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At least 1,063 records · Page 59

Size- and concentration-dependent Eu 2+ /Eu 3+ mixed luminescent characteristics of rare-earth-doped CaF 2 nanoparticles and their monolithic epoxy nanocomposites

CaF 2 is a promising luminescent host material for a wide range of applications, due to its high transparency, non-hygroscopy, low refractive index, low density, low backscattering efficiency, and abundance in nature. Here we report the photoluminescence (PL) and cathodoluminescence (CL) characteristics of rare-earth-doped CaF 2 nanoparticles and their composite monoliths with epoxy with visible emissions. The CaF 2 nanoparticles of ca. 36, 108 and 305 nm were prepared by a facile solution-mixing process and subsequent hydrothermal treatment. As the particle size decreases, the luminescence intensity increases for single-doped particles, while oppositely decreases for codoped particles because of energy transfer. Further, Eu 2+ - and Tb 3+ -codoped CaF 2 nanoparticles exhibit red emission, providing an efficient path for red emission through an energy transfer by Tb 3+ bridging without direct Eu 3+ doping. The effects of size and concentration are found to be pronounced in CL than PL, as the charge transfer between Eu 2+ and Eu 3+ reduces the concentration quenching in CL. The luminescence emission characteristics of epoxy/CaF 2 monoliths are different from those of particles due to the interactions with the epoxy molecules, and thus the energy transfer is hindered in PL while not in CL, enabling them for high-energy irradiation applications.

36 MATERIALS SCIENCE↗

Thermal Processing Conditions for the Synthesis of Near Theoretical Density Li 5 La 3 Ta 2 O 12 Ceramics for Ceramic Dual-Mode Detectors

A family of Li-containing garnet compounds, extensively investigated for Li-ion solid electrolyte applications, show great potential to be developed into transparent ceramic dual-mode scintillators. In particular, Li 5 La 3 Ta 2 O 12 (LLTaO) shows promise as an efficient dual-mode scintillator due to its high Li content, high density, non-hygroscopicity, and high effective-Z. Often the synthesis of LLTaO ceramics involves solid state processing techniques starting with oxide and carbonate powders, calcining, sintering for the removal of residual porosity, and post-processing. This study focuses on two objectives: (1) establishing thermal processing boundary conditions for a flexible alkoxide-based sol-gel method for synthesizing fine-grained powders; and (2), consolidating powders via hot-pressing to form high-density ceramics. In this study, near single-phase ceramics were achieved by hot-pressing sol-gel powders with varying amounts of excess Li. Rietveld refinements were used to analyze X-ray diffraction data and provide a quantitative evaluation of the phases present in the hot pressed ceramics. Some of the diffraction data showed large low angle peak asymmetry, suggesting the presence of two cubic Li 5 La 3 Ta 2 O 12 garnet phases with different lattice parameters. Depending on the synthesis and processing conditions, the refinement revealed ~ 90 wt% concentration of a phase with a ≈ 12.8 Å and ~ 10 wt% concentration of a phase with a ≈ 12.9 Å, indicating a remaining excess of Li in the hot pressed ceramics in the large lattice parameter phase. These synthesis experiments allowed for the determination of a baseline for Li loss during hot-pressing. X-ray excited radioluminescence and photoluminescence excitation and emission spectra were obtained from the hot pressed ceramics. In conclusion, the measured emission spectra featured broad tantalate emission and line emissions likely from a rare-earth impurity.

36 MATERIALS SCIENCE↗

Vibrational sum frequency generation spectroscopy reveals the inertness of chromium oxide (001) surfaces

Nanoengineered metal oxides such as Cr(III)-oxide (chromia) films have diverse potential applications in corrosion inhibition, remediation, energy generation, catalysis, data storage, and biological and environmental systems. Concerns about material degradation or oxidation to toxic chromate necessitate an understanding of chromia/aqueous interfaces, beginning with their hydroxylation and hydration behavior. Vibrational sum-frequency generation spectroscopy (vSFG) provides specific molecular-level information about water at the oxide/aqueous junction with high surface selectivity. To overcome the strong absorber problem typical of certain metal oxides in the UV–visible range during nonlinear optical studies, we employed molecular beam epitaxy to deposit transparent, epitaxial nanofilms of Cr 2 O 3 with (001) crystalline orientation on sapphire (Al 2 O 3 (001)) substrates, as confirmed by atomic force microscopy and X-ray diffraction. vSFG spectra of the air and water interfaces of the Cr 2 O 3 (001) films reveal hydroxyl features corresponding to both dissociated and molecular water on the surface. In contrast to the dangling hydroxyls found on the bare Al 2 O 3 (001) substrate, the hydroxyl groups on the deposited Cr 2 O 3 (001) nanofilm do not readily undergo isotopic H/D exchange when exposed to varying forms of D 2 O under ambient conditions. When considering the chemistries of the corresponding trivalent cations in aqueous solution, the finding is at variance with their similar acidities and proton exchange dynamics but consistent with markedly slower inner-sphere water ligand exchange of hexaquo Cr 3+ . This finding challenges the idea that proton and water exchange at the water/Cr₂O₃(001) interface are solely correlated, driven by the strength of metal-bridging oxygen bonds and surface hydroxyl distribution, without direct causation.

Boamah-Agyemang, Mavis D. [Pacific Northwest Natio↗

Advanced high-performance large diameter Cs 2 HfCl 6 (CHC) and mixed halides scintillator

This paper reports on successful growth and performance evaluation of two large diameter Cs 2 HfCl 6 (CHC) and Cs 2 HfCl 4 Br 2 (CHCB), both recently developed scintillator crystals. The discovery of Cs 2 HfCl 6 (CHC) as a scintillator has lately generated much interest in this material and its family, which belongs to the K 2 PtCl 6 cubic crystal structure. CHC is an intrinsic scintillator that is non-hygroscopic (slightly deliquescent, i.e., slightly moisture sensitive but does not deteriorate much when left in air), has no self-radioactivity, provides excellent energy resolution, and has excellent non-proportionality. CHC has a moderate density of 3.9 g/cm 3 and an effective atomic number of 58. Reported in this paper are transparent crack-free single crystal CHC and CHCB boules of one inch in diameter, both grown using the vertical Bridgman method. Samples retrieved from the boules, sized 23 mm × 30 mm and 23 mm × 26 mm, respectively, are characterized for their optical and scintillation properties. Energy resolutions of 3.5% and 3.7% (FWHM) at 662 keV, respectively, are reported. Light yields of 23,000 ph/MeV and 20,000 ph/MeV have been calculated for the large diameter CHC and CHCB crystals, respectively. Results comparable to previously reported results for smaller crystals have been obtained. Studies on decay time, non-proportionality, as well as detector characterization are also reported.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Growth, optical, and luminescence characterization of LiCsMoO{sub 4} crystal.

A crack-free LiCsMoO4 crystal was grown with the conventional Czochralski technique. The optical properties of the crystal show it transparent well in the visible region. The luminescence properties of the crystal were studied from 300 to 14 K under the excitation with a 280 nm light-emitting diode (LED). At room temperature, the luminescence light yield is low; however, it increases significantly at low temperatures. The decay time of the crystal is measured under the excitation of the crystal with the 280 nm LED source. The decay times at all the temperatures are fitted with three exponential functions. The average decay time from 300 to 14 K varies from 6.7 to 8.6 mu s. A thermoluminescence (TL) study of the crystal was carried out from 9 to 300 K. Three TL peaks are found between 165 and 250 K. This study shows that the developed crystal has a potential application in search of neutrinoless double-beta decay of Mo-100 at cryogenic temperatures.

Conventional Czochralski technique↗

Intrinsic scintillation performance & europium concentration effects in RbSr 2 I 5 and RbSr 2 Br 5 scintillators

Scintillators play crucial roles in homeland security applications like gamma ray spectroscopy and high energy X-ray radiography. For promising new scintillators, fine-tuning the luminescent dopant concentration is one avenue to further improve their performance and tailor their properties. In this work, the effects of europium dopant concentrations on the crystal growth, luminescence and scintillation properties of RbSr 2 Br 5 and RbSr 2 I 5 crystals was investigated. Nine transparent 7 mm diameter single crystals were grown via the Vertical Bridgman method. Here, the optical band gap of RbSr 2 Br 5 was 5.9 eV and that of RbSr 2 I 5 was 4.7 eV. High scintillation performance was achieved with a relatively low europium concentration of 1 mol%. For both RbSr 2 Br 5 :Eu and RbSr 2 I 5 :Eu crystals, light yield of 60–90,000 ph/MeV, energy resolution 2.8–4.0 % at 662 keV, and X-ray afterglow 0.79–1.5 % at 2 ms were obtained.

36 MATERIALS SCIENCE↗

A web-based decision support system for collaborative mitigation of multiple water-related hazards using serious gaming

The paper presents a web-based application developed as a medium for executing a serious game to enhance multi-jurisdictional collaborative planning and decision making for mitigation of multiple hazards related to water (i.e., floods, soil erosions, water quality). The gaming application is integrated into the Iowa Watershed Decision Support System (IoWaDSS) designed to serve as a comprehensive multi-sectoral data repository along with the simulation results of process modeling to educate and inform communities on the status of their watersheds during extreme conditions. The interactive serious gaming application was devised to encourage public engagement, facilitate communication and positive relationship between watershed communities, and make the decision process more attractive and transparent for the stakeholders. The web environment offers easily-accessible, user-friendly interfaces that match the skills and knowledge level of a non-technical user. Developed with adaptive design and flexible architecture, the gaming application is generalizable and extendable to support hazard mitigation in other watersheds.

54 ENVIRONMENTAL SCIENCES↗

Evidence-based indicator approach to guide preliminary environmental impact assessments of hydropower development

Global expansion of hydropower resources has increased in recent years to meet growing energy demands and fill worldwide gaps in electricity supply. However, hydropower induces significant environmental impacts on river ecosystems - impacts that are addressed through environmental impact assessment (EIA) processes. The need for effective EIA processes is increasing as environmental regulations are either stressed in developing countries undertaking rapid expansion of hydropower capacity or time- and resource-intensive in developed countries. Part of the challenge in implementing EIAs lies in reaching a consensus among stakeholders regarding the most important environmental factors as the focus of impact studies. To help address this gap, we developed a weight-of-evidence approach (and toolkit) as a preliminary and coarse assessment of the most relevant impacts of hydropower on primary components of the river ecosystem, as identified using river function indicators. Through a science-based questionnaire and predictive model, users identify which environmental indicators may be impacted during hydropower development as well as those indicators that have the highest levels of uncertainty and require further investigation. Furthermore, an assessment tool visualizes inter-dependent indicator relationships, which help formulate hypotheses about causal relationships explored through environmental studies. We apply these tools to four existing hydropower projects and one hypothetical new hydropower project of varying sizes and environmental contexts. We observed consistencies between the output of our tools and the Federal Energy Regulatory Commission licensing process (inclusive of EIAs) but also important differences arising from holistic scientific evaluations (our toolkit) versus regulatory policies. The tools presented herein are aimed at increasing the efficiency of the EIA processes that engender environmental studies without loss of rigor or transparency of rationale necessary for understanding, considering, and mitigating the environmental consequences of hydropower.

54 ENVIRONMENTAL SCIENCES↗

Re-evaluating probable maximum precipitation estimates: sensitivity to transposition domains and storm rotation using modern datasets

This study examines the sensitivity of Probable Maximum Precipitation (PMP) estimates to key methodological decisions embedded in the legacy approach adopted in the U.S. National Weather Service Hydrometeorological Reports No. 51 and No. 52. Although widely used for infrastructure design and risk regulation, fundamental aspects of PMP estimation—such as storm sample size, transposition domain, maximization procedures, and storm rotation—remain poorly constrained and lack formal guidance. Using the Red Rock watershed in Iowa as a case study, and leveraging the 2002–2023 NOAA Analysis of Record for Calibration (AORC) precipitation dataset, we systematically evaluate how each methodological choice, individually and in combination, influences PMP estimates. Our findings demonstrate that PMP is not a fixed physical upper bound but rather a modeling construct shaped heavily by user-defined assumptions. Notably, PMP values derived from modern gridded rainfall datasets can be substantially higher than the legacy estimate used in the original spillway design for Red Rock Dam. Decisions regarding storm sample size, domain extent, climatological window, and particularly storm rotation all contributed to higher PMP estimates. Storm rotation alone—a loosely constrained element in the current PMP practice—can amplify PMP by more than 25%. These results reveal the lack of standardized bounds in current PMP workflows and the need for systematic sensitivity and uncertainty analysis. As PMP estimation shifts toward probabilistic approaches, incorporating physically meaningful storm attributes will be key to developing more transparent, defensible methods for dam safety and climate-resilient infrastructure.

Probable maximum precipitation↗

Spherical Indentation and Implementation of S 3 /P for yield stress determination of brittle materials

Here, a mathematically transparent and robust experimental method has been developed to estimate the yield stress of brittle materials through the analysis of depth-sensing spherical indentation. Employing Hertzian contact mechanics, an elastically invariant ratio based on the simple equation S 3 / P = 6RE r 2 , (where S and P are contact stiffness and indentation load, respectively) has been derived that enables more accurate and confident determination of the transition from elastic to inelastic deformation; a transition that the yield stress dictates and represents. Using two diamond spheres with radii of 3.2 and 8.6 μm, the indentation test method and analyses are applied to two vitreous silicates: Corning's HPFS 7980® fused silica and Vitro's Starphire® soda lime silicate. The estimated yield strengths are 8.15 GPa ± 2.5% for the fused silica and 6.1 GPa ± 3.3% for the soda-lime silicate, and both were independent of indenter radius. Verification of this new experimental method is demonstrated with an as-drawn titanium by showing equivalence of measured yield stress by its spherical indentation and that from uniaxial compression testing. This method will enable easier and more confident estimation of yield stress in brittle materials - a property that historically has been elusive to measure for these materials using common laboratory mechanical test methods.

36 MATERIALS SCIENCE↗

Leveraging Open-Source Tools for Collaborative Macro-energy System Modeling Efforts

The authors are founding team members of a new effort to develop an Open Energy Outlook for the United States. The effort aims to apply best practices of policy-focused energy system modeling, ensure transparency, build a networked community, and work toward a common purpose: examining possible US energy system futures to inform energy and climate policy efforts. Individual author biographies can be found on the project website: https://openenergyoutlook.org/.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Highly efficient bifacial single-junction perovskite solar cells

Bifacial photovoltaics (PV) harvest solar irradiance from both their front and rear surfaces, boosting energy conversion efficiency to maximize their electrical power production. For single-junction perovskite solar cells (PSCs), the performance of bifacial configurations is still far behind that of their state-of-the-art monofacial counterparts. Here, in this paper, we report on highly efficient, bifacial, single-junction PSCs based on the p-i-n (or inverted) architecture. We used optical and electrical modeling to design a transparent conducting rear electrode for bifacial PSCs to enable optimized efficiency under a variety of albedo illumination conditions. The bifaciality of the PSCs was about 91%–93%. Under concurrent bifacial measurement conditions, we obtained equivalent, stabilized bifacial power output densities of 26.9, 28.5, and 30.1 mW/cm 2 under albedos of 0.2, 0.3, and 0.5, respectively. We further showed that bifacial perovskite PV technology has the potential to outperform its monofacial counterparts with higher energy yields and lower levelized cost of energy (LCOE).

14 SOLAR ENERGY↗

Grid connection barriers to renewable energy deployment in the United States

Bulk-power grid connection is an emerging bottleneck to the entry of wind, solar, and storage but has been understudied due to a lack of data. We create and analyze two novel interconnection datasets with more than 38,000 project-level observations that provide new information documenting interconnection challenges in the United States. Active grid connection requests are more than double the total installed capacity of the US power plant fleet (2,600 vs. 1,280 GW). The time required to secure a connection has increased by 70% over the last decade, and withdrawal rates remain high at 80%, suggesting a constrained transmission system that jeopardizes energy transition targets. Wide distributions of interconnection costs indicate the inherent uncertainty of the interconnection process. Interconnection requests that identify large transmission upgrades tend to withdraw from the process. These findings suggest the need for interconnection reforms, tighter links between long-term transmission planning and project-level interconnection processes, and more interconnection outcome transparency.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Electrochemical Reactions Under Reverse Bias Create Additional Mobile Ions That Enable Hole Tunneling in Metal Halide Perovskite Diodes

Gradual reverse-bias breakdown in metal-halide perovskite diodes and solar cells is thought to originate from hole tunneling through steep bands in an ionic depletion region near the electron-transport layer after positively charged iodine vacancies accumulate near the hole-transport layer (HTL). However, typical reported mobile-ion concentrations near 1 x 10^17 cm-3 are too small to quantitatively explain significant tunneling-current densities and (Zener) breakdown observed near -5 V. Here, we show that inferred mobile-ion concentrations increase by more than 100x, to over 1 x 10^18cm-3 , within just 3 min of reverse bias at -6.0 V in p-i-n perovskite diodes. We attribute this increase to iodide oxidation and coupled iodine vacancy creation that must be balanced by reduction reactions near the HTL. Sub-optimal HTL coverage leads to direct contact between the transparent conducting electrode and perovskite, facilitates reduction events, enables the creation of even larger inferred mobile-ion concentrations (~1 x 10^19cm-3 ), and leads to faster degradation under reverse bias. This explains previous work that showed increased breakdown voltages and improved reverse-bias stability by implementing thick, uniform HTLs.

14 SOLAR ENERGY↗

El Agente: An autonomous agent for quantum chemistry

Computational chemistry tools are widely used to study the behavior of chemical phenomena. Yet, the complexity of these tools can make them inaccessible to non-specialists and challenging even for experts. In this work, we introduce El Agente Q, an LLM-based multi-agent system that dynamically generates and executes quantum chemistry workflows from natural language user prompts. The system is built on a novel cognitive architecture featuring a hierarchical memory framework that enables flexible task decomposition, adaptive tool selection, post-analysis, and autonomous file handling and submission. El Agente Q is benchmarked on six university-level course exercises and two case studies, demonstrating robust problem-solving performance (averaging >87% task success) and adaptive error handling through in situ debugging. It also supports longer-term, multi-step task execution for more complex workflows, while maintaining transparency through detailed action trace logs. Together, these capabilities lay the foundation for increasingly autonomous and accessible quantum chemistry.

agentic systems↗

Making the most of your electrons: Challenges and opportunities in characterizing hybrid interfaces with STEM

Inspired by the unique architectures composed of hard and soft materials in natural and biological systems, synthetic hybrid structures and associated hard-soft interfaces have recently evoked significant interest. Soft matter is typically dominated by structural fluctuations even at room temperature, while hard matter is governed by rigid mechanical behavior. This dichotomy offers considerable opportunities to leverage the disparate properties offered by these components across a wide spectrum spanning from basic science to engineering insights with significant technological overtones. Such hybrid structures, which include polymer nanocomposites, DNA functionalized nanoparticle superlattices, and metal organic frameworks to name a few, have delivered promising insights into the technologically relevant applications such as catalysis, environmental remediation, optoelectronics, and medicine. The interfacial structure between the hard and soft phases demonstrates features across a variety of length scales and often strongly influence the functionality of hybrid systems. While scanning/transmission electron microscopy (S/TEM) has proven to be a valuable tool for acquiring intricate molecular and nanoscale details of these interfaces, the unusual nature of hybrid composites presents a suite of challenges that make assessing or establishing structure–property relationships especially difficult. There are additional considerations at all stages of sample analysis from preparing electron-transparent samples to obtaining sufficient contrast to resolve the interface between dissimilar materials given the dose sensitivity of soft materials. Here, we discuss each of these challenges and supplement a review of recent developments in the field with additional experimental investigations and simulations to present solutions for attaining a nano or molecular-level understanding of these interfaces. These solutions present a host of opportunities for investigating the role interfaces play in this unique class of functional materials.

36 MATERIALS SCIENCE↗

Modeling plasticity-mediated void growth at the single crystal scale: A physics-informed machine learning approach

Modeling the evolution of voids during plastic flow as well as their effects on plastic dissipation is critical for both component manufacturing and lifetime estimation purposes. To this end, we propose a rate-dependent constitutive model to homogenize the effects of semi-randomly distributed voids on single crystal plasticity whilst capturing void interaction and plastic anisotropy. Here, this present work focuses on the case of face centered cubic crystals to introduce an anisotropic gauge function applicable within the crystal plasticity formalism. The approach combines analytical methods to describe the micromechanics of the system in combination with symbolic regression to capture analytically intractable mechanisms from data. The hybrid framework uses a physics-informed genetic programming-based symbolic regression algorithm to solve a multiform optimization problem simultaneously producing a new gauge function and a new strain rate equation. This is also a multi-objective optimization problem with many competing objectives. A new search and selection step is introduced to the genetic algorithm that promotes convergence toward a global solution that better satisfies all the objectives. Overall, the symbolic equations produced leverage data-driven methods to achieve greater accuracy than comparable alternatives on an analytically intractable problem while maintaining model transparency.

36 MATERIALS SCIENCE↗

Explaining drivers of housing prices with nonlinear hedonic regressions

Housing markets play a critical role in shaping the spatial and demographic evolution of urban areas. Simulating housing price dynamics can enhance projections of future urban development outcomes. However, traditional hedonic regressions for housing prices, which neglect nonlinear interactions among explanatory variables, often exhibit limited predictive performance. While machine learning (ML) methods can provide a more flexible representation of the relationships between predictors, they are often regarded as “black boxes” due to their complexity and lack of transparency. Interpretable ML techniques provide a promising route by combining the flexibility of ML methods with approaches to analyze the relationships between inputs and outputs. In this study, we employ interpretable ML to analyze the patterns driving the housing market in Baltimore, Maryland, USA. We train an Artificial Neural Network (ANN) to predict Baltimore housing prices based on structural characteristics (e.g., home size, number of stories) and locational attributes (e.g., distance to the city center). We then conduct sensitivity and Partial Dependence Plot (PDP) analyses to interpret the fitted ANN model. We find that the ML model achieves higher predictive accuracy and explains 16 % more of housing price variance than a traditional linear regression model. The interpretable ML model also reveals more nuanced and realistic nonlinear relationships between housing sales price and predictors as well as interactive effects underlying Baltimore home price dynamics. For instance, while the linear model indicates a steady housing price increase over time, our interpretable ML model detects a post-2008 decline, with smaller properties experiencing the sharpest drop.

97 MATHEMATICS AND COMPUTING↗