Discovery of chalcogenides structures and compositions using mixed fluxes.

Advancements in many modern technologies rely on the continuous need for materials discovery. However, the design of synthesis routes leading to new and targeted solid-state materials requires understanding of reactivity patterns1-3. Advances in synthesis science are necessary to increase efficiency and accelerate materials discovery4-10. We present a highly effective methodology for the rational discovery of materials using high-temperature solutions or fluxes having tunable solubility. This methodology facilitates product selection by projecting the free-energy landscape into real synthetic variables: temperature and flux ratio. We demonstrate the effectiveness of this technique by synthesizing compounds in the chalcogenide system of A(Ba)-Cu-Q(O) (Q = S or Se; A = Na, K or Rb) using mixed AOH/AX (A = Li, Na, K or Rb; X = Cl or I) fluxes. We present 30 unreported compounds or compositions, including more than ten unique structural types, by systematically varying the temperature and flux ratios without requiring changing the proportions of starting materials. Also, we found that the structural dimensionality of the compounds decreases with increasing reactant solubility and temperature. This methodology serves as an effective general strategy for the rational discovery of inorganic solids.

Subnanometer Scale Mapping of Hydrogen Doping in Vanadium Dioxide.

Hydrogen donor doping of correlated electron systems such as vanadium dioxide (VO2) profoundly modifies the ground state properties. The electrical behavior of HxVO2 is strongly dependent on the hydrogen concentration; hence, atomic scale control of the doping process is necessary. It is however a nontrivial problem to quantitatively probe the hydrogen distribution in a solid matrix. As hydrogen transfers its sole electron to the material, the ionization mechanism is suppressed. In this study, a methodology mapping the doping distribution at subnanometer length scale is demonstrated across a HxVO2 thin film focusing on the oxygen-hydrogen bonds using electron energy loss spectroscopy (EELS) coupled with first-principles EELS calculations. The hydrogen distribution was revealed to be nonuniform along the growth direction and between different VO2 grains, calling for intricate hydrogenation mechanisms. Our study points to a powerful approach to quantitatively map dopant distribution in quantum materials relevant to energy and information sciences.

Resolving signal drift in the wall-mounted camera of the RGSC system.

PURPOSE: To present a modified calibration method to reduce signal drift due to table sagging in Respiratory Gating for Scanner (RGSC) systems with a wall-mounted camera. MATERIALS AND METHODS: Approximately 70 kg of solid water phantoms were evenly distributed on the CT couch, mimicking the patient's weight. New calibration measurements were performed at 9 points at the combination of three lateral positions, the CT isocenter and ±10 cm laterally from the isocenter, and three longitudinal locations, the CT isocenter and ±30 cm or ±40 cm from the isocenter. The new calibration was tested in two hospitals. RESULTS: Implementing the new weighed calibration method at the extended distance yielded improved results during the DIBH scan, reducing the drift to within 1 from 3 mm. The extended calibration positions exhibited similarly reduced drift in both hospitals, reinforcing the method's robustness and its potential applicability across all centers. CONCLUSION: This proposed solution aims to minimize the systematic error in radiation delivery for patients undergoing motion management with wall-mounted camera RGSC systems, especially in conjunction with a bariatric CT couchtop.

The AXEAP2 program for Kß X-ray emission spectra analysis using artificial intelligence.

The processing and analysis of synchrotron data can be a complex task, requiring specialized expertise and knowledge. Our previous work addressed the challenge of X-ray emission spectrum (XES) data processing by developing a standalone application using unsupervised machine learning. However, the task of analyzing the processed spectra remains another challenge. Although the non-resonant Kß XES of 3d transition metals are known to provide electronic structure information such as oxidation and spin state, finding appropriate parameters to match experimental data is a time-consuming and labor-intensive process. Here, a new XES data analysis method based on the genetic algorithm is demonstrated, applying it to Mn, Co and Ni oxides. This approach is also implemented as a standalone application, Argonne X-ray Emission Analysis 2 (AXEAP2), which finds a set of parameters that result in a high-quality fit of the experimental spectrum with minimal intervention. AXEAP2 is able to find a set of parameters that reproduce the experimental spectrum, and provide insights into the 3d electron spin state, 3d-3p electron exchange force and Kß emission core-hole lifetime.

Nutrition in the Management of Kidney Transplant Recipients.

Kidney transplantation offers patients with end stage kidney disease the best outcomes. Concentration on nutrition is pivotal throughout the transplant life course. Nutritional requirements change during each phase of transplantation, from pretransplant evaluation and wait-time, acute transplantation, maintenance and ultimately declining graft function, and care should be taken to consider each stage. In this article we concentrate on addressing each phase, with additional focus on current hot topics of dysglycaemia management and on the impact of diet on gut microbiome.

Nutritional Adequacy of Essential Nutrients in Low Protein Animal-Based and Plant-Based Diets in the United States for Chronic Kidney Disease Patients.

OBJECTIVES: The nutritional adequacy of both animal-based and plant-based low protein diets (LPDs) and moderate protein diets that are recommended for patients with chronic kidney disease have not been well examined. We therefore analyzed the nutrient content of three representative LPDs and moderate protein diets (lacto-ovo vegetarian, omnivorous, and vegan) containing foods that are likely to be prescribed for nondialyzed chronic kidney disease or chronic dialysis patients in the United States to determine the nutritional adequacy at different levels of protein intake. METHODS: Theoretical 3-day menus were developed as per current renal dietary guidelines to model each diet at 7 different levels of protein intake (0.5-1.2 g/kilograms body weight/day [g/kg/d]). The diets were analyzed for their content of essential amino acids (EAAs) and other essential nutrients. RESULTS: At an a priori recognized inadequate dietary protein level of 0.5 g/kg/d, all 3 diets failed to meet the Recommended Dietary Allowances (RDAs) for the following EAAs: histidine, leucine, lysine, and threonine. The omnivorous LPD met both the RDA and Estimated Average Requirement at levels of 0.6 g protein/kg/d or more. The lacto-ovo and vegan diets at 0.6 and 0.8 g protein/kg/d, respectively, were below the RDA for lysine. The amounts of several other vitamins and minerals were not uncommonly reduced below the RDA or Adequate Intake with all 3 LPDs. CONCLUSION: In comparison to omnivorous LPDs, both vegan and lacto-ovo LPDs are more likely to be deficient in several EAAs and other essential nutrients. To provide sufficient amounts of all EAA, vegan and lacto-ovo LPDs must be carefully planned to include adequate amounts of appropriate dietary sources. Supplements of some other essential nutrients may be necessary with all three LPDs.

New Insights Into Dietary Approaches to Potassium Management in Chronic Kidney Disease.

Potassium disorders are one of the most common electrolyte abnormalities in patients with chronic kidney disease (CKD), contributing to poor clinical outcomes. Maintaining serum potassium levels within the physiologically normal range is critically important in these patients. Dietary potassium restriction has long been considered a core strategy for the management of chronic hyperkalemia in patients with CKD. However, this has been challenged by recent evidence suggesting a paradigm shift toward fostering more liberalized, plant-based dietary patterns. The advent of novel potassium binders and an improved understanding of gastrointestinal processes involved in potassium homeostasis (e.g., gastrointestinal potassium wasting) may facilitate a paradigm shift and incorporation of heart-healthy potassium-enriched food sources. Nevertheless, uncertainty regarding the risk-benefit of plant-based diets in the context of potassium management in CKD remains, requiring well-designed clinical trials to determine the efficacy of dietary potassium manipulation toward improvement of clinical outcomes in patients with CKD.

Understanding, discovery, and synthesis of 2D materials enabled by machine learning.

Machine learning (ML) is becoming an effective tool for studying 2D materials. Taking as input computed or experimental materials data, ML algorithms predict the structural, electronic, mechanical, and chemical properties of 2D materials that have yet to be discovered. Such predictions expand investigations on how to synthesize 2D materials and use them in various applications, as well as greatly reduce the time and cost to discover and understand 2D materials. This tutorial review focuses on the understanding, discovery, and synthesis of 2D materials enabled by or benefiting from various ML techniques. We introduce the most recent efforts to adopt ML in various fields of study regarding 2D materials and provide an outlook for future research opportunities. The adoption of ML is anticipated to accelerate and transform the study of 2D materials and their heterostructures.

Ingrained: An Automated Framework for Fusing Atomic-Scale Image Simulations into Experiments.

To fully leverage the power of image simulation to corroborate and explain patterns and structures in atomic resolution microscopy, an initial correspondence between the simulation and experimental image must be established at the outset of further high accuracy simulations or calculations. Furthermore, if simulation is to be used in context of highly automated processes or high-throughput optimization, the process of finding this correspondence itself must be automated. In this work, "ingrained," an open-source automation framework which solves for this correspondence and fuses atomic resolution image simulations into the experimental images to which they correspond, is introduced. Herein, the overall "ingrained" workflow, focusing on its application to interface structure approximations, and the development of an experimentally rationalized forward model for scanning tunneling microscopy simulation are described.

AXEAP: a software package for X-ray emission data analysis using unsupervised machine learning.

The Argonne X-ray Emission Analysis Package (AXEAP) has been developed to calibrate and process X-ray emission spectroscopy (XES) data collected with a two-dimensional (2D) position-sensitive detector. AXEAP is designed to convert a 2D XES image into an XES spectrum in real time using both calculations and unsupervised machine learning. AXEAP is capable of making this transformation at a rate similar to data collection, allowing real-time comparisons during data collection, reducing the amount of data stored from gigabyte-sized image files to kilobyte-sized text files. With a user-friendly interface, AXEAP includes data processing for non-resonant and resonant XES images from multiple edges and elements. AXEAP is written in MATLAB and can run on common operating systems, including Linux, Windows, and MacOS.

Machine learning for impurity charge-state transition levels in semiconductors from elemental properties using multi-fidelity datasets.

Quantifying charge-state transition energy levels of impurities in semiconductors is critical to understanding and engineering their optoelectronic properties for applications ranging from solar photovoltaics to infrared lasers. While these transition levels can be measured and calculated accurately, such efforts are time-consuming and more rapid prediction methods would be beneficial. Here, we significantly reduce the time typically required to predict impurity transition levels using multi-fidelity datasets and a machine learning approach employing features based on elemental properties and impurity positions. We use transition levels obtained from low-fidelity (i.e., local-density approximation or generalized gradient approximation) density functional theory (DFT) calculations, corrected using a recently proposed modified band alignment scheme, which well-approximates transition levels from high-fidelity DFT (i.e., hybrid HSE06). The model fit to the large multi-fidelity database shows improved accuracy compared to the models trained on the more limited high-fidelity values. Crucially, in our approach, when using the multi-fidelity data, high-fidelity values are not required for model training, significantly reducing the computational cost required for training the model. Our machine learning model of transition levels has a root mean squared (mean absolute) error of 0.36 (0.27) eV vs high-fidelity hybrid functional values when averaged over 14 semiconductor systems from the II-VI and III-V families. As a guide for use on other systems, we assessed the model on simulated data to show the expected accuracy level as a function of bandgap for new materials of interest. Finally, we use the model to predict a complete space of impurity charge-state transition levels in all zinc blende III-V and II-VI systems.

Comparative study of SRS end-to-end QA processes of a diode array device and an anthropomorphic phantom loaded with GafChromic XD film.

PURPOSE: End-to-end testing (E2E) is a necessary process for assessing the readiness of the stereotactic radiosurgery (SRS) program and annual QA of an SRS system according to the AAPM MPPG 9a. This study investigates the differences between using a new SRS MapCHECK (SRSMC) system and an anthropomorphic phantom film-based system in a large network with different SRS delivery techniques. METHODS AND MATERIALS: Three SRS capable Linacs (Varian Medical Systems, Palo Alto, CA) at three different regional sites were chosen to represent a hospital network, a Trilogy with an M120 multi-leaf collimator (MLC), a TrueBeam with an M120 MLC, and a TrueBeam Stx with an HD120 MLC. An anthropomorphic STEEV phantom (CIRS, Norfolk, VA) and a phantom/diode array: StereoPHAN/SRSMC (Sun Nuclear, Melbourne, FL) were CT scanned at each site. The new STV-PHANTOM EBT-XD films (Ashland, Bridgewater, NJ) were used. Six plans with various complexities were measured with both films and SRSMC in the StereoPHAN to establish their dosimetric correlations. Three SRS cranial plans with a total of sixteen fields using dynamic conformal arc and volumetric-modulated arc therapy, with 1-4 targets, were planned with Eclipse v15.5 treatment planning system (TPS) using a custom SRS beam model for each machine. The dosimetric and localization accuracy were compared. The time of analysis for the two systems by three teams of physicists was also compared to assess the throughput efficiency. RESULTS: The correlations between films and SRSMC were found to be 0.84 (p = 0.03) and 0.16 (p = 0.76) for γ (3%, 1 mm) and γ (3%, 2 mm), respectively. With film, the local dose differences (ΔD) relative to the average dose within the 50% isodose line from the three sites were found to be -3.2%-3.7%. The maximum localization errors (Elocal ) were found to be within 0.5 ± 0.2 mm. With SRSMC, the ΔD was found to be within 5% of the TPS calculation. Elocal were found to be within 0.7 to 1.1 ± 0.4 mm for TrueBeam and Trilogy, respectively. Comparing with film, an additional uncertainty of 0.7 mm was found with SRSMC. The delivery and analysis times were found to be 6 and 2 h for film and SRSMC, respectively. CONCLUSIONS: The SRS MapCHECK agrees dosimetrically with the films within measurement uncertainties. However, film dosimetry shows superior sub-millimeter localization resolving power for the MPPG 9a implementation.

Mechanistic Investigation of Molybdenum Disulfide Defect Photoluminescence Quenching by Adsorbed Metallophthalocyanines.

Lattice defects play an important role in determining the optical and electrical properties of monolayer semiconductors such as MoS2. Although the structures of various defects in monolayer MoS2 are well studied, little is known about the nature of the fluorescent defect species and their interaction with molecular adsorbates. In this study, the quenching of the low-temperature defect photoluminescence (PL) in MoS2 is investigated following the deposition of metallophthalocyanines (MPcs). The quenching is found to significantly depend on the identity of the phthalocyanine metal, with the quenching efficiency decreasing in the order CoPc > CuPc > ZnPc, and almost no quenching by metal-free H2Pc is observed. Time-correlated single photon counting (TCSPC) measurements corroborate the observed trend, indicating a decrease in the defect PL lifetime upon MPc adsorption, and the gate voltage-dependent PL reveals the suppression of the defect emission even at large Fermi level shifts. Density functional theory modeling argues that the MPc complexes stabilize dark negatively charged defects over luminescent neutral defects through an electrostatic local gating effect. These results demonstrate the control of defect-based excited-state decay pathways via molecular electronic structure tuning, which has broad implications for the design of mixed-dimensional optoelectronic devices.

First principles modeling of polymer encapsulant degradation in Si photovoltaic modules.

An outstanding issue in the longevity of photovoltaic (PV) modules is the accelerated degradation caused by the presence of moisture. Moisture leads to interfacial instability, de-adhesion, encapsulant decomposition, and contact corrosion. However, experimental characterization of moisture in PV modules is not trivial and its impacts can take years or decades to establish in the field, presenting a major obstacle to designing high-reliability modules. First principles calculations provide an alternative way to study the ingress of water and its detrimental effect on the structure and decomposition of the polymer encapsulant and interfaces between the encapsulant and the semiconductor, the metal contacts, or the dielectric layer. In this work, we use density functional theory (DFT) computations to model single chain, crystalline and cross-linked structures, infrared (IR) signatures, and degradation mechanisms of ethylene vinyl acetate (EVA), the most common polymer encapsulant used in Si PV modules. IR-active modes computed for low energy EVA structures and possible decomposition products match well with reported experiments. The EVA decomposition energy barriers computed using the Nudged Elastic Band (NEB) method show a preference for acetic acid formation as compared to acetaldehyde, are lowered in the presence of a water solvent or hydroxyl ion catalyst, and match well with reported experimental activation energies. This systematic study leads to a clear picture of the hydrolysis-driven decomposition of EVA in terms of energetically favorable mechanisms, possible intermediate structures, and IR signatures of reactants and products.

Growth effects in oregano plants (Origanum vulgare L.) assessment through inoculation of bacteria isolated from crop fields located on desert soils.

Bacteria can establish beneficial interactions with plants by acting as growth promoters and enhancing stress tolerance during plant interactions. Likewise, bacteria can develop multispecies communities where multiple interactions are possible. In this work, we assessed the physiological effects of three bacteria isolated from an arid environment (Bacillus niacini, Bacillus megaterium, and Moraxella osloensis) applied as single species or as a consortium on oregano (Origanum vulgare L.) plants. Moreover, we assessed the quorum-sensing (QS) signaling activity to determine the molecular communication between plant-growth-promoting bacteria. The plant inoculation with B. megaterium showed a positive effect on morphometric and physiologic parameters. However, no synergistic effects were observed when a bacterial consortium was inoculated. Likewise, activation of QS signaling in biofilm assays was observed only for interspecies interaction within the Bacillus genus, not for either interaction with M. osloensis. These results suggest a neutral or antagonistic interaction for interspecific bacterial biofilm establishment, as well as for the interaction with oregano plants when bacteria were inoculated in a consortium. In conclusion, we were able to determine that the bacterial interactions are not always positive or synergistic, but they also might be neutral or antagonistic.

Commissioning of optical surface imaging systems for cranial frameless stereotactic radiosurgery.

PURPOSE: This study aimed to evaluate and compare different system calibration methods from a large cohort of systems to establish a commissioning procedure for surface-guided frameless cranial stereotactic radiosurgery (SRS) with intrafractional motion monitoring and gating. Using optical surface imaging (OSI) to guide non-coplanar SRS treatments, the determination of OSI couch-angle dependency, baseline drift, and gated-delivered-dose equivalency are essential. METHODS: Eleven trained physicists evaluated 17 OSI systems at nine clinical centers within our institution. Three calibration methods were examined, including 1-level (2D), 2-level plate (3D) calibration for both surface image reconstruction and isocenter determination, and cube phantom calibration to assess OSI-megavoltage (MV) isocenter concordance. After each calibration, a couch-angle dependency error was measured as the maximum registration error within the couch rotation range. A head phantom was immobilized on the treatment couch and the isocenter was set in the middle of the brain, marked with the room lasers. An on-site reference image was acquired at couch zero, the facial region of interest (ROI) was defined, and static verification images were captured every 10° for 0°-90° and 360°-270°. The baseline drift was assessed with real-time monitoring of the motionless phantom over 20 min. The gated-delivered-dose equivalency was assessed using the electron portal imaging device and gamma test (1%/1mm) in reference to non-gated delivery. RESULTS: The maximum couch-angle dependency error occurs in longitudinal and lateral directions and is reduced significantly (P < 0.05) from 1-level (1.3 ± 0.4 mm) to 2-level (0.8 ± 0.3 mm) calibration. The MV cube calibration does not further reduce the couch-angle dependency error (0.8 ± 0.2 mm) on average. The baseline drift error plateaus at 0.3 ± 0.1 mm after 10 min. The gated-delivered-dose equivalency has a >98% gamma-test passing rate. CONCLUSION: A commissioning method is recommended using the 3D plate calibration, which is verified by radiation isocenter and validated with couch-angle dependency, baseline drift, and gated-delivered-dose equivalency tests. This method characterizes OSI uncertainties, ensuring motion-monitoring accuracy for SRS treatments.

Spectroscopic Comparison of Thermal Transport at Organic-Inorganic and Organic-Hybrid Interfaces Using CsPbBr3 and FAPbBr3 (FA = Formamidinium) Perovskite Nanocrystals.

Thermal transport across interfaces depends on the matching of vibrational structure at the interface. This work examines the transfer of thermal excitation from an organic ligand coating to either all-inorganic cesium lead tribromide (CsPbBr3) nanocrystals or hybrid organic-inorganic formamidinium lead tribromide (FAPbBr3) nanocrystals using selective infrared optical excitation. These two semiconductors are directly compared because they (or similar semiconductors) are currently envisioned as strong candidates in many optoelectronic technologies and they differ due to the presence of an organic or inorganic cation, which introduces substantial differences in the phonon density of states in otherwise quite similar semiconductors. Infrared excitation of C-H vibrations of surface-bound ligands generates a temperature gradient between the organic ligand shell and nanocrystal core, which results in heat flow, measured by probing changes of the semiconductor band gap. Heat transfer to both perovskite compositions of comparable sizes is similar (25-30 ps), due to fast intramolecular vibrational relaxation and similar matching of low-energy phonons with the organic ligand, but FAPbBr3 samples show a slow bleaching kinetic on the order of 1 ns. This slow, heat-induced change in the semiconductor band gap is attributed not to interfacial heat transfer but instead to thermal equilibration between the organic and inorganic sublattices of FAPbBr3. Ab initio molecular dynamics simulations support the hypothesis that low-energy inorganic sublattice phonon modes are populated initially in the heat transfer process, with a slow thermal population of the higher-energy phonon modes associated primarily with the organic cation. Slow thermal equilibration of FAPbBr3 is likely to substantially impact the time-dependent response of optoelectronic devices that heat the semiconductor active layer and provide further evidence that the poor bulk thermal transport of hybrid perovskite materials extends to microscopic thermal processes.

Identification of a 'Candidatus Phytoplasma hispanicum'-related strain, associated with yellows-type diseases, in smoke-tree sharpshooter (Homalodisca liturata Ball).

The 16SrXIII group from phytoplasma bacteria were identified in salivary glands from Homalodisca liturata, which were collected in El Comitán on the Baja California peninsula in Mexico. We were able to positively identify 15 16S rRNA gene sequences with the corresponding signature sequence of 'CandidatusPhytoplasma' (CAAGAYBATKATGTKTAGCYGGDCT) and in silico restriction fragment length polymorphism (RFLP) profiles (F value estimations) coupled with a phylogenetic analysis to confirm their relatedness to 'CandidatusPhytoplasma hispanicum', which in turn belongs to the 16SrXIII group. A restriction analysis was carried out with AluI and EcoRI to confirm that the five sequences belongs to subgroup D. The rest of the sequences did not exhibit any known RFLP profile related to a subgroup reported in the 16SrXIII group.

Atomistic determination of the surface structure of Cu2O(111): experiment and theory.

Cuprous oxide (Cu2O) is a promising catalyst for several important reactions. However, the atomic structures of defective Cu2O surfaces, which critically affect the catalytic properties both thermodynamically and kinetically, are not unambiguously characterized. High-resolution scanning tunneling microscopy (STM), combined with density functional theory (DFT) calculations and STM simulations, has been used to determine the atomic structure of the (111) surface of a Cu2O bulk crystal. The single crystal surface, processed by ultrahigh vacuum cleaning and oxygen annealing, shows a (1 × 1) periodicity in the low-energy electron diffraction pattern. The pristine (defect-free) Cu2O(111) surface exhibits a lattice of protrusions with hexagonal symmetry under STM, which is attributed to the dangling bonds of the coordinatively unsaturated copper (CuU) atoms on the surface. Two types of surface atomic defects are also identified, including the CuU vacancy and the oxygen-vacancy-induced local surface restructuring. The electronic structure of this surface measured by dI/dV spectroscopy shows an energy band gap of ∼1.6-2.1 eV. Consistent with dI/dV measurements, DFT calculations identified surface states within the electronic band gap arising from the Cu ions on the surface. Our results provide a clear picture of the pristine and defective Cu2O(111) surface structure in addition to the formation mechanism of the reconstructed surface, paving the way toward studying the site-dependent reactivity of this surface.