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Developing theoretical understanding of complex reactions and processes at interfaces requires using methods that go beyond semilocal density functional theory to accurately describe the interactions between solvent, reactants and substrates. Methods based on many-body perturbation theory, such as the random phase approximation (RPA), have previously been limited due to their computational complexity. However, this is now a surmountable barrier due to the advances in computational power available, in particular through modern GPU-based supercomputers. In this work, we describe the implementation of RPA calculations within BerkeleyGW and show its favorable computational performance on large complex systems relevant for catalysis and electrochemistry applications. Our implementation builds off of the static subspace approximation which, by employing a compressed representation of the frequency dependent polarizability, enables the evaluation of the RPA correlation energy with significant acceleration and systematically controllable accuracy. We find that the computational cost of calculating the RPA correlation energy scales only linearly with system size for systems containing up to 50 thousand bands, and is expected to scale quadratically thereafter. We also show excellent strong scaling results across several supercomputers, demonstrating the performance and portability of this implementation., Comment: 10 pages, 5 figures

We present BEAST DB, an open-source database comprised of ab initio electrochemical data computed using grand-canonical density functional theory in implicit solvent at consistent calculation parameters. The database contains over 20,000 surface calculations and covers a broad set of heterogeneous catalyst materials and electrochemical reactions. Calculations were performed at self-consistent fixed potential as well as constant charge to facilitate comparisons to the computational hydrogen electrode. This article presents common use cases of the database to rationalize trends in catalyst activity, screen catalyst material spaces, understand elementary mechanistic steps, analyze electronic structure, and train machine learning models to predict higher fidelity properties. Users can interact graphically with the database by querying for individual calculations to gain granular understanding of reaction steps or by querying for an entire reaction pathway on a given material using an interactive reaction pathway tool. BEAST DB will be periodically updated, with planned future updates to include advanced electronic structure data, surface speciation studies, and greater reaction coverage., Comment: 24 pages, 8 figures

Polymers are an effective test-bed for studying topological constraints in condensed matter due to a wide array of synthetically-available chain topologies. When linear and ring polymers are blended together, emergent rheological properties are observed as the blend can be more viscous than either of the individual components. This emergent behavior arises since ring-linear blends can form long-lived topological constraints as the linear polymers thread the ring polymers. Here, we demonstrate how the Gauss linking integral can be used to efficiently evaluate the relaxation of topological constraints in ring-linear polymer blends. For majority-linear blends, the relaxation rate of topological constraints depends primarily on reptation of the linear polymers, resulting in the diffusive time $\tau_{d,R}$ for rings of length $N_R$ blended with linear chains of length $N_l$ to scale as $\tau_{d,R}\sim N_R^2N_L^{3.4}$., Comment: 6 pages, 6 figures

Nanoflares are thought to be one of the prime candidates that can heat the solar corona to its multi-million kelvin temperature. Individual nanoflares are difficult to detect with the present generation instruments, however their presence can be inferred by comparing simulated nanoflare-heated plasma emissions with the observed emission. Using HYDRAD coronal loop simulations, we model the emission from an X-ray bright point (XBP) observed by the Marshall Grazing Incidence X-ray Spectrometer (MaGIXS), along with nearest-available observations from the Atmospheric Imaging Assembly (AIA) onboard Solar Dynamics Observatory (SDO) and X-Ray Telescope (XRT) onboard Hinode observatory. The length and magnetic field strength of the coronal loops are derived from the linear-force-free extrapolation of the observed photospheric magnetogram by Helioseismic and Magnetic Imager (HMI) onboard SDO. Each loop is assumed to be heated by random nanoflares, whose magnitude and frequency are determined by the loop length and magnetic field strength. The simulation results are then compared and matched against the measured intensity from AIA, XRT, and MaGIXS. Our model results indicate the observed emissions from the XBP under study could be well matched by a distribution of nanoflares with average delay times 1500 s to 3000 s, which suggest that the heating is dominated by high-frequency events. Further, we demonstrate the high sensitivity of MaGIXS and XRT to diagnose the heating frequency using this method, while AIA passbands are found to be the least sensitive., Comment: Accepted for publication in the Astrophysical Journal (ApJ)

The COVID-19 virus brought on a public health emergency that massively disrupted school systems and learning nationwide. During the 2020-2021 school year, many local education agencies (LEAs) in Pennsylvania and other states adopted remote learning to help slow the virus's spread. However, remote learning came with challenges for students, families, and LEAs. These challenges included very practical ones like not having a reliable internet connection or the correct link to log into classes, as well as fatigue from so many remote meetings and feelings of social isolation. This brief examines remote learning in Pennsylvania and its role in shaping education outcomes and COVID-19 case rates in local communities during the 2020-2021 school year. Key findings for the 2020-2021 school year: (1) Vulnerable groups of students were more likely than students overall to attend LEAs where the predominant instructional modes included remote learning; (2) The same groups of students were also more likely to be in LEAs where larger shares of the student population had trouble accessing reliable internet; (3) More remote learning was associated with lower assessment performance in grades 5-8, especially in schools with higher levels of economic disadvantage. It was also associated with lower suspension rates in grades 6-12 and did not appear to harm or help graduation rates; and (4) Remote learning in high school was associated with lower subsequent COVID-19 rates within an LEA's boundary, suggesting it had an important public health benefit. [Contributions from Candy Miller, Rhonda Johnson, and Rosemary Riccardo.]

This report, the fifth in the "On Shared Equity Leadership series," explores ways to build capacity for the work of shared equity leadership (SEL) in higher education. SEL is a leadership approach that scales diversity, equity, and inclusion (DEI) work and creates culture change by connecting individual and organizational transformation. Capacity-building efforts help leaders develop a repertoire of knowledge, skills, and dispositions to collectively lead equity-minded change efforts on campus. To create environments where SEL can thrive, campuses need to build capacity for both shared leadership and DEI. This distinction is important because shared leadership capacity building involves working and leading collaboratively, whereas capacity building for DEI is more focused on the knowledge, skills, and critical consciousness necessary to make progress toward DEI-related goals. Additionally, capacity for SEL must be built at multiple levels--the personal or individual level, the collective or team level, and the organizational level. The report identifies distinct strategies for building capacity at each level and indicates whether they can build capacity for shared leadership, DEI, or both.

The COVID-19 pandemic raised concerns about the possibility of increased staff attrition from the public school sector, as it did for other occupations during the Great Resignation that followed the pandemic's onset. Recruiting and retaining education staff were pressing challenges even before the pandemic began. Since March 2020, education staff have needed to adapt to new job expectations and risk exposure to an unknown virus. These factors might have contributed to staff leaving public education jobs due to mental and physical health concerns and other issues. This research brief describes staff attrition during the pandemic from Pennsylvania local education agencies (LEAs). The brief describes annual rates of staff leaving the statewide public school sector from several jobs--including teachers, health and counseling staff, school administrators, and LEA administrators--and how changes in attrition during the pandemic varied with staff, school, and LEA characteristics. Key findings for teachers, health and counseling staff, and administrators include: (1) five percent of staff working in Pennsylvania local education agencies (LEAs) in fall 2020 left the statewide public school sector by fall 2021, an increase from 4 percent attrition in preceding years; (2) pre-pandemic attrition rates for staff of color were generally higher than for non-Hispanic White staff, and these differences grew during the pandemic except for school administrators, where they narrowed; and (3) gaps in attrition rates were also exacerbated during the pandemic for teachers and health and counseling staff early in their careers and in charter schools and for LEA administrators in large LEAs. [This brief includes contributions from Candy Miller, Rhonda Johnson, and Rosemary Riccardo.]

The disruptions to schooling created by the COVID-19 pandemic prompted nationwide concern about negative impacts on academic proficiency, particularly for vulnerable student populations. Pennsylvania's 2021 statewide assessments offered the first opportunity since the pandemic began to assess how students across the Commonwealth were faring, whether achievement gaps had widened, and how remote learning affected student performance. As in other states, the raw assessment data did not tell the full story of the pandemic's impacts on academic proficiency. Fewer Pennsylvania students participated in the 2021 assessments than in prior years, and test takers were not a representative sample of all students. In addition, test administration dates varied widely across the state in 2021, with some local education agencies (LEAs) postponing the usual spring assessments to the fall. Using a predictive model that accounts for the unique assessment issues in 2021 and the instructional modes that Pennsylvania LEAs offered, this research brief provides a fuller picture of the pandemic's impacts on academic proficiency in grades 5 through 8. Key findings for Pennsylvania students in grades 5 through 8 include: (1) students in vulnerable groups and in fully remote learning had lower assessment participation rates than other students in 2021; (2) the pandemic led to a substantial reduction in academic proficiency statewide in 2021, reducing academic achievement even more than the results for tested students indicated (3) the pandemic had consistently large negative academic effects across student groups, including for vulnerable groups that had low rates of proficiency before the pandemic; and (4) LEAs that were fully remote after winter break saw lower proficiency rates in 2021, compared with LEAs that offered fully in-person learning to similar students. [This brief includes contributions from Candy Miller, Rhonda Johnson, and Rosemary Riccardo.]

We present a model for atmospheric absorption of solar ultraviolet (UV) radiation. The initial motivation for this work is to predict this effect and correct it in Sounding Rocket (SR) experiments. In particular, the Full-sun Ultraviolet Rocket Spectrograph (FURST) is anticipated to launch in mid-2023. FURST has the potential to observe UV absorption while imaging solar spectra between 120-181 nm, at a resolution of R > 2x10$^4$ ($\Delta$ V < $\pm$ 15 km/s), and at altitudes of between 110-255 km. This model uses estimates for density and temperature, as well as laboratory measurements of the absorption cross-section, to predict the UV absorption of solar radiation at high altitudes. Refraction correction is discussed and partially implemented but is negligible for the results presented. Absorption by molecular Oxygen is the primary driver within the UV spectral range of our interest. The model is built with a wide range of applications in mind. The primary result is a method for inversion of the absorption cross-section from images obtained during an instrument flight, even if atmospheric observations were not initially intended. The potential to obtain measurements of atmospheric properties is an exciting prospect, especially since sounding rockets are the only method currently available for probing this altitude in situ. Simulation of noisy spectral images along the FURST flight profile is performed using data from the High-Resolution Telescope and Spectrograph (HRTS) SR and the FISM2 model for comparison. Analysis of these simulated signals allows us to capture the Signal-to-Noise Ratio (SNR) of FURST and the capability to measure atmospheric absorption properties as a function of altitude. Based on the prevalence of distinct spectral features, our calculations demonstrate that atmospheric absorption may be used to perform wavelength calibration from in-flight data., Comment: To be Published in JPCS. Submitted December 2022. Accepted February 2023

Hybrid lead halide perovskites (LHPs) are a class of semiconductor with novel properties that are distinctively governed by structural fluctuations. Diffraction experiments sensitive to average, long-range order reveal a cubic structure in the device-relevant, high-temperature phase. Local probes find additional short-range order with lower symmetry that may govern the structure-function relationships of LHPs. However, the dimensionality, participating atoms, and dynamics of this short-range order are unresolved, impeding our understanding of technologically relevant properties including long carrier lifetimes and facile halide migration. Here, we determine the true structure of two prototypical hybrid LHPs, CH$_3$NH$_3$PbI$_3$ and CH$_3$NH$_3$PbBr$_3$, using a combination of single-crystal X-ray and neutron diffuse scattering, neutron inelastic spectroscopy, and molecular dynamics simulations. The remarkable collective dynamics we found are not suggested by previous studies and consist of a network of local two-dimensional, circular pancake-like regions of dynamically tilting lead halide octahedra (lower symmetry) that induce longer range intermolecular correlations within the CH$_3$NH$_3^+$ sublattice. The dynamic local structure can introduce transient ferroelectric or antiferroelectric domains that increase charge carrier lifetimes, and strongly affect the halide migration, a poorly understood degradation mechanism. Our approach of co-analyzing single-crystal X-ray and neutron diffuse scattering data with MD simulations will provide unparalleled insights into the structure of hybrid materials and materials with engineered disorder.

In this report, the second in the On Shared Equity Leadership series, we highlight four distinct ways to structure Shared Equity Leadership (SEL) that we observed from our participating institutions. We lay the groundwork for understanding these structures by first describing some of the more common or traditional ways that diversity leadership has been structured in higher education, followed by a brief overview of shared leadership structures and then a detailed analysis of the four SEL models. We conclude with examples that show how institutions can reward and incentivize the development of these models. [Jordan Harper contributed to this study and report.]

In this report, the fourth in the "On Shared Equity Leadership series," the authors describe the ways that leaders in different campus roles contribute to shared equity leadership (SEL) efforts. SEL is a leadership approach that scales diversity, equity, and inclusion (DEI) work and creates culture change by connecting individual and organizational transformation. Individuals embrace a personal journey toward critical consciousness to become equity-oriented leaders. Collectively, leaders embody a set of values and enact a set of practices that form new relationships and understandings, ultimately working to dismantle current systems and structures that inhibit equitable outcomes. This report examines roles from both a functional perspective (e.g., faculty, student affairs, and DEI-specific roles) and from a positional view (e.g., senior-level, mid-level, and groundlevel leaders), and it highlights the ways in which different values and practices are especially important for leaders in particular roles.

The Marshall Grazing Incidence X-ray Spectrometer (MaGIXS) sounding rocket experiment launched on July 30, 2021 from the White Sands Missile Range in New Mexico. MaGIXS is a unique solar observing telescope developed to capture X-ray spectral images, in the 6 - 24 Angstrom wavelength range, of coronal active regions. Its novel design takes advantage of recent technological advances related to fabricating and optimizing X-ray optical systems as well as breakthroughs in inversion methodologies necessary to create spectrally pure maps from overlapping spectral images. MaGIXS is the first instrument of its kind to provide spatially resolved soft X-ray spectra across a wide field of view. The plasma diagnostics available in this spectral regime make this instrument a powerful tool for probing solar coronal heating. This paper presents details from the first MaGIXS flight, the captured observations, the data processing and inversion techniques, and the first science results., Comment: 20 pages, 18 figures

Any pair of consecutive B-smooth integers for a given smoothness bound B corresponds to a solution (x, y) of the equation x^2 - 2Dy^2 = 1 for a certain square-free, B-smooth integer D and a B-smooth integer y. This paper describes algorithms to find such twin B-smooth integers that lie in a given interval by using the structure of solutions of the above Pell equation. The problem of finding such twin smooth integers is motivated by the quest for suitable parameters to efficiently instantiate recent isogeny-based cryptosystems. While the Pell equation structure of twin B-smooth integers has previously been used to describe and compute the full set of such pairs for very small values of B, increasing B to allow for cryptographically sized solutions makes this approach utterly infeasible. We start by revisiting the Pell solution structure of the set of twin smooth integers. Instead of using it to enumerate all twin smooth pairs, we focus on identifying only those that lie in a given interval. This restriction allows us to describe algorithms that navigate the vast set of Pell solutions in a more targeted way. Experiments run with these algorithms have provided examples of twin B-smooth pairs that are larger and have smaller smoothness bound B than previously reported pairs. Unfortunately, those examples do not yet provide better parameters for cryptography, but we hope that our methods can be generalized or used as subroutines in future work to achieve that goal.