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At least 703 records · Page 39

Probing lithium mobility at a solid electrolyte surface

Abstract Solid-state electrolytes overcome many challenges of present-day lithium ion batteries, such as safety hazards and dendrite formation 1,2 . However, detailed understanding of the involved lithium dynamics is missing due to a lack of in operando measurements with chemical and interfacial specificity. Here we investigate a prototypical solid-state electrolyte using linear and nonlinear extreme-ultraviolet spectroscopies. Leveraging the surface sensitivity of extreme-ultraviolet-second-harmonic-generation spectroscopy, we obtained a direct spectral signature of surface lithium ions, showing a distinct blueshift relative to bulk absorption spectra. First-principles simulations attributed the shift to transitions from the lithium 1 s state to hybridized Li- s /Ti- d orbitals at the surface. Our calculations further suggest a reduction in lithium interfacial mobility due to suppressed low-frequency rattling modes, which is the fundamental origin of the large interfacial resistance in this material. Our findings pave the way for new optimization strategies to develop these electrochemical devices via interfacial engineering of lithium ions.

25 ENERGY STORAGE↗

Introgressions of novel diseases resistance genes from Miscanthus into energycane

Sugarcane (Saccharum) is among the world’s leading bioenergy crops. However, modern sugarcane cultivars are derived from a relatively small set of founder genotypes, which has contributed to cultivar susceptibility to diseases. Miscanthus is a close relative of sugarcane that is genetically diverse and a potential source of genes for improving sugarcane. We found that Miscanthus is a source of resistance to four major diseases of sugarcane and we crossed these disease-resistance genes into a predominantly sugarcane genetic background (BC1 generation). Additionally, we found that Miscanthus could also confer genes for chilling-tolerant photosynthesis to sugarcane, which would be highly advantageous for production of energycane in subtropical environments, like the southern coastal plain of the US. Using advanced modeling techniques, we found that standard marker-assisted selection could be effective for breeding resistance conferred by a small number of genes each with large effect (i.e. vertical resistance), but to breed for many genes each of small effect (i.e. horizontal resistance), genomic selection would be the better strategy. Lastly, we learned that Miscanthus can be induced to flower sooner by giving the plants short days (long nights) but that the ideal day length for a given accession depends on its adaptation to its latitude of origin, with tropical accessions requiring shorter days to flower than accessions from high latitudes. This information will facilitate plant breeders’ ability to make crosses between Miscanthus and sugarcane, and enable greater use of Miscanthus as a genetic resource to improve sugarcane.

09 BIOMASS FUELS↗

Particle-Tracking Proton Computed Tomography—Data Acquisition, Preprocessing, and Preconditioning

Proton CT (pCT) is a promising new imaging technique that can reconstruct relative stopping power (RSP) more accurately than x-ray CT in each cubic millimeter voxel of the patient. This, in turn, will result in better proton range accuracy and, therefore, smaller planned tumor volumes (PTV). The hardware description and some reconstructed images have previously been reported. In a series of two contributions, we focus on presenting the software algorithms that convert pCT detector data to the final reconstructed pCT images for application in proton treatment planning. There were several options on how to accomplish this, and we will describe our solutions at each stage of the data processing chain. In the first paper of this series, we present the data acquisition with the pCT tracking and energy-range detectors and how the data are preprocessed, including the conversion to the well-formatted track information from tracking data and water-equivalent path length from the data of a calibrated multi-stage energy-range detector. These preprocessed data are then used for the initial image formation with an FDK cone-beam CT algorithm. The output of data acquisition, preprocessing, and FDK reconstruction is presented along with illustrative imaging results for two phantoms, including a pediatric head phantom. The second paper in this series will demonstrate the use of iterative solvers in conjunction with the superiorization methodology to further improve the images resulting from the upfront FDK image reconstruction and the implementation of these algorithms on a hybrid CPU/GPU computer cluster.

42 ENGINEERING↗

Ensemble Manufacturing Techniques for Steam Turbine Components Across Length Scales

Faster design to manufacturing requirements were sought for steam turbine components to meet the changing demands of today’s power grid of improved efficiency through operating temperature increases and enhanced operational flexibility from baseload to cyclic operations. Advances in multiple advanced manufacturing (AM) process enabled redesign of turbine components for extreme environments with the potential to reduce cost. AM is of particular interest to improve component functionality, higher temperature capability, and superior durability in large scale steam turbine applications. AM methods have an immense potential to open-up the design space by working directly with the 3D model to produce near-net shapes, enable fast design-manufacturing iterations, thereby significantly reducing product cost and lead-time up to 25 % from current baseline. However, these benefits cannot be fully realized due to the potential for unknown AM processing defects and their resultant effect upon component performance in service. Siemens is partnering with Oak Ridge National Laboratory (ORNL), Electric Power Research Institute (EPRI), and Connecticut Center for Advanced Technology (CCAT) to advance the knowledge of complex process-material interactions for desired microstructures and properties that are closely interlinked to component geometries across different length scales. The proposed program utilized an ensemble of multidisciplinary technologies to accelerate the development of materials, high-throughput experiments for their qualification, and design flexibility/topology optimization for repair/redesign of components to address critical failure mechanisms for improved performance and increased reliability of existing power plant components. The proposed activities, if successfully demonstrated for identified components, will enable paradigm shift in customized manufacturing and accelerated qualification/certification towards increased steam turbine component durability, increased turbine efficiency, and reduced CO 2 emissions in load-following environments compared to today’s technology. Technology maturation is built into the project as successful research will include customized process-component down-selection enabling AM methodologies to be incorporated directly into the existing supply chain. The specific activities of the proposed effort are: 1. Topology optimization of down-selected steam turbine parts that are amenable to additive and hybrid manufacturing for cost/performance improvement. 2. Process-structure-property relationships for five AM processes for steam turbine materials of interest to compare with conventional materials. 3. Perform part/assembly build process using advanced additive/hybrid machine tools followed by quality inspection of the built components for insight into qualification for production scale-up. Steam turbine rig testing of printed components under targeted, well monitored and characterized environmental conditions of for performance comparison of baseline and redesigned components.

36 MATERIALS SCIENCE↗

Ground state of Ce 3 Bi 4 Pd 3 unraveled by hydrostatic pressure

Noncentrosymmetric Ce 3 Bi 4 Pd 3 has attracted a lot of attention as a candidate for strongly correlated topological material, yet its experimental ground state remains a matter of contention. Two conflicting scenarios have emerged from a comparison to the prototypical Kondo insulator Ce 3 Bi 4 Pd 3 : Either Ce 3 Bi 4 Pd 3 is a spin-orbit-driven topological semimetal or a Kondo insulator with smaller Kondo coupling than its Pt counterpart. Here, we determine the ground state of Ce 3 Bi 4 Pd 3 via electrical resistivity measurements under hydrostatic pressure, which is a clean symmetry-preserving tuning parameter that increases hybridization but virtually preserves spin-orbit coupling. Ce 3 Bi 4 Pd 3 becomes more insulating under pressures up to 2.3 GPa, which is a signature of Ce-based Kondo insulating materials in the considered pressure range. Its small zero-pressure gap increases quadratically with pressure, similar to the behavior observed in the series Ce 3 Bi 4 (Pt 1 - x Pd x ) 3 , which indicates that Pt substitution and applied pressure have a similar effect. Finally, our result not only demonstrates that Kondo coupling, rather than spin-orbit coupling, is the main tuning parameter in this class of materials, but it also establishes that Ce 3 Bi 4 Pd 3 has a narrow-gap Kondo insulating ground state.

36 MATERIALS SCIENCE↗

Machine learning and process-based modeling of spatiotemporal changes in active layer thickness across Alaska

Permafrost degradation poses a growing threat to infrastructure stability and ecosystem resilience in the rapidly warming Arctic. We investigated the spatiotemporal dynamics of active layer thickness (ALT) across Alaska by integrating field observations, environmental datasets, a physically based Stefan model, and machine learning (ML) techniques. Using weather projections from the Coupled Model Intercomparison Project Phase 6 under two Shared Socioeconomic Pathways (SSP 2-4.5 and SSP 5-8.5), we assessed ALT sensitivity to projected future weather conditions. The random forest (RF) model outperformed the Stefan approach in predicting ALT on the training dataset (R² = 0.84 vs. 0.53) but demonstrated lower generalizability on the test dataset (R² = 0.24 vs. 0.54). The root mean square error (RMSE) for the RF model for training and testing ranged from 14 to 22 cm, compared to 17 and 18 cm for the Stefan model. Variable importance analysis revealed that mean annual temperature and slope angle were the strongest predictors of ALT, accounting for 19% and 18% of the variance, respectively, followed by sediment transport index (14%) and stream power index (11%). Comparative analysis of baseline ALT predictions showed the Stefan model tended to project a thicker active layer (mean ± SD: 65 ± 16 cm), compared to the RF model (mean ± SD: 59 ± 8.8) cm). Both models indicated a latitudinal gradient in ALT, with shallower depths at higher latitudes. Projected ALT increases by 2100 were estimated at 3.3 ± 2.2 cm under SSP 2-4.5 and 5.9 ± 4.0 cm under SSP 5-8.5 for the ML model, whereas the Stefan model projected substantially larger increases of 13 ± 2.6 cm (SSP 2-4.5) and 28 ± 4.4 cm (SSP5-8.5). Spatial analysis showed the greatest ALT increases in northern Alaska, with relatively smaller changes in southern regions. These findings highlight the complex, multifactorial nature of ALT dynamics and the value of hybrid modeling approaches. As rising temperatures accelerate permafrost thaw, changes in ALT can disrupt ecosystems, damage infrastructures, and enhance the release of stored soil carbon, highlighting the urgent need for improved predictive capabilities to inform adaptation strategies in the Arctic.

Climate sciences↗

Hard x-ray standing-wave photoemission study of the interfaces in a BiFeO$_3$/La$_{0.7}$Sr$_{0.3}$MnO$_3$ superlattice

Hybrid multiferroics such as BiFeO$_3$ (BFO) and La$_{0.7}$Sr$_{0.3}$MnO$_3$ (LSMO) heterostructures are highly interesting functional systems due to their complex electronic and magnetic properties. One of the key parameters influencing the emergent properties is the quality of interfaces, where varying interdiffusion lengths can give rise to different chemistry and distinctive electronic states. Here we report high-resolution depth resolved chemical and electronic investigation of BFO/LSMO superlattice using standing-wave hard X-ray photoemission spectroscopy in the first-order Bragg as well as near-total-reflection geometry. Our results show that the interfaces of BFO on top of LSMO are atomically abrupt, while the LSMO on top of BFO interfaces show an interdiffusion length of around 1.2 unit cells. The two interfaces also exhibit different chemical gradients, with the BFO/LSMO interface being Sr-terminated by a spectroscopically distinctive high binding energy component in Sr 2p core-level spectra, which is spatially contained within 1 unit cell from the interface. From the electronic point of view, unique valence band features were observed for bulk-BFO, bulk-LSMO and their interfaces. Our X-ray optical analysis revealed a unique electronic signature at the BFO/LSMO interface, which we attribute to the coupling between those respective layers. Valence band decomposition based on the Bragg-reflection standing-wave measurement also revealed the band alignment between BFO and LSMO layers. Our work demonstrates that standing-wave hard x-ray photoemission is a reliable non-destructive technique for probing depth-resolved electronic structure of buried layers and interfaces with sub-unit-cell resolution. Equivalent investigations can be successfully applied to a broad class of material such as perovskite complex oxides with emergent interfacial phenomena.

Martins, HP↗

Application of FISH based G2-PCC assay for the cytogenetic assessment of high radiation dose exposures: Potential implications for rapid triage biodosimetry

The main goal of this study is to test the utility of calyculin A induced G2-PCC assay as a biodosimetry triage tool for assessing a wide range of low and acute high radiation dose exposures of photons. Towards this initiative, chromosome aberrations induced by low and high doses of x-rays were evaluated and characterized in G2-prematurely condensed chromosomes (G2-PCCs) by fluorescence in situ hybridization (FISH) using human centromere and telomere specific PNA (peptide nucleic acid) probes. A dose dependent increase in the frequency of dicentric chromosomes was observed in the G2-PCCs up to 20 Gy of x-rays. The combined yields of dicentrics and rings in the G2-PCCs showed a clear dose dependency up to 20 Gy from 0.02/cell for 0.1 Gy to 14.98/cell for 20 Gy. Centric rings were observed more frequently than acentric ring chromosomes in the G2-PCCs at all the radiation doses from 1 Gy to 20 Gy. A head-to-head comparison was also performed by FISH on the yields of chromosome aberrations induced by different doses of x-rays (0 Gy -7.5 Gy) in colcemid arrested metaphase chromosomes and calyculin A induced G2-PCCs. In general, the frequencies of dicentrics, rings and acentric fragments were slightly higher in G2-PCCs than in colcemid arrested metaphase chromosomes at all the radiation doses, but the differences were not statistically significant. To reduce the turnaround time for absorbed radiation dose estimation, attempt was made to obtain G2-PCCs by reducing the culture time to 36 hrs. The absorbed doses estimated in x-rays irradiated (0,1,2 and 4 Gy) G2-PCCs after 36 hrs of culture were grossly like that of G2-PCCs and colcemid arrested metaphase chromosomes prepared after 48 hrs of culture. Our study indicates that the shortened version of calyculin A induced G2-PCC assay coupled with the FISH staining technique can serve as an effective triage biodosimetry tool for large-scale radiological/nuclear incidents.

Science & Technology - Other Topics↗

Leveraging operator learning to accelerate convergence of the preconditioned conjugate gradient method

We propose a new deflation strategy to accelerate the convergence of the preconditioned conjugate gradient (PCG) method for solving parametric large-scale linear systems of equations. Unlike traditional deflation techniques that rely on eigenvector approximations or recycled Krylov subspaces, we generate the deflation subspaces using operator learning, specifically the Deep Operator Network (DeepONet). To this aim, we introduce two complementary approaches for assembling the deflation operators. The first approach approximates near-null space vectors of the discrete PDE operator using the basis functions learned by the DeepONet. The second approach directly leverages solutions predicted by the DeepONet. To further enhance convergence, we also propose several strategies for prescribing the sparsity pattern of the deflation operator. Here, a comprehensive set of numerical experiments encompassing steady-state, time-dependent, scalar, and vector-valued problems posed on both structured and unstructured geometries is presented and demonstrates the effectiveness of the proposed DeepONet-based deflated PCG method, as well as its generalization across a wide range of model parameters and problem resolutions.

Deflation↗

Accelerating Biomimetic Solar - Energy Harvesting: Mapping the Interaction Landscape of Plasmonic-Excitonic Hybrid Nanosystems (Final Report)

In general, excitonic and plasmonic nanoscale materials in close proximity show high potential for significant breakthroughs in energy related materials research. The interactions between these two kinds of materials result in coupled optical transitions (plexcitons), distinct from those of both the individual exciton and plasmon as well as from those of the sum of their constituents (synergistic effects). By linking together materials-research and physical-research approaches, this project contributes to a concerted approach on nanomaterials energy research. The project’s overall goal is to accelerate the development of well-defined plexcitonic model systems consisting of carefully engineered plasmonic and excitonic nanomaterial— essential for both gaining a fundamental understanding of plexcitonic nanomaterials and the development of novel design principles for biomimetic solar energy harvesting. During the 3-year project period and the terminal renewal with limited support for a 12-month period, we successfully synthesized and characterized (1) a robust excitonic nanomaterial and (2) a library of plasmonic nanoparticles as well as developed (3) a microfluidic platform for homogenous nanosynthesis as summarized below: (1) Robust Excitonic Nanomaterial. Supramolecular assemblies are Nature’s most successful material system for solar energy harvesting. However, photovoltaic devices based on artificial supramolecular assemblies continue to be stymied by disappointing efficiencies and poor stability. The conceptual failure may lie in current solar cell architectures, which rely on solidifying supramolecular assemblies as an ensemble into a solid matrix, neglecting the intrinsic fragility of the assemblies’ internal structure, thus disrupting or even destroying their delicate optoelectronic properties, that is, delicate Frenkel excitonic properties. Supramolecular assemblies may finally serve as usable light harvesting material systems for solar energy conversion technologies, only if they meet the following criteria: (a) Stability, that is, the fragile structure including its delicate Frenkel excitonic character needs to be stable, (b) Robustness, that is, resistant against elevated and fluctuating temperatures, and (c) Viability for device integration, that is, capable of being immobilized onto solid substrates. Here, by developing a nanocomposite via a tunable, cage-like scaffold design, we successfully provided stable supramolecular nanocomposites, that inhabit robust Frenkel excitons despite harming environmental conditions such as extreme heat stress. (2) Library of Plasmonic Nanoparticles. Naturally, current models describing plasmonic hybrid quantum states—plasmonic hybridizations—parallel those developed for molecular orbitals, equating individual plasmonic nanostructures with “atoms” and the plasmonic nanoassemblies with “molecules.” In analogy to organic synthesis, a suitably robust fabrication method would allow for “atom-like” manipulation of “molecule-like” plasmonic nanoassemblies; of high value for next-generation energy nanotechnologies. Despite this frequent comparison, current plasmonic nanoassembly fabrication methods favor top-down templating over wet-chemical synthesis, however, achieving precise control over nanostructure’s geometry and surface characteristics remain an art and a scientific challenge. The conceptual failure may lie in the current wet-chemical synthesis paradigm, as it relies on the accessibility of a multi-dimensional synthesis parameter space through limited, rather one-dimensional synthesis procedures by employing step-by-step approaches. Solution-based nanoarchitectonics for rational design of precisely built plasmonic nanoassemblies via solution-based fabrication may finally be possible only if multi-dimensional syntheses approaches are available that allow for comprehensive control over the plasmonic nanomaterials’ (a) Structural Properties and (b) Surface Properties. Here, by developing an innovative multidimensional 1,3-propanediol based polyol synthesis, we successfully provided control over the plasmonic building-block’s geometry (size and shape) together with its surface characteristics. Our results present a critical step toward the vision of a “periodic table-like” system for plasmonic materials based on straightforward wet-chemical syntheses for energy nanotechnologies. Developing deliberate modifications on this synthesis, we generated a library of plasmonic nanostructures covering the vast parameter space—opening the door for fundamental investigation of plexcitonic model systems. (3) Microfluidic Platform for Homogenous Nanosynthesis. Control over structural properties of plexcitonic nanocomposites remains a challenge due to current limitations in nanosynthesis techniques. Slight variations in nanostructure’s geometry impact their optoelectronic properties, demanding precise synthesis beyond the capabilities of solution-based (batch) synthesis processes. In contrast, the small, confined liquid volumes used in microfluidics—a reaction technique where the manipulation of fluids takes place in channels with dimensions of tens of micrometers—allows for homogenous synthesis conditions, providing excellent control of the reaction and, as a result, of the materials’ geopmetry and composition. However, thus far, the majority of plexcitonic systems has been developed via batch synthesis. Here, by successfully developing a two-channel microreactor, our microfluidic-supported synthesis approach combines the advantages of both microfluidics and batch platforms, allowing for precise spatio-temporal control over all synthesis parameters opening the possibility for homogenous nanosythnesis of well-defined plexcitonic model systems.

14 SOLAR ENERGY↗

Dual Mechanism for Transient Capacitance Anomaly in Improper Ferroelectrics

Negative capacitance (NC) effects in ferroelectrics can potentially break fundamental limits of power dissipation known as “Boltzmann tyranny.” However, the origin of transient NC of ferroelectrics, which is attributed to two different mechanisms involving free-energy landscape and nucleation, is under intense debate. Here, we report the coexistence of transient NC and an S-shaped anomaly during the switching of ferroelectric hexagonal ferrites capacitor in an RC circuit. The early-stage NC arises from the nucleation process, while the late-stage S-shaped anomaly corresponds to a nascent NC associated with the free-energy landscape. The entire waveform can be reproduced using a hybrid model that simultaneously incorporates these two mechanisms. These results highlight the multivariable free-energy landscape of hexagonal ferrites that enables an abrupt change of the internal field and demonstrate that the two mechanisms are not mutually exclusive, resolving the long-standing debate. In conclusion, the behavior of the S-shaped anomaly also provides a pathway to extract parameters of free-energy landscape and switching dynamics.

Capacitance↗

Comparative Studies of Optoelectrical Properties of Prominent PV Materials: Halide Perovskite, CdTe, and GaAs

We compare three representative high performance PV materials: halide perovskite MAPbI3, CdTe, and GaAs, in terms of photoluminescence (PL) efficiency, PL lineshape, carrier diffusion, and surface recombination and passivation, over multiple orders of photo-excitation density or carrier density appropriate for different applications. An analytic model is used to describe the excitation density dependence of PL intensity and extract the internal PL efficiency and multiple pertinent recombination parameters. A PL imaging technique is used to obtain carrier diffusion length without using a PL quencher, thus, free of unintended influence beyond pure diffusion. Our results show that perovskite samples tend to exhibit lower Shockley-Read-Hall (SRH) recombination rate in both bulk and surface, thus higher PL efficiency than the inorganic counterparts, particularly under low excitation density, even with no or preliminary surface passivation. PL lineshape and diffusion analysis indicate that there is considerable structural disordering in the perovskite materials, and thus photo-generated carriers are not in global thermal equilibrium, which in turn suppresses the nonradiative recombination. This study suggests that relatively low point-defect density, less detrimental surface recombination, and moderate structural disordering contribute to the high PV efficiency in the perovskite. This comparative photovoltaics study provides more insights into the fundamental material science and the search for optimal device designs by learning from different technologies.

14 SOLAR ENERGY↗

Forecasting for ESCAPE: A Multi-Institution Hybrid Forecasting and Nowcasting Operation for Sea-Breeze Convection Supporting a Ground-Based and Airborne Field Campaign

The Experiment of Sea-Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) field project deployed two aircraft and ground-based assets in the vicinity of Houston, Texas, between 27 May and 2 July 2022, examining how meteorological conditions, dynamics, and aerosols control the initiation, early growth stage, and evolution of coastal convective clouds. To ensure that airborne- and ground-based assets were deployed appropriately, a forecasting and nowcasting team was formed. Daily forecasts guided real-time decision-making by assessing synoptic weather conditions, environmental aerosol, and a variety of atmospheric modeling data to assign a probability for meeting specific ESCAPE campaign objectives. During the research flights, a small team of forecasters provided “nowcasting” support by analyzing radar, satellite, and new model data in real time. The nowcasting team proved invaluable to the campaign operation, as sometimes changing environmental conditions affected, for example, the timing of convective initiation. In addition to the success of the forecasting and nowcasting teams, the ESCAPE campaign offered a unique “testbed” opportunity where in-person and virtual support both contributed to campaign objectives. The forecasting and nowcasting teams were each composed of new and experienced forecasters alike, where new forecasters were given invaluable experience that would otherwise be difficult to attain. Both teams received training on forecast models, map analysis, Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT), and thermodynamic sounding analysis before the beginning of the campaign. In this article, the ESCAPE forecasting and nowcasting teams reflect on these experiences, providing potentially useful advice for future field campaigns requiring forecasting and nowcasting support in a hybrid virtual/in-person framework.

54 ENVIRONMENTAL SCIENCES↗

Synthetic Pathways to gamma-Graphyne and Related Allotropes of Carbon

Graphynes, two-dimensional carbon lattices combining sp 1 and sp 2 hybridized atoms, were predicted theoretically more than three decades ago, but few structures have been realized to date. These carbons are believed to possess remarkable mechanical and electronic properties, including high charge carrier mobilities comparable to those in graphene (10 4 to 10 5 cm 2 V -1 s -1 ). Unlike graphene, certain graphynes are predicted to be intrinsic semiconductors. Among these intriguing structures, γ-graphyne stands out as the structurally simplest and most symmetric sp 1 /sp 2 lattice. γ-Graphyne was first theorized in 1987. In contrast with graphene, γ-graphyne will be a semiconductor with a small band gap suitable for fabrication of electronic devices. This solves one of the fundamental problems of carbon-based electronics, the necessity for inducing a band gap in graphene. γ-Graphyne has the potential to form the basis for the next generation of carbon-based electronics operating at speeds unattainable by traditional silicon chips. Unlike silicon, γ-graphyne is a direct band gap semiconductor, and it will feature exceptional strength comparable to that of other 2D carbon allotropes. Such combination of properties may enable a new generation of highly efficient, ultra-light and flexible solar cells. Despite being a potentially “magical” material, γ-graphyne remained synthetically elusive for over three decades. The primary goals of this project were: (1) Synthesis of bulk γ-graphyne phases through solution-phase 2D polymerizations; (2) Experimental exploration of the physical and chemical properties of γ-graphyne; and (3) Mechanistic and theoretical studies of the novel chemical transformations developed in Goal 1. Common pyrolytic and vapor-deposition methodologies used for the synthesis of graphitic allotropes are unsuitable for graphyne and other sp 1 -contaning structures, as acetylenes readily convert to graphene and amorphous carbon at high temperatures. In contrast, this proposal is based on solution-based 2D polymerization. The major advantages of this approach over the traditional high temperature techniques are the potential to adjust the structure of the material with atomic precision, and the possibility of using structurally complex and relatively fragile repeat units. The outcomes of this research can revolutionize carbon nanotechnology, expanding the field’s structural toolbox beyond primarily graphitic and benzenoid structures. Understanding the chemistry of sp 1 carbon allotropes can lead to entirely new classes of structures with unique properties, including graphyne ribbons, nanotubes, quantum dots, and heterostructures with other 2D materials. Furthermore, the development of reliable and robust synthetic pathways towards periodic covalent molecular sheets with atomically precise structures shall have a profound impact on chemistry and materials science.

2D polymerization↗

Bulk electronic structure of lanthanum hexaboride (LaB 6 ) by hard x-ray angle-resolved photoelectron spectroscopy

In the last decade rare-earth hexaborides have been investigated for their fundamental importance in condensed matter, and for their applications in advanced technological fields. Among these compounds, LaB 6 has a special place, being a traditional d-band metal without additional f- bands. In order to understand the bulk electronic structure of the more complex rare-earth hexaborides, in this paper we investigate the bulk electronic structure of LaB 6 using tender/hard x-ray photoemission spectroscopy, measuring both core-level and angle-resolved valence-band spectra. Furthermore, we compare the La 3d core level spectrum to cluster model calculations in order to understand the bulk-like core-hole screening effects. The results show that the La 3d well-screened peak is at a lower binding energy compared to the main poorly-screened peak; the relative intensity between these peaks depends on how strong the hybridization is between La and B atoms. Here, we show that the recoil effect, negligible in the soft x-ray regime, becomes prominent at higher kinetic energies for lighter elements, such as boron, but is still negligible for heavy elements, such as lanthanum. In addition, we report the bulk-like band structure of LaB6 determined by tender/hard x-ray angle-resolved photoemission spectroscopy (HARPES). We compare HARPES experimental results to the free-electron final-state calculations and to the more precise one-step photoemission theory including matrix element and phonon excitation effects. The agreement between the features present in the experimental ARPES data and the theoretical calculations is very good. In addition, we consider the nature and the magnitude of phonon excitations in order to interpret HARPES experimental data measured at different temperatures and excitation energies. We demonstrate that one step theory of photoemission and HARPES experiments provide, at present, the only approach capable of probing, both experimentally and theoretically, true “bulk-like” electronic band structure of rare-earth hexaborides and strongly correlated materials.

36 MATERIALS SCIENCE↗

High spatial resolution direct conversion amorphous selenium X-ray detectors with monolithically integrated CMOS readout

Recent progress in the field of micron-scale spatial resolution direct conversion X-ray detectors for high-energy synchrotron light sources serve applications ranging from nondestructive and noninvasive microscopy techniques which provide insight into the structure and morphology of crystals, to medical diagnostic measurement devices. Amorphous selenium ( a -Se) as a wide-bandgap thermally evaporated photoconductor exhibits ultra-low thermal generation rates for dark carriers and has been extensively used in X-ray medical imaging. Being an amorphous material, it can further be deposited over large areas at room temperatures and at substantially lower costs as compared to crystalline semiconductors. Here, to address the demands for a high-energy and high spatial resolution X-ray detector for synchrotron light source applications, we have thermally evaporated a -Se on a Mixed-Mode Pixel Array Detector (MM-PAD) Application Specific Integrated Circuit (ASIC). The ASIC format consists of 128 × 128 square pixels each 150 μm on a side. A 200 μm a -Se layer was directly deposited on the ASIC followed by a metal top electrode. The completed detector assembly was tested with 45 kV Ag and 23 kV Cu X-ray tube sources. The detector fabrication, performances, Modulation Transfer Function (MTF) measurements, and simulations are reported.

36 MATERIALS SCIENCE↗

AutoEnRichness: A hybrid empirical and analytical approach for estimating the richness of galaxy clusters

ABSTRACT We introduce AutoEnRichness, a hybrid approach that combines empirical and analytical strategies to determine the richness of galaxy clusters (in the redshift range of 0.1 ≤ z ≤ 0.35) using photometry data from the Sloan Digital Sky Survey Data Release 16, where cluster richness can be used as a proxy for cluster mass. In order to reliably estimate cluster richness, it is vital that the background subtraction is as accurate as possible when distinguishing cluster and field galaxies to mitigate severe contamination. AutoEnRichness is comprised of a multistage machine learning algorithm that performs background subtraction of interloping field galaxies along the cluster line of sight and a conventional luminosity distribution fitting approach that estimates cluster richness based only on the number of galaxies within a magnitude range and search area. In this proof-of-concept study, we obtain a balanced accuracy of 83.20 per cent when distinguishing between cluster and field galaxies as well as a median absolute percentage error of 33.50 per cent between our estimated cluster richnesses and known cluster richnesses within r200. In the future, we aim for AutoEnRichness to be applied on upcoming large-scale optical surveys, such as the Legacy Survey of Space and Time and Euclid, to estimate the richness of a large sample of galaxy groups and clusters from across the halo mass function. This would advance our overall understanding of galaxy evolution within overdense environments as well as enable cosmological parameters to be further constrained.

79 ASTRONOMY AND ASTROPHYSICS↗

Grey-box modeling and application for building energy simulations - A critical review

Grey-box modeling, as one of the three fundamental modeling techniques for building energy models, has many advantages compared with black-box modeling and white-box modeling. Additionally, it has been widely applied to solve problems of building technologies, such as building load estimation, control and optimization, and building-grid integration. However, a thorough review of grey-box modeling is not available. This review study systematically investigated various aspects of grey-box modeling for buildings. First, the fundamental aspects of grey-box modeling are presented, including the theoretical background, modeling of building elements, modeling order, modeling diagram, and order reduction. Second, the detailed modeling approaches are discussed. Third, multiple applications of grey-box modeling are investigated for building energy domain, which are categorized into the following groups: heat dynamics analysis, thermal load estimation, building control and optimization, district/urban scale energy modeling, and building-grid integration. Finally, the available software packages for grey-box modeling are compared. Overall, the challenges of using grey-box modeling can be summarized as follows: (1) the theoretical limitations and assumptions of grey-box modeling are unclear; (2) grey-box model naming convention and structure are confusing; (3) grey-box model creation is vague; (4) suitable applications of grey-box models are unknown; and (5) grey-box models lack unified software solutions for wider adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗