Solution-processable mixed-anion cluster chalcohalide Rb6Re6S8I8 in a light-emitting diode.

Rhenium chalcohalide cluster compounds are a photoluminescent family of mixed-anion chalcohalide cluster materials. Here we report the new material Rb6Re6S8I8, which crystallizes in the cubic space group Fm[Formula: see text]m and contains isolated [Re6S8I6]4- clusters. Rb6Re6S8I8 has a band gap of 2.06(5) eV and an ionization energy of 5.51(3) eV, and exhibits broad photoluminescence (PL) ranging from 1.01 eV to 2.12 eV. The room-temperature PL exhibits a PL quantum yield of 42.7% and a PL lifetime of 77 µs (99 µs at 77 K). Rb6Re6S8I8 is found to be soluble in multiple polar solvents including N,N-dimethylformamide, which enables solution processing of the material into films with thickness under 150 nm. Light-emitting diodes based on films of Rb6Re6S8I8 were fabricated, demonstrating the potential for this family of materials in optoelectronic devices.

Using Surface Composition and Energy to Control the Formation of Either Tetrahexahedral or Hexoctahedral High-Index Facet Nanostructures.

High-index facet nanoparticles with structurally complex shapes, such as tetrahexahedron (THH) and hexoctahedron (HOH), represent a class of materials that are important for catalysis, and the study of them provides a fundamental understanding of the relationship between surface structures and catalytic properties. However, the high surface energies render them thermodynamically unfavorable compared to low-index facets, thereby making their syntheses challenging. Herein, we report a method to control the shape of high-index facet Cu nanoparticles (either THH with {210} facets or HOH with {421} facets) by tuning the facet surface energy with trace amounts of Te atoms. Density functional theory (DFT) calculations reveal that the density of Te atoms on Cu nanoparticles can change the relative stability of the high-index facets associated with either the THH or HOH structures. By controlling the annealing conditions and the rate of Te dealloying from CuTe nanoparticles, the surface density of Te atoms can be deliberately adjusted, which can be used to force the formation of either THH (higher surface Te density) or HOH (lower surface Te density) nanoparticles.

Crystal structure engineering in multimetallic high-index facet nanocatalysts.

In the context of metal particle catalysts, composition, shape, exposed facets, crystal structure, and atom distribution dictate activity. While techniques have been developed to control each of these parameters, there is no general method that allows one to optimize all parameters in the context of polyelemental systems. Herein, by combining a solid-state, Bi-influenced, high-index facet shape regulation strategy with thermal annealing, we achieve control over crystal structure and atom distribution on the exposed high-index facets, resulting in an unprecedentedly diverse library of chemically disordered and ordered multimetallic (Pt, Co, Ni, Cu, Fe, and Mn) tetrahexahedral (THH) nanoparticles. Density functional theory calculations show that surface Bi modification stabilizes the {210} high-index facets of the nanoparticles, regardless of their internal atomic ordering. Moreover, we find that the ordering transition temperatures for the nanoparticles are dependent on their composition, and, in the case of Pt3Fe1 THH nanoparticles, increasing Ni substitution leads to an order-to-disorder transition at 900 °C. Finally, we have discovered that ordered intermetallic THH Pt1Co1 nanocatalysts exhibit a catalytic performance superior to disordered THH Pt1Co1 nanoparticles and commercial Pt/C catalysts toward methanol electrooxidation, highlighting the importance of crystal structure and atom distribution control on high-index facets in nanoscale catalysts.

Accelerated Screening of Ternary Chalcogenides for Potential Photovoltaic Applications.

Chalcogenides, which refer to chalcogen anions, have attracted considerable attention in multiple fields of applications, such as optoelectronics, thermoelectrics, transparent contacts, and thin-film transistors. In comparison to oxide counterparts, chalcogenides have demonstrated higher mobility and p-type dopability, owing to larger orbital overlaps between metal-X covalent chemical bondings and higher-energy valence bands derived by p-orbitals. Despite the potential of chalcogenides, the number of successfully synthesized compounds remains relatively low compared to that of oxides, suggesting the presence of numerous unexplored chalcogenides with fascinating physical characteristics. In this study, we implemented a systematic high-throughput screening process combined with first-principles calculations on ternary chalcogenides using 34 crystal structure prototypes. We generated a computational material database containing over 400,000 compounds by exploiting the ion-substitution approach at different atomic sites with elements in the periodic table. The thermodynamic stabilities of the candidates were validated using the chalcogenides included in the Open Quantum Materials Database. Moreover, we trained a model based on crystal graph convolutional neural networks to predict the thermodynamic stability of novel materials. Furthermore, we theoretically evaluated the electronic structures of the stable candidates using accurate hybrid functionals. A series of in-depth characteristics, including the carrier effective masses, electronic configuration, and photovoltaic conversion efficiency, was also investigated. Our work provides useful guidance for further experimental research in the synthesis and characterization of such chalcogenides as promising candidates, as well as charting the stability and optoelectronic performance of ternary chalcogenides.

Cubic Stuffed-Diamond Semiconductors LiCu3TiQ4 (Q = S, Se, and Te).

Lithium chalcogenides have been understudied, owing to the difficulty in managing the chemical reactivity of lithium. These materials are of interest as potential ion conductors and thermal neutron detectors. In this study, we describe three new cubic lithium copper chalcotitanates that crystallize in the P4̅3m space group. LiCu3TiS4, a = 5.5064(6) Å, and LiCu3TiSe4, a = 5.7122(7) Å, represent two members of a new stuffed diamond-type crystal structure, while LiCu3TiTe4, a = 5.9830(7) Å crystallized into a similar structure exhibiting lithium and copper mixed occupancy. These structures can be understood as hybrids of the zinc-blende and sulvanite structure types. In situ powder X-ray diffraction was utilized to construct a "panoramic" reaction map for the preparation of LiCu3TiTe4, facilitating the design of a rational synthesis and uncovering three new transient phases. LiCu3TiS4 and LiCu3TiSe4 are thermally stable up to 1000 °C under vacuum, while LiCu3TiTe4 partially decomposes when slowly cooled to 400 °C. Density functional theory calculations suggest that these compounds are indirect band gap semiconductors. The measured work functions are 4.77(5), 4.56(5), and 4.69(5) eV, and the measured band gaps are 2.23(5), 1.86(5), and 1.34(5) eV for the S, Se, and Te analogues, respectively.

Regioselective Deposition of Metals on Seeds within a Polymer Matrix.

We use scanning probe block copolymer lithography in a two-step sequential manner to explore the deposition of secondary metals on nanoparticle seeds. When single element nanoparticles (Au, Ag, Cu, Co, or Ni) were used as seeds, both heterogeneous and homogeneous growth occurred, as rationalized using the thermodynamic concepts of bond strength and lattice mismatch. Specifically, heterogeneous growth occurs when the heterobond strength between the seed and growth atoms is stronger than the homobond strength between the growth atoms. Moreover, the resulting nanoparticle structure depends on the degree of lattice mismatch between the seed and growth metals. Specifically, a large lattice mismatch (e.g., 13.82% for Au and Ni) typically resulted in heterodimers, whereas a small lattice mismatch (e.g., 0.19% for Au and Ag) resulted in core-shell structures. Interestingly, when heterodimer nanoparticles were used as seeds, the secondary metals deposited asymmetrically on one side of the seed. By programming the deposition conditions of Ag and Cu on AuNi heterodimer seeds, two distinct nanostructures were synthesized with (1) Ag and Cu on the Au domain and (2) Ag on the Au domain and Cu on the Ni domain, illustrating how this technique can be used to predictively synthesize structurally complex, multimetallic nanostructures.

Low Thermal Conductivity in Heteroanionic Materials with Layers of Homoleptic Polyhedra.

Although BiAgOSe, an analogue of a well-studied thermoelectric material BiCuOSe, is thermodynamically stable, its synthesis is complicated by the low driving force of formation from the stable binary and ternary intermediates. Here we have developed a "subtraction strategy" to suppress byproducts and produce pure phase BiAgOSe using hydrothermal methods. Electronic structure calculations and optical characterization show that BiAgOSe is an indirect bandgap semiconductor with a bandgap of 0.95 eV. The prepared sample exhibits lower lattice thermal conductivities (0.61 W·m-1·K-1 at room temperature and 0.35 W·m-1·K-1 at 650 K) than BiCuOSe. Lattice dynamical simulations and variable temperature diffraction measurements demonstrate that the low lattice thermal conductivity arises from both the low sound velocity and high phonon-phonon scattering rates in BiAgOSe. These in turn result primarily from the soft Ag-Se bonds in the edge-sharing AgSe4 tetrahedra and large sublattice mismatch between the quasi-two-dimensional [Bi2O2]2+ and [Ag2Se2]2- layers. These results highlight the advantages of manipulating the chemistry of homoleptic polyhedra in heteroanionic compounds for electronic structure and phonon transport control.

Mixed Anion Semiconductor In8S2.82Te6.18(Te2)3.

The new heteroanionic compound In8S2.82Te6.18(Te2)3 crystallizes in the monoclinic space group C2/c with lattice parameters a = 14.2940(6) Å, b = 14.3092(4) Å, c = 14.1552(6) Å, and ß = 90.845(3)°. The three-dimensional (3D) framework of In8S2.82Te6.18(Te2)3 is composed of a complex 3D network of corner-connected InQ4 tetrahedra with three Te22- dumbbell dimers per formula unit. The optical bandgap is 1.12(2) eV and the work function is 5.15(5) eV. First-principles electronic structure calculations using density functional theory (DFT) indicate that this material has potential as a p-type thermoelectric material as it is a narrow bandgap semiconductor, incorporates several heavy elements, and has multiple overlapping bands near the valence band maximum.

2D Homologous Series SrFMnBiSn+2 (M = Pb, Ag0.5Bi0.5; n = 0, 1) and Commensurately Modulated Sr2F2Bi2/3S2.

We report three new mixed-anion two-dimensional (2D) compounds: SrFPbBiS3, SrFAg0.5Bi1.5S3, and Sr2F2Bi2/3S2. Their structures as well as the parent compound SrFBiS2 were refined using single-crystal X-ray diffraction data, with the sequence of SrFBiS2, SrFPbBiS3, and SrFAg0.5Bi1.5S3 defining the new homologous series SrFMnBiSn+2 (M = Pb, Ag0.5Bi0.5; n = 0, 1). Sr2F2Bi2/3S2 has a different structure, which is modulated with a q vector of 1/3b* and was refined in superspace group X2/m(0ß0)00 as well as in the 1 × 3 × 1 superstructure with space group C2/m (with similar results). Sr2F2Bi2/3S2 features hexagonal layers of alternating [Sr2F2]2+ and [Bi2/3S2]2-, and the modulated structure arises from the unique ordering pattern of Sr2+ cations. SrFPbBiS3, SrFAg0.5Bi1.5S3, and Sr2F2Bi2/3S2 are semiconductors with band gaps of 1.31, 1.21, and 1.85 eV, respectively. The latter compound exhibits room temperature red photoluminescence at ∼700 nm.

In Situ Mechanistic Studies of Two Divergent Synthesis Routes Forming the Heteroanionic BiOCuSe.

Heteroanionic materials are a burgeoning class of compounds that offer new properties via the targeted selection of anions. However, understanding the design principles and achieving successful syntheses of new materials in this class are in their infancy. To obtain mechanistic insight and a panoramic view of the reaction progression from beginning to end of the formation of a heteroanionic material, we selected BiOCuSe, a well-known thermoelectric compound, and utilized in situ synchrotron powder diffraction as a function of temperature and time. BiOCuSe is a layered material, which crystallizes in a common mixed anion structure type: ZrSiAsFe. Two reactions of starting materials (Bi2O2Se + Cu2Se and Bi2O3 + Bi + 3Cu + 3Se) were studied to determine the effect of precursors on the reaction pathway. Our in situ investigation shows that the ternary-binary Bi2O2Se + Cu2Se reaction proceeds without intermediates to directly form BiOCuSe, while the binary-elemental Bi2O3 + Bi + 3Cu + 3Se reaction generates many intermediates before the final product forms. These intermediates include CuSe, Bi3Se4, Bi2Se3, and Cu2Se. While the stoichiometric loading of the precursors necessarily dictates the identity of the first intermediates, kinetics also plays a contributing role in stabilizing unexpected intermediates such as CuSe and Bi3Se4. Understanding and establishing a link between the selection of precursors and the reaction pathways improves the potential for rational synthesis of heteroanionic materials and solid-state reactions in general.

Fluoridation of HfO2.

Fluoridation of HfO2 was carried out with three commonly used solid-state fluoridation agents: PVDF, PTFE, and NH4HF2. Clear and reproducible differences are observed in the reaction products of the fluoropolymer reagents and NH4HF2 with the latter more readily reacting in air. Strong evidence of distinct, previously unreported hafnium oxyfluoride phases is produced by both reactions, and efforts to isolate them were successful for the air-NH4HF2 reaction. Synchrotron XRD, 19F NMR, and elemental analysis were employed to characterize the phase-pure material which appears to be analogous to known Zr-O-F phases with anion-deficient α-UO3 structures such as Zr7O9F10. Comparison with the hydrolysis of ß-HfF4 under identical conditions depicts that the NH4HF2 route produces the oxyfluoride with greater selectivity and at lower temperatures. Thermodynamic calculations were employed to explain this result. Potential reaction pathways for the NH4HF2 fluoridation of HfO2 are discussed.

Synthesis of Metal-Capped Semiconductor Nanowires from Heterodimer Nanoparticle Catalysts.

Semiconductor nanowires (NWs) capped with metal nanoparticles (NPs) show multifunctional and synergistic properties, which are important for applications in the fields of catalysis, photonics, and electronics. Conventional colloidal syntheses of this class of hybrid structures require complex sequential seeded growth, where each section requires its own set of growth conditions, and methods for preparing such wires are not universal. Here, we report a new and general method for synthesizing metal-semiconductor nanohybrids based on particle catalysts, prepared by scanning probe block copolymer lithography, and chemical vapor deposition. In this process, metallic heterodimer NPs were used as catalysts for NW growth to form semiconductor NWs capped with metallic particles (Au, Ag, Co, Ni). Interestingly, the growth processes for NWs on NPs are regioselective and controlled by the chemical composition of the metallic heterodimer used. Using a systematic experimental approach, paired with density functional theory calculations, we were able to postulate three different growth modes, one without precedent.

Predicting mortality in critically ill patients with diabetes using machine learning and clinical notes.

BACKGROUND: Diabetes mellitus is a prevalent metabolic disease characterized by chronic hyperglycemia. The avalanche of healthcare data is accelerating precision and personalized medicine. Artificial intelligence and algorithm-based approaches are becoming more and more vital to support clinical decision-making. These methods are able to augment health care providers by taking away some of their routine work and enabling them to focus on critical issues. However, few studies have used predictive modeling to uncover associations between comorbidities in ICU patients and diabetes. This study aimed to use Unified Medical Language System (UMLS) resources, involving machine learning and natural language processing (NLP) approaches to predict the risk of mortality. METHODS: We conducted a secondary analysis of Medical Information Mart for Intensive Care III (MIMIC-III) data. Different machine learning modeling and NLP approaches were applied. Domain knowledge in health care is built on the dictionaries created by experts who defined the clinical terminologies such as medications or clinical symptoms. This knowledge is valuable to identify information from text notes that assert a certain disease. Knowledge-guided models can automatically extract knowledge from clinical notes or biomedical literature that contains conceptual entities and relationships among these various concepts. Mortality classification was based on the combination of knowledge-guided features and rules. UMLS entity embedding and convolutional neural network (CNN) with word embeddings were applied. Concept Unique Identifiers (CUIs) with entity embeddings were utilized to build clinical text representations. RESULTS: The best configuration of the employed machine learning models yielded a competitive AUC of 0.97. Machine learning models along with NLP of clinical notes are promising to assist health care providers to predict the risk of mortality of critically ill patients. CONCLUSION: UMLS resources and clinical notes are powerful and important tools to predict mortality in diabetic patients in the critical care setting. The knowledge-guided CNN model is effective (AUC = 0.97) for learning hidden features.

Retraction Note: Large local lattice expansion in graphene adlayers grown on copper.

The authors unanimously wish to retract this Article due to their concerns about the interpretation of the low-energy electron microscopy (LEEM) and diffraction (LEED) patterns reported in the manuscript. In this study, the authors used spatial and angle-resolved photoemission spectroscopy (ARPES) to characterize graphene monolayers grown on copper foils, and observed regions of graphene adlayers with enhanced graphene/Cu interaction, higher Dirac cone doping level, moiré mini Dirac cones and large lattice expansion. All these properties have been clearly verified and reproduced by photoemission spectroscopy as well as explained by density functional theory. LEEM and LEED characterization were also carried out to confirm the existence of a moiré superlattice and lattice expansion, and the results were included in the main manuscript and Supplementary Information. On further analysis of the LEEM/LEED data, it seems that while the existence of a moiré superlattice can be corroborated, the conclusion of graphene lattice expansion (7%) based on spatially resolved ARPES determinations cannot be confirmed by the LEEM/LEED measurements. The authors realized that these measurements were collected from statistically non-representative areas of the sample. Moreover, the fact that the raw microLEED images bear an asymmetry factor of as much as 5% due to the instrumental aberration makes it impossible to estimate any compression or expansion of the same order. Consequently, their conclusion on the graphene lattice expansion can only be supported by the photoemission data. In view that more complete and reliable structural determinations should be conducted, all authors wish to retract this Article.

Large local lattice expansion in graphene adlayers grown on copper.

Variations of the lattice parameter can significantly change the properties of a material, and, in particular, its electronic behaviour. In the case of graphene, however, variations of the lattice constant with respect to graphite have been limited to less than 2.5% due to its well-established high in-plane stiffness. Here, through systematic electronic and lattice structure studies, we report regions where the lattice constant of graphene monolayers grown on copper by chemical vapour deposition increases up to ~7.5% of its relaxed value. Density functional theory calculations confirm that this expanded phase is energetically metastable and driven by the enhanced interaction between the substrate and the graphene adlayer. We also prove that this phase possesses distinctive chemical and electronic properties. The inherent phase complexity of graphene grown on copper foils revealed in this study may inspire the investigation of possible metastable phases in other seemingly simple heterostructure systems.

Carnosine ameliorates postoperative cognitive dysfunction of aged rats by limiting astrocytes pyroptosis.

Postoperative cognitive dysfunction (POCD) is a common postoperative complication in elderly patients, and neuroinflammation is a key hallmark. Recent studies suggest that the NOD-like receptor family, pyrin domain containing 3 (NLRP3) inflammasome-mediated astrocytes pyroptosis is involved in the regulation of neuroinflammation in many neurocognitive diseases, while its role in POCD remains obscure. Carnosine is a natural endogenous dipeptide with anti-inflammatory and neuroprotective effects. To explore the effect of carnosine on POCD and its mechanism, we established a POCD model by exploratory laparotomy in 24-month-old male Sprague-Dawley rats. We found that the administrated of carnosine notably attenuated surgery-induced NLRP3 inflammasome activation and pyroptosis in astrocytes, central inflammation, and neuronal damage in the hippocampus of aged rats. In addition, carnosine dramatically ameliorated the learning and memory deficits of surgery-induced aged rats. Then in the in vitro experiments, we stimulated primary astrocytes with lipopolysaccharide (LPS) after carnosine pretreatment. The results also showed that the application of carnosine alleviated the activation of the NLRP3 inflammasome, pyroptosis, and inflammatory response in astrocytes stimulated by LPS. Taken together, these findings suggest that carnosine improves POCD in aged rats via inhibiting NLRP3-mediated astrocytes pyroptosis and neuroinflammation.

Esketamine Prevents Postoperative Emotional and Cognitive Dysfunction by Suppressing Microglial M1 Polarization and Regulating the BDNF-TrkB Pathway in Ageing Rats with Preoperative Sleep Disturbance.

Postoperative depression (POD) and postoperative cognitive dysfunction (POCD) have placed heavy burden on patients' physical and mental health in recent years. Sleep disturbance before surgery is a common phenomenon that has been increasingly believed to affect patients' recovery, especially in aged patients, while little attention has been paid to sleep disruption before surgery and the potential mechanism remains ambiguous. Ketamine has been reported to attenuate POCD after cardiac surgery and elicit rapid-acting and sustained antidepressant actions. The present study aimed to clarify the effect of esketamine's (the S-enantiomer of ketamine) protective effects and possible mechanisms of action in POCD and POD. Our results showed that sleep disturbance before surgery exacerbated microglial M1 polarization and microglial BDNF-TrkB signalling dysfunction induced by surgery, resulting in postoperative emotional changes and cognitive impairments. Notably, treatment with esketamine reversed the behavioural abnormalities through inhibiting the M1 polarization of microglia and the inflammatory response thus improving BDNF-TrkB signalling in vivo and vitro. In addition, esketamine administration also reversed the impaired hippocampal synaptic plasticity which has been perturbed by sleep disturbance and surgery. These findings warrant further investigations into the interplay of esketamine and may provide novel ideas for the implication of preoperative preparations and the prevention of postoperative brain-related complications.

Synthesis and symmetry of perovskite oxynitride CaW(O,N)3.

Perovskite oxynitrides, in addition to being promising electrocatalysts and photoabsorbers, present an interesting case study in crystal symmetry. Full or partial ordering of the O and N anions affects global symmetry and influences material performance and functionality; however, anion ordering is challenging to detect experimentally. In this work, we synthesize a novel perovskite oxynitride CaW(O,N)3 and characterize its crystal structure using both X-ray and neutron diffraction. Through co-refinement of the diffraction patterns with a range of literature and theory-derived model structures, we demonstrate that CaW(O,N)3 adopts an orthorhombic Pnma average structure and exhibits octahedral distortion with evidence for preferred anion site occupancy. However, through comparison with a large, low-symmetry unit cell, we identify the presence of disorder that is not fully accounted for by the high-symmetry model. We compare CaW(O,N)3 with SrW(O,N)3 to demonstrate the broader presence of such disorder and identify contrasting features in the electronic structures. This work signifies an updated perspective on the inherent crystal symmetry present in perovskite oxynitrides.

Ultrathin, Transferred Layers of Silicon Oxynitrides as Tunable Biofluid Barriers for Bioresorbable Electronic Systems.

Bio/ecoresorbable electronic systems create unique opportunities in implantable medical devices that serve a need over a finite time period and then disappear naturally to eliminate the need for extraction surgeries. A critical challenge in the development of this type of technology is in materials that can serve as thin, stable barriers to surrounding ground water or biofluids, yet ultimately dissolve completely to benign end products. This paper describes a class of inorganic material (silicon oxynitride, SiON) that can be formed in thin films by plasma-enhanced chemical vapor deposition for this purpose. In vitro studies suggest that SiON and its dissolution products are biocompatible, indicating the potential for its use in implantable devices. A facile process to fabricate flexible, wafer-scale multilayer films bypasses limitations associated with the mechanical fragility of inorganic thin films. Systematic computational, analytical, and experimental studies highlight the essential materials aspects. Demonstrations in wireless light-emitting diodes both in vitro and in vivo illustrate the practical use of these materials strategies. The ability to select degradation rates and water permeability through fine tuning of chemical compositions and thicknesses provides the opportunity to obtain a range of functional lifetimes to meet different application requirements.

Morphology Engineering in Multicomponent Hollow Metal Chalcogenide Nanoparticles.

Hollow metal chalcogenide nanoparticles are widely applicable in environmental and energy-related processes. Herein, we synthesized such particles with large compositional and morphological diversity by combining scanning probe block copolymer lithography with a Kirkendall effect-based sulfidation process. We explored the influence of temperature-dependent diffusion kinetics, elemental composition and miscibility, and phase boundaries on the resulting particle morphologies. Specifically, CoNi alloys form single-shell sulfides for the synthetic conditions explored because Co and Ni exhibit similar diffusion rates, while CuNi alloys form sulfides with various types of morphologies (yolk-shell, double-shell, and single-shell) because Cu and Ni have different diffusion rates. In contrast, Co-Cu heterodimers form hollow heterostructured sulfides with varying void numbers and locations depending on synthesis temperature and phase boundary. At higher temperatures, the increased miscibility of CoS2 and CuS makes it energetically favorable for the heterostructure to adopt a single alloy shell morphology, which is rationalized using density functional theory-based calculations.