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AuBr crystallizes in the tetragonal P4_2/ncm space group. The structure is one-dimensional and consists of two AuBr ribbons oriented in the (1, 1, 0) direction. Au1+ is bonded in a linear geometry to two equivalent Br1- atoms. Both Au–Br bond lengths are 2.49 Å. Br1- is bonded in a distorted L-shaped geometry to two equivalent Au1+ atoms.
AuBr crystallizes in the tetragonal I4_1/amd space group. The structure is one-dimensional and consists of four AuBr ribbons oriented in the (1, 0, 0) direction. Au1+ is bonded in a linear geometry to two equivalent Br1- atoms. Both Au–Br bond lengths are 2.45 Å. Br1- is bonded in a water-like geometry to two equivalent Au1+ atoms.
The removal of vacancy-related defects by addition of AuBr3 to the melt during crystal growth impacts the performance of BaBr2:Eu and Cs2LiLaBr6:Ce very differently.
The metalation chemistry of the phlorin, which is a non-aromatic tetrapyrrole macrocycle containing a single sp 3 -hybridized meso-carbon has remained underdeveloped, as compared to that of more traditional tetrapyrroles such as porphyrins, corroles and phthalocyanines. There have been few prior efforts to prepare metallophlorins, and those that have been reported have relied on either reduction or nucleophilic attack of parent metalloporphyrins, rather than direct metalation of freebase phlorin constructs. In this work, an alternate synthetic approach for preparation of gold(III) phlorin complexes that involves the first direct metalation of two different freebase phlorin derivatives (3H(Phl tBu ) and 3H(Phl F )) with AuBr 3 to produce the stable and fully isolable gold(III) phlorin complexes Au(Phl tBu ) and Au(Phl F ) is reported. The first structural characterization of a metallophlorin bearing geminal dimethyl substituents at the sp 3 -hybridized meso-carbon via X-ray crystallography is also reported. In addition to the preparation of Au(Phl tBu ) and Au(Phl F ), the UV-vis absorption and redox properties of these two gold(III) phlorins in comparison to those of their freebase homologues is also detailed. Notably, the metallophlorins are characterized by panchromatic absorbance profiles and intense and broad bands that span the long-visible and into the near-IR regions, as well as two fully reversible oxidation and reduction waves as probed by cyclic voltammetry. Lastly, the chlorination of Au(Phl tBu ) using PhI(Cl 2 ) was probed and it was found that this regioslective reaction generates monochlorinated (Au(Phl tBu Cl)) and dichlorinated (Au(Phl tBu Cl 2 )) products, which were both structurally characterized by X-ray crystallography.
AuBrO2 crystallizes in the monoclinic C2/c space group. The structure is one-dimensional and consists of four hydrogen peroxide molecules and two AuBr ribbons oriented in the (1, 0, 1) direction. In each AuBr ribbon, Au5+ is bonded in a linear geometry to two equivalent Br1- atoms. Both Au–Br bond lengths are 2.51 Å. Br1- is bonded in a 4-coordinate geometry to two equivalent Au5+ atoms.
Enstatite meteorites are identified by their extremely reduced mineralogy (1) and similar oxygen isotope composition (2). The enstatite meteorite clan incorporates both EH and EL chondrites, as well as a wide variety of enstatite achondrites, such as aubrites or anomalous enstatite meteorites (e.g. Mt. Egerton, Shallowater, Zaklodzie, NWA 2526). The role of nebular versus planetary processes in the formation of enstatite meteorites is still under debate (e.g. 3-5). Past studies showed a significant influence of metal segregation in the formation of enstatite achondrites. Casanova et al. (6) suggested incomplete metal-silicate segregation during core formation and attributed the unfractionated siderophile element patterns in aubrites metals to a lack of fractional crystallization in a planetary core. Recent studies suggest a significant role of impact melting in the formation of primitive enstatite chondrites (7) and identified NWA 2526 as a partial melt residue of an enstatite chondrite (8). To understand the nature of siderophile element-bearing phases in enstatite achondrites, establish links between enstatite achondrites and enstatite chondrites (9), and constrain planetary differentiation on their respective parent bodies and their petrogenetic histories, we present laser ablation ICP-MS measurements of metal and sulfide phases in Shallowater, Mt. Egerton, and the aubrites Aubres, Cumberland Falls, and Mayo Belwa.
During a natural disaster such as Hurricane Melissa, understanding where people are located is critical for situational awareness, operational planning and humanitarian support and consequence assessment. Traditional population datasets focus on mapping populations based on residential, or "business-as-usual" scenarios. However, natural disasters can create disruptions in daily routines of population in addition to the magnitude of the population displacement, depending on the type, duration, context, and location of the event. The Geospatial Science and Human Security Division at Oak Ridge National Laboratory (ORNL) produced this latest LandScan Mosaic Rapid Population Update for Jamaica following Hurricane Melissa, a category 5 hurricane that made landfall on Jamaica on October 28 2025. This Rapid Population Update captures the immediate population displacement following the hurricane using a combination of open-source building damage assessment data from Microsoft, flood exposure data from the Global Flood Monitoring service, reported population displacement information, and humanitarian shelter locations from the Jamaican Office of Disaster Preparedness and Emergency Management and the underlying LandScan Mosaic Jamaica as a base population.
For a quarter of a century, the LandScan Global (LSG) project has annually released a global, high-resolution gridded population dataset representing the ambient or unwarned population at a 30 arcsecond resolution. LSG supports a range of applications such as emergency management, disaster response, and human health and security for understanding populations at risk. The 2023 release of LSG, the LandScan Silver Edition, represents a major methodological leap forward while also leveraging previous knowledge—the previous year was the baseline for the current annual update carrying forward valuable knowledge of the built environment for the past quarter century—to train the machine learning models. Compared with annual releases over the past 24years, multiple advancements were made to different aspects of the methodology to achieve reproducibility, transparency, and consistent global propagation of solutions to modeling or population distribution issues identified during the review process. These novel changes include incorporation of the latest available geospatial inputs across the globe, machine learning models instead of manual modifications, population feature importance analysis, open-source solutions vs. proprietary software, generation of multiple global versions, analytic validations, and human-in-the-loop revisions to produce the final version. Additionally, algorithms—such as anomaly detection—were introduced to quickly identify areas of focus to develop a new and robust systematic review. Significant changes in modeled population distributions were observed between the 2022 and 2023 releases, largely attributable to improvements in data and methods and discussed thoroughly within this report. In summation, the LandScan Silver Edition leverages the best of the past quarter century of LSG legacy knowledge and continues a tradition of applying cutting-edge enhancements to serve as a new benchmark for accurate, actionable gridded population data
The LandScan program is excited to share LandScan 2024, the latest annual update of a global gridded population dataset at 30 arc-second resolution that serves as foundational GEOINT Human Geography data. Substantial changes were continued from last year in the new ML methodological approach with the goal to retain the knowledge and expertise represented through improvements with each annual release over the past quarter century. Through these annual releases, Oak Ridge National Laboratory (ORNL) has consistently produced the most accurate global gridded population data, reflecting both ambient and unwarned population patterns that meet the United States Department of Defense (U.S. DoD) requirements. Additionally, the dataset is used widely across various U.S. government programs and is released publicly through an NGA and ORNL collaborative open portal (https://LandScan.ornl.gov) to expand its availability to researchers, humanitarian organizations, and the public at large.
The LandScan Mosaic Annual Global Ambient Population Time Series, Version 1.0, provides annual high-resolution global ambient population estimates from 1975 to 2024. The dataset is distributed as one Cloud-Optimized GeoTIFF per year on a globally aligned 3 arc-second WGS 84 grid. The 2024 layer is the LandScan Mosaic benchmark reference year, while the 1975–2023 layers are historical estimates generated using the LandCast backcasting framework.