solutions. Conditions under which the performance of these schedulers approach the theoretical upper bound, which is the performance possible with no interference among the operators sharing the spectrum, are presented; 5) The ability of a base station to use its own user equipment as sensors, for optimal spectrum sharing with base stations in other operator networks, is demonstrated to be an effective approach.

5G↗

DOE OSTI2020

Materials Data on AsS by Materials Project

SAs crystallizes in the triclinic P1 space group. The structure is zero-dimensional and consists of two $l^{1}-arsanylsulfanylarsenic molecules, two arsenic molecules, two arsinothious acid (9ci) molecules, two As4S5 clusters, one As5S7 cluster, and one SAs cluster. In each As4S5 cluster, there are four inequivalent As2+ sites. In the first As2+ site, As2+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.23 Å. In the second As2+ site, As2+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.31 Å. In the third As2+ site, As2+ is bonded in a distorted linear geometry to two S2- atoms. There are one shorter (2.38 Å) and one longer (2.85 Å) As–S bond lengths. In the fourth As2+ site, As2+ is bonded in an L-shaped geometry to two S2- atoms. There are one shorter (2.29 Å) and one longer (2.31 Å) As–S bond lengths. There are five inequivalent S2- sites. In the first S2- site, S2- is bonded in a distorted bent 120 degrees geometry to one As2+ and one S2- atom. The S–S bond length is 2.00 Å. In the second S2- site, S2- is bonded in a bent 120 degrees geometry to two As2+ atoms. In the third S2- site, S2- is bonded in a water-like geometry to one As2+ and one S2- atom. The S–S bond length is 2.03 Å. In the fourth S2- site, S2- is bonded in a distorted L-shaped geometry to one As2+ and one S2- atom. In the fifth S2- site, S2- is bonded in a distorted water-like geometry to one As2+ and one S2- atom. In the As5S7 cluster, there are five inequivalent As2+ sites. In the first As2+ site, As2+ is bonded in an L-shaped geometry to two S2- atoms. There are one shorter (2.27 Å) and one longer (2.41 Å) As–S bond lengths. In the second As2+ site, As2+ is bonded in a distorted single-bond geometry to two S2- atoms. There are one shorter (2.35 Å) and one longer (2.98 Å) As–S bond lengths. In the third As2+ site, As2+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.30 Å. In the fourth As2+ site, As2+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.31 Å. In the fifth As2+ site, As2+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.35 Å. There are seven inequivalent S2- sites. In the first S2- site, S2- is bonded in a distorted bent 120 degrees geometry to one As2+ and one S2- atom. The S–S bond length is 1.99 Å. In the second S2- site, S2- is bonded in a distorted water-like geometry to one As2+ and one S2- atom. The S–S bond length is 2.04 Å. In the third S2- site, S2- is bonded in a water-like geometry to one As2+ and one S2- atom. In the fourth S2- site, S2- is bonded in a bent 120 degrees geometry to one As2+ and one S2- atom. The S–S bond length is 2.01 Å. In the fifth S2- site, S2- is bonded in a distorted water-like geometry to one As2+ and one S2- atom. In the sixth S2- site, S2- is bonded in a 3-coordinate geometry to two As2+ and one S2- atom. The S–S bond length is 2.18 Å. In the seventh S2- site, S2- is bonded in a water-like geometry to two S2- atoms. In the SAs cluster, there are three inequivalent As2+ sites. In the first As2+ site, As2+ is bonded in an L-shaped geometry to two S2- atoms. There are one shorter (2.29 Å) and one longer (2.32 Å) As–S bond lengths. In the second As2+ site, As2+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.30 Å. In the third As2+ site, As2+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.23 Å. There are three inequivalent S2- sites. In the first S2- site, S2- is bonded in a bent 120 degrees geometry to two As2+ atoms. In the second S2- site, S2- is bonded in a distorted water-like geometry to one As2+ and one S2- atom. The S–S bond length is 2.03 Å. In the third S2- site, S2- is bonded in a distorted water-like geometry to one As2+ and one S2- atom.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Materials Data on As12S13 by Materials Project

As(SAs)9As14S17 crystallizes in the triclinic P1 space group. The structure is zero-dimensional and consists of one arsenic molecule, one As14S17 cluster, and one SAs cluster. In the As14S17 cluster, there are fourteen inequivalent As+2.17+ sites. In the first As+2.17+ site, As+2.17+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.19 Å. In the second As+2.17+ site, As+2.17+ is bonded in a trigonal non-coplanar geometry to three S2- atoms. There are a spread of As–S bond distances ranging from 2.27–2.35 Å. In the third As+2.17+ site, As+2.17+ is bonded in a water-like geometry to two S2- atoms. There are one shorter (2.34 Å) and one longer (2.36 Å) As–S bond lengths. In the fourth As+2.17+ site, As+2.17+ is bonded in an L-shaped geometry to two S2- atoms. There are one shorter (2.28 Å) and one longer (2.62 Å) As–S bond lengths. In the fifth As+2.17+ site, As+2.17+ is bonded in an L-shaped geometry to two S2- atoms. There are one shorter (2.24 Å) and one longer (2.39 Å) As–S bond lengths. In the sixth As+2.17+ site, As+2.17+ is bonded in a T-shaped geometry to three S2- atoms. There are a spread of As–S bond distances ranging from 2.24–2.70 Å. In the seventh As+2.17+ site, As+2.17+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.25 Å. In the eighth As+2.17+ site, As+2.17+ is bonded in a water-like geometry to two S2- atoms. There are one shorter (2.31 Å) and one longer (2.33 Å) As–S bond lengths. In the ninth As+2.17+ site, As+2.17+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.26 Å. In the tenth As+2.17+ site, As+2.17+ is bonded in a distorted single-bond geometry to one S2- atom. The As–S bond length is 2.45 Å. In the eleventh As+2.17+ site, As+2.17+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.36 Å. In the twelfth As+2.17+ site, As+2.17+ is bonded in a 3-coordinate geometry to three S2- atoms. There are a spread of As–S bond distances ranging from 2.07–2.97 Å. In the thirteenth As+2.17+ site, As+2.17+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.37 Å. In the fourteenth As+2.17+ site, As+2.17+ is bonded in a water-like geometry to two S2- atoms. There are one shorter (2.10 Å) and one longer (2.43 Å) As–S bond lengths. There are seventeen inequivalent S2- sites. In the first S2- site, S2- is bonded in a single-bond geometry to one As+2.17+ atom. In the second S2- site, S2- is bonded in a single-bond geometry to one As+2.17+ atom. In the third S2- site, S2- is bonded in a distorted single-bond geometry to one S2- atom. The S–S bond length is 1.98 Å. In the fourth S2- site, S2- is bonded in a distorted water-like geometry to one As+2.17+ and one S2- atom. The S–S bond length is 2.03 Å. In the fifth S2- site, S2- is bonded in a distorted water-like geometry to one As+2.17+ and one S2- atom. In the sixth S2- site, S2- is bonded in a bent 120 degrees geometry to two As+2.17+ atoms. In the seventh S2- site, S2- is bonded in a bent 120 degrees geometry to two As+2.17+ atoms. In the eighth S2- site, S2- is bonded in a distorted water-like geometry to one As+2.17+ and one S2- atom. The S–S bond length is 2.01 Å. In the ninth S2- site, S2- is bonded in a 3-coordinate geometry to two As+2.17+ and one S2- atom. The S–S bond length is 2.07 Å. In the tenth S2- site, S2- is bonded in a distorted single-bond geometry to one As+2.17+ and one S2- atom. In the eleventh S2- site, S2- is bonded in a 1-coordinate geometry to one As+2.17+ and one S2- atom. In the twelfth S2- site, S2- is bonded in a 3-coordinate geometry to three As+2.17+ atoms. In the thirteenth S2- site, S2- is bonded in a distorted water-like geometry to one As+2.17+ and one S2- atom. The S–S bond length is 2.01 Å. In the fourteenth S2- site, S2- is bonded in a distorted L-shaped geometry to two As+2.17+ atoms. In the fifteenth S2- site, S2- is bonded in a 3-coordinate geometry to two As+2.17+ and one S2- atom. In the sixteenth S2- site, S2- is bonded in a 3-coordinate geometry to three As+2.17+ atoms. In the seventeenth S2- site, S2- is bonded in a distorted water-like geometry to one As+2.17+ and one S2- atom. In the SAs cluster, there are nine inequivalent As+2.17+ sites. In the first As+2.17+ site, As+2.17+ is bonded in a water-like geometry to two S2- atoms. There are one shorter (2.21 Å) and one longer (2.43 Å) As–S bond lengths. In the second As+2.17+ site, As+2.17+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 3.05 Å. In the third As+2.17+ site, As+2.17+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.28 Å. In the fourth As+2.17+ site, As+2.17+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.30 Å. In the fifth As+2.17+ site, As+2.17+ is bonded in a water-like geometry to two S2- atoms. There are one shorter (2.26 Å) and one longer (2.41 Å) As–S bond lengths. In the sixth As+2.17+ site, As+2.17+ is bonded in an L-shaped geometry to two S2- atoms. There are one shorter (2.28 Å) and one longer (2.33 Å) As–S bond lengths. In the seventh As+2.17+ site, As+2.17+ is bonded in a single-bond geometry to one S2- atom. The As–S bond length is 2.22 Å. In the eighth As+2.17+ site, As+2.17+ is bonded in a water-like geometry to two S2- atoms. There are one shorter (2.27 Å) and one longer (2.33 Å) As–S bond lengths. In the ninth As+2.17+ site, As+2.17+ is bonded in a bent 150 degrees geometry to two S2- atoms. There are one shorter (2.41 Å) and one longer (2.58 Å) As–S bond lengths. There are nine inequivalent S2- sites. In the first S2- site, S2- is bonded in an L-shaped geometry to two As+2.17+ atoms. In the second S2- site, S2- is bonded in a 2-coordinate geometry to two As+2.17+ atoms. In the third S2- site, S2- is bonded in a distorted L-shaped geometry to one As+2.17+ and one S2- atom. The S–S bond length is 2.02 Å. In the fourth S2- site, S2- is bonded in a 1-coordinate geometry to two As+2.17+ and one S2- atom. The S–S bond length is 2.06 Å. In the fifth S2- site, S2- is bonded in a water-like geometry to one As+2.17+ and one S2- atom. In the sixth S2- site, S2- is bonded in a distorted trigonal non-coplanar geometry to three As+2.17+ atoms. In the seventh S2- site, S2- is bonded in a distorted water-like geometry to one As+2.17+ and one S2- atom. In the eighth S2- site, S2- is bonded in a distorted water-like geometry to one As+2.17+ and one S2- atom. The S–S bond length is 2.07 Å. In the ninth S2- site, S2- is bonded in a distorted water-like geometry to one As+2.17+ and one S2- atom.

36 MATERIALS SCIENCE↗