Dinuclear Research Articles

Identification of copper death-associated molecular clusters and immunological profiles for lumbar disc herniation based on the machine learning

Lumbar disc herniation (LDH) is a common clinical spinal disorder, yet its etiology remains unclear. We aimed to explore the role of cuproptosis-related genes (CRGs) and identify potential diagnostic biomarkers. Our analysis involved interrogating the GSE124272 and GSE150408 datasets for differential gene expression profiles associated with CRGs and immune characteristics. Molecular clustering was performed on LDH samples, followed by expression and immune infiltration analyses. Using the WGCNA algorithm, specific genes within CRG clusters were identified. After selecting the most predictive genes from the optimal model, four machine learning models were constructed and validated. This study identified nine CRGs associated with copper-regulated cell death. Two copper-containing molecular clusters linked to death were detected in LDH samples. Elevated expression and immune infiltration levels were found in LDH patients, particularly in CRG cluster C2. Utilizing XGB, five genes were identified for constructing a diagnostic model, achieving an area under the curve values of 0.715. In conclusion, this research provides valuable insights into the association between LDH and copper-regulated cell death, alongside proposing a promising predictive model.

Sub-nanometric ruthenium clusters prepared by solid-state dispersion for catalytic selective aerobic oxidation of aromatic alcohols

The selective aerobic oxidation of alcohols to corresponding aldehydes is one of the most important challenges in the green chemical industry. In this work, Ru/Al2O3-SSD catalyst with highly dispersed metallic ruthenium clusters (average particle size of 0.97 nm) was prepared by solid-state dispersion (SSD) for efficient selective aerobic oxidation of aromatic alcohols to aldehydes. Compared with the counterpart catalyst Ru/Al2O3-IM prepared by wet impregnation (IM), this catalyst has smaller metal particles (0.97 nm vs. 3.4 nm), resulting in a special electronic structure, and exhibits much higher TOF (234 h−1 vs. 98 h−1) in the aerobic oxidation reaction of benzyl alcohol at 80 °C. The catalyst also shows excellent catalytic activity in the preparation of vanillin by selective aerobic oxidation of vanillyl alcohol at 100 °C, delivering a vanillin yield of 99%. The solid-state dispersion strategy provides an efficient and facile way for the fabrication of high-performance sub-nanometric metal catalysts.

Experimental and Computational 77Se NMR Spectroscopic Study on Selenaborane Cluster Compounds.

Calculated and measured 77Se nuclear magnetic resonance (NMR) chemical shift data on a diverse collection of 13 selenaborane cluster compounds, containing a total of 19 selenium centers, reveals a correlation between chemical shifts and the intracluster coordination of selenium atoms within their borane frameworks. A plot of the measured against calculated 77Se NMR chemical shifts shows an approximately linear relationship that can serve as a predictive tool in assessing the chemical shift range in which a selenium vertex from a particular compound might be expected to be found, thereby reducing expensive experimental time. Furthermore, the relative chemical shifts between selenium vertices in clusters containing more than one selenium atom are consistent across the range, thus allowing the assignment of the selenium resonances with a high degree of confidence even in relatively low-level density functional theory calculations. A new macropolyhedral 20-vertex selenaborane Se2B18H20 (A) is also reported.

Clustering Molecules at a Large Scale: Integrating Spectral Geometry with Deep Learning.

This study conducts an in-depth analysis of clustering small molecules using spectral geometry and deep learning techniques. We applied a spectral geometric approach to convert molecular structures into triangulated meshes and used the Laplace-Beltrami operator to derive significant geometric features. By examining the eigenvectors of these operators, we captured the intrinsic geometric properties of the molecules, aiding their classification and clustering. The research utilized four deep learning methods: Deep Belief Network, Convolutional Autoencoder, Variational Autoencoder, and Adversarial Autoencoder, each paired with k-means clustering at different cluster sizes. Clustering quality was evaluated using the Calinski-Harabasz and Davies-Bouldin indices, Silhouette Score, and standard deviation. Nonparametric tests were used to assess the impact of topological descriptors on clustering outcomes. Our results show that the DBN + k-means combination is the most effective, particularly at lower cluster counts, demonstrating significant sensitivity to structural variations. This study highlights the potential of integrating spectral geometry with deep learning for precise and efficient molecular clustering.

Cross-talk between oxidative stress and lipid metabolism regulators reveals molecular clusters and immunological characterization in polycystic ovarian syndrome

BackgroundChanges in the oxidative stress and lipid metabolism (OSLM) pathways play important roles in polycystic ovarian syndrome (PCOS) pathogenesis and development. Consequently, a systematic analysis of genes related to OSLM was conducted to identify molecular clusters and explore new biomarkers that are helpful for the diagnostic of PCOS.MethodsGene expression and clinical data from 22 PCOS women and 14 normal women were obtained from the GEO database (GSE34526, GSE95728, and GSE106724). Consensus clustering identified OSLM-related molecular clusters, and WGCNA revealed co-expression patterns. The immune microenvironment was quantitatively assessed utilizing the CIBERSORT algorithm. Multiple machine learning models and connectivity map analyses were subsequently applied to explore potential biomarkers for PCOS, and nomograms were employed to develop a predictive multigene model of PCOS. Finally, the OSLM status of PCOS and the hub genes expression profiles were preliminarily verified using TUNEL, qRT‒PCR, western blot, and IHC assays in a PCOS mouse model.Results19 differential expression genes (DEGs) related to OSLM were identified. Based on 19 DEGs that were strongly influenced by OSLM, PCOS patients were stratified into two distinct clusters, designated Cluster 1 and Cluster 2. Distinct differences in the immune cell proportions existed in normal and two PCOS clusters. The random forest showed the best results, with the least cross-entropy and the utmost AUC (cross-entropy: 0.111 AUC: 0.960). Among the 19 OSLM-related genes, CXCR1, ACP5, CEACAM3, S1PR4, and TCF7 were identified by a Bayesian network and had a good fit with PCOS disease risk by the nomogram (AUC: 0.990 CI: 0.968–1.000). TUNEL assays revealed more severe DNA damage within the ovarian granule cells of PCOS mice than in those of normal mice (P < 0.001). The RNA and protein expression levels of the five hub genes were significantly elevated in PCOS mice, which was consistent with the results of the bioinformatics analyses.ConclusionA novel predictive model was constructed for PCOS patients and five hub genes were identified as potential biomarkers to offer novel insights into clinical diagnostic strategies for PCOS.

A computational study of the role of cobalt in thiophene adsorption on small Mo and MoCo clusters as site models for the HDS process

Non periodic density functional theory calculations are used to investigate the role of cobalt atoms in the adsorption of thiophene on small Mo and MoCo clusters. Metallic aggregates play the role of those active sites found in the true catalysts. Two interaction modes between thiophene and metallic sites are considered, namely, the S-mode, in which the organosulfur molecule interacts through the S atom, and the R-mode, in which the interaction takes place through the thiophene ring. A large number of sites, in which thiophene effectively adsorbs, was found, both in the monometallic case and in the bimetallic one. Considerably larger adsorption energies were found when thiophene interacts via the R-mode than when adsorption occurs through the S-mode. The activation of C-S bonds is also more important for R-mode cases than for S-mode ones. Further analysis made on some selected systems and based on density of states and molecular orbital overlap population-projected density of states reveals that thiophene and metallic clusters interact in an energy range around −6.0 eV with respect to the Fermi energy. Bands observed at energies below −6.0 eV correspond to thiophene states that become shifted with respect to the values obtained for isolated thiophene depending on the strength of the interaction. Bands above -6.0 eV describe how C and S atoms interact with Co and Mo ones, providing both bonding and antibonding patterns that helps to understand the overall interaction. Most important is the finding that cobalt atoms seem to play no relevant role during the adsorption of thiophene on metallic sites. Thus, present results obtained using non periodic GGA density functional theory seem to point to cobalt taking part in another step of the overall HDS process, hydrogen adsorption or hydrogen attack to C-S bonds, for instance.

Quantum design of magnetic structures with enhanced magnetocaloric properties

Abstract The magnetization processes and magnetocaloric effect (MCE) of molecular magnets are studied using the quantum Heisenberg model with the goal of finding magnetic structures with optimal magnetocaloric properties. To fulfill this goal, we examine the influence of various factors such as quantum fluctuations, the magnitude and distribution of spins, the cluster size and its geometry on the conventional (cooling) and inverse (heating) MCE. We find, surprisingly, that the best cooling and heating effects are observed in the Ising limit on the smallest possible molecular clusters represented by dimers and trimers. The increasing Heisenberg interaction suppresses both the cooling as well as heating effects, but while the heating is reduced very strongly, for relatively small values of the anisotropic Heisenberg constant, the cooling effects are reduced only weakly. Since the heating effect is undesired in low-temperature refrigeration, the Heisenberg limit is also interesting from a practical point of view. Moreover, we find that spin distributions also have a significant influence on the magnetocaloric properties of molecular magnets. Specifically, configurations with large spins on the edges of the finite chain significantly enhance the cooling effect.

Engineering ZnIn2S4 with efficient charge separation and utilization for synergistic accelerate dual-function photocatalysis

Combining photocatalytic reduction with organic synthetic oxidation in the same photocatalytic redox system can effectively utilize photoexcited electrons and holes from solar to chemical energy. Here, we stabilized 0D Au clusters on the substrate surface of Zn vacancies modified 2D ZnIn2S4 (ZIS-V) nanosheets by chemically bonding Au-S interaction, forming surfactant functionalized Au/ZIS-V photocatalyst, which can not only synergistic accelerate the selective oxidation of phenylcarbinol to value-added products coupled with clean energy hydrogen production but also further drive photocatalytic CO2-to-CO conversion. An internal electric field of Au/ZIS-V ohmic junction and Zn vacancies synchronously promote the photoexcited charge carrier separation and transfer to optimized active sites for redox reactions. Compared with CO2 reduction in water and the pristine ZnIn2S4, the reaction thermodynamics and kinetics of CO2 reduction over the Au/ZIS-V were simultaneously improved about 11.09 and 45.51 times, respectively. Moreover, the photocatalytic redox mechanisms were also profoundly studied by 13CO2 isotope tracing tests, in situ electron paramagnetic resonance (in situ EPR), in situ X-ray photoelectron spectroscopy (in situ XPS), in situ diffuse reflection infrared Fourier transform spectroscopy (in situ DRIFTS) and density functional theory (DFT) characterizations, etc. These results demonstrate the advantages of vacancies coupled with metal clusters in the synergetic enhancement of photocatalytic redox performance and have great potential applications in a wide range of environments and energy.

In situ Construction of Single-Atom Electronic Bridge on COF to Enhance Photocatalytic H2 Production.

Photocatalytic hydrogen production is one of the most valuable technologies in the future energy system. Here, we designed a metal-covalent organic frameworks (MCOFs) with both small-sized metal clusters and nitrogen-rich ligands, named COF-Cu3TG. Based on our design, small-sized metal clusters were selected to increase the density of active sites and shorten the distance of electron transport to active sites. While another building block containing nitrogen-rich organic ligands acted as a node that could in situ anchor metal atoms during photocatalysis and form interlayer single-atom electron bridges (SAEB) to accelerate electron transport. Together, they promoted photocatalytic performance. This represented the further utilization of Ru atoms and was an additional application of the photosensitizer. N2-Ru-N2 electron bridge (Ru-SAEB) was created in situ between the layers, resulting in a considerable enhancement in the hydrogen production rate of the photocatalyst to 10.47 mmol g-1 h-1. Through theoretical calculation and EXAFS, the existence position and action mechanism of Ru-SAEB were reasonably inferred, further confirming the rationality of the Ru-SAEB configuration. A sufficiently proximity between the small-sized Cu3 cluster and the Ru-SAEB was found to expedite electron transfer. This work demonstrated the synergistic impact of small molecular clusters with Ru-SAEB for efficient photocatalytic hydrogen production.

Spectral selectivity of luminescence of a copper ion-exchange layer in sodium-potassium-magnesium silicate glass

The bright luminescence of the copper ion-exchange layer in glass has potential applications as a converter of electric spark and corona discharge radiation in devices for the rapid analysis of metals because of its selectivity. The selectivity of the luminescence of the copper ion-exchange layer was achieved by the presence of different luminescent centers within it. In this work, the copper monomers, Cu+-Cu+ monovalent dimers, and Cun molecular clusters were formed in an ion-exchange layer of sodium-potassium-magnesium silicate glass (SiO2-Na2O-CaO-MgO-Al2O3-K2O-Fe2O3). The luminescence of the copper ion exchange layer was characterized by steady-state spectroscopy and time-resolved spectroscopy. Molecular copper clusters Cun exhibited luminescence in the nanosecond range, and Cu+ monomers and Cu+-Cu+ monovalent dimers in the microsecond range, respectively. At the same time the formation of divalent copper led to a limitation in the duration of ion exchange for the production of luminescent glasses. Heat treatment of the ion-exchange layers led to an increase in the concentration of molecular copper clusters, Cu+-Cu+ monovalent dimers, and Cu2+ divalent monomers.

A new luminescent nickel nanocluster with solvent and ion induced emission enhancement toward heavy metal analysis

Expanding the family of fluorescent metal clusters beyond gold, silver, and copper has always been an issue for researchers to solve. In this study, a novel type of cysteine-capped nickel nanoclusters (Cys-Ni NCs) with bright turquoise emission was developed. The as-synthesized Ni NCs showed aggregation-induced emission enhancement (AIEE) properties across Cd2+ and various polar organic solvents. Concurrently, solvents with different viscosities were used to explore the principle of solvent-induced AIEE of Cys-Ni NCs, revealing a positive correlation between fluorescence intensity and solution viscosity. In addition, the concentration of Cd2+ that induced the AIEE effect was reduced by nearly two orders of magnitude in highly viscous solvents, indicating the possibility of Cys-Ni NCs as a promising nanomaterial platform for Cd2+ sensing analysis. Moreover, we propose a novel fluorescent sensing method for rapid detection of Cu2+ based on the carboxyl group of Cys-Ni NCs coupling with Cu2+. Further, validation of Cu2+ detecting methodologies in environmental water samples with the accuracy up to 93.94% underscores their potential as robust and efficient sensing platforms. This study expands the repertoire of fluorescent metal nanoclusters for highly sensitive and selective sensing of hazardous ions and paves the way for further exploration and wide applications in Cu2+ detection in biological and medicine fields.

(Invited) Synthesis of Multi-Metallic Nanoparticles for Advanced Catalysts

Dendrimers are highly branched organic macromolecules with successive layers or “generations” of branch units surrounding a central core. Organic inorganic hybrid versions have also been produced, by trapping metal ions or metal clusters within the voids of the dendrimers. Their unusual, tree-like topology endows these nanometer-sized macromolecules with a gradient in branch density from the interior to the exterior, which can be exploited to direct the transfer of charge and energy from the dendrimer periphery to its core.We show that PtCl4, SnCl2, FeCl3, and so on complexes to the imines groups of a spherical polyphenylazomethine dendrimer in a stepwise fashion according to an electron gradient, with complexation in a more peripheral generation proceeding only after complexation in generations closer to the core has been completed. By attaching an electron-withdrawing group to the dendrimer core, we are able to change the complexation pattern, so that the core imines are complexed last. By further extending this strategy, it should be possible to control the number and location of metal ions incorporated into dendrimer structures, which might and uses as tailored catalysts, building blocks, or fine-controlled clusters for advanced materials. The metal-assembly in a discrete dendrimer molecule can be converted to a size-regulated metal particle with a size smaller than 1 nm as a molecular reactor. Due to the well-defined number of metal clusters in the subnanometer region, its property is much different from that of bulk or general metal nanoparticles. The chemistry of nanocatalysts on the sub-nanometer scale is not yet well understood because precise multi-metallic nanoparticles are difficult to synthesize with control over size and composition. The template synthesis of multi-metallic sub-nanocalaysts is achieved using a phenylazomethine dendrimer as a macromolecular template.

Nanoparticle/Cellulose-Based Surface Enhanced Raman Scattering Hybrid Sensors

Surface-Enhanced Raman Scattering (SERS) sensors are versatile biosensors for detecting very low concentrations of molecules. Their molecular and chemical sensitivity crucially depends on the tailoring of their nanostructure. These sensors rely on noble metal or oxide cluster layers, with their crystallinity and nanostructure carefully tuned to enable a maximum of plasmonic hot spots and enabling charge transfer. Typically, such sensors are in thin film geometry. In order to optimize their nanostructure and optical properties of the metal or oxide clusters, cellulose nanofibrils (CNFs) as template for nanoparticle-biopolymer hybrid materials are readily employed due to their high mechanical strength and ability to establish nanoporous, scalable thin films via spray deposition.[1] In order to characterize their nanostructure during synthesis of the hybrid nanoparticle-CNF material, grazing incidence X-ray scattering (GIXS) is ideally suited due to its ability to observe the nanostructural changes during farication and optimization of the sensor materials. The resulting nanostructure is then directly correlation to the sensor capability of the hybrid materials. As a first example, we use the catalytic properties of CNF during thermal decomposition of silver nitrate as precursor for fabrication of size-tuned silver clusters on CNF to tune their optical band-gap. The correlation between hot-spot size and silver nanoparticle size for optimizing the SERS sensitivity is elucidated using GIXS, showing for the first time the optimum hot spot size.[2] In order to facilitate an equal distribution of hot-spots, we make use of the three-dimensional nanoporous structure of the CNF thin films by adding shell-free silver nanoparticles in aqueous solution, again applying spray deposition.[3] The nanoporosity allows for reducing drastically agglomerations of silver nanoparticles, detrimental to hot-spots. At the same time, the spectral position of the plasmon resonance is tuned by the amount of CNF as structural matrix. As a final example we extend these results to novel semiconductor metal oxide nanomaterial (SMON)-based sensors.[4] Here, titanium oxide is deposited via atomic layer deposition (ALD) on the nanoporous CNF network, preserving its three-dimensional morphology. We optimize the nanostructure, crystallinity and rutile-to-anatase ratio in order to obtain superior sensitivity of the hybrid titania/CNF thin films as SMON SERS substrates. The improvement of SERS activity relies on the cooperative modulation of the CNF network and the crystalline states of the deposited titania. To summarize, we present new routes for SERS sensors based on plasmonic and charge transfer properties of hybrid materials by tailoring the hybrid nanostructure.[1] Brett, C. J.; Ohm, W.; Fricke, B.; Alexakis, A. E.; Laarmann, T.; Körstgens, V.; Müller-Buschbaum, P.; Söderberg, L. D.; Roth, S. V. Nanocellulose-Assisted Thermally Induced Growth of Silver Nanoparticles for Optical Applications. ACS Appl. Mater. Interfaces 2021, 13 (23), 27696–27704. https://doi.org/10.1021/acsami.1c07544.[2] Santoro, G.; Yu, S.; Schwartzkopf, M.; Zhang, P.; Koyiloth Vayalil, S.; Risch, J. F. H.; Rübhausen, M. A.; Hernández, M.; Domingo, C.; Roth, S. V. Silver Substrates for Surface Enhanced Raman Scattering: Correlation between Nanostructure and Raman Scattering Enhancement. Appl. Phys. Lett. 2014, 104 (24), 243107. https://doi.org/10.1063/1.4884423.[3] Chen, Q.; Brett, C. J.; Chumakov, A.; Gensch, M.; Schwartzkopf, M.; Körstgens, V.; Söderberg, L. D.; Plech, A.; Zhang, P.; Müller-Buschbaum, P.; Roth, S. V. Layer-by-Layer Spray-Coating of Cellulose Nanofibrils and Silver Nanoparticles for Hydrophilic Interfaces. ACS Appl. Nano Mater. 2021, 4 (1), 503–513. https://doi.org/10.1021/acsanm.0c02819.[4] Chen, Q.; Betker, M.; Harder, C.; Brett, C. J.; Schwartzkopf, M.; Ulrich, N. M.; Toimil‐Molares, M. E.; Trautmann, C.; Söderberg, L. D.; Weindl, C. L.; Körstgens, V.; Müller‐Buschbaum, P.; Ma, M.; Roth, S. V. Biopolymer‐Templated Deposition of Ordered and Polymorph Titanium Dioxide Thin Films for Improved Surface‐Enhanced Raman Scattering Sensitivity. Adv. Funct. Mater. 2022, 32 (6), 2108556. https://doi.org/10.1002/adfm.202108556.

Rational Design and Synthesis of CO2 Reduction Reaction Catalysts of High Faradaic Efficiency Toward C2 + Chemical Conversions

Carbon dioxide emission from fossil fuel combustion poses a major threat to global environment and ecological systems.Carbon capture, sequestration and conversion technologies are widely pursued as possible solutions to mitigate negative impact by CO2. The electrochemical CO2 reduction reaction (CO2RR) to fuels and chemicals using renewable electricity offers attractive “carbon-neutral” and “carbon-negative” mitigation strategies. Various catalysts have been investigated as the electrocatalysts for CO2RR. Key challenges facing the current catalyst and electrolyzer designs include insufficient energy efficiency and low single product selectivity.CO2RR to C2+ chemicals represent a highly important area for CO2 reduction and utilization. For example, ethanol, ethylene, propanol, etc. are among the most produced chemicals by the industry and are widely used for various applications. Using CO2 as raw material for chemical production through electrocatalysis not only improves the carbon cycling, but also reduces the overall emissions from chemical production. While CO2RR via two proton-electron pairs (PEPs), such as the conversion of CO2 to CO or formate, have been proven high selective with fast kinetics, conversions to C2+ chemicals are significantly more difficult due to the rapid escalation of required PEPs to much higher numbers (for example, 12 for ethanol and 18 for propanol), in addition to C-C bond coupling. The increased PEPs substantially complicate the conversion by required multiple steps along the electrochemical coordinate, leading to a high probability of branching reactions and low single product Faradaic efficiency (FE).To address these challenges, the design criteria for CO2RR to C2+ chemicals should be based on high uniformity of active center for directing identical catalytic path and suppressing competing reactions, strong catalyst-reactant binding in capturing the transient species through multiple PEP transfers, and microenvironment with nanoconfinement for retaining reaction intermediates during extended catalytic processes.Recently, we developed a new amalgamated lithium metal (ALM) synthesis method of preparing highly selective and active CO2RR catalyst and achieved > 90% FE for conversion of CO2 to ethanol [1]. Our have since expanded the approach to other C2 + chemicals including acetate, acetone, glycerol, isopropanol, etc., all with FE at or higher than 80%. To better formulate our catalyst design strategy, we not only measured the CO2RR performance over a variety of electrocatalysts, but also investigated their activity-structure relationship through advanced material characterizations, combined with the first-principle computation. We found many interesting properties uniquely associated to CO2RR mechanism and kinetics, such as catalyst-size and electro-potential modulated single selectivity. In this presentation, we will share our recent discoveries and future perspective on the development of highly selective CO2RR catalysts for C2+ chemical conversions. Acknowledgement: This work is supported by U. S. Department of Energy, Office of Energy Efficiency and Renewable Energy - Industrial Efficiency & Decarbonization Office and by Office of Science, U.S. Department of Energy under Contract DE-AC02-06CH11357.[1] “Highly selective electrocatalytic CO2 reduction to ethanol by metallic clusters dynamically formed from atomically dispersed copper” Haiping Xu, Dominic Rebollar, Haiying He, Lina Chong, Yuzi Liu, Cong Liu, Cheng-Jun Sun, Tao Li, John V. Muntean, Randall E. Winans, Di-Jia Liu and Tao Xu, (2020) Nature Energy, 5, 623–632

Gas‐Phase Anion Photoelectron Spectroscopy of Alkanethiolate‐Protected PtAu12 Superatoms: Charging Energy in Vacuum vs Solution

AbstractThe charging behavior of molecular Au clusters protected by alkanethiolate (SCnH2n+1=SCn) is, under electrochemical conditions, significantly affected by the penetration of solvents and electrolytes into the SCn layer. In this study, we estimated the charging energy EC(n) associated with [PtAu24(SCn)18]−+e−→[PtAu24(SCn)18]2− (n=4, 8, 12, and 16) in vacuum using mass‐selected gas‐phase anion photoelectron spectroscopy of [PtAu24(SCn)18]z (z=−1 and −2). The EC(n) values of PtAu24(SCn)18 in vacuum are significantly larger than those in solution and decrease with n in contrast to the behavior reported for Au25(SCn)18 in solution. The effective relative permittivity (ϵm*) of the SCn layer in vacuum is estimated to be 2.3–2.0 based on the double‐concentric‐capacitor model. Much smaller ϵm* values in vacuum than those in solution are explained by the absence of solvent/electrolyte penetration into the monolayer. The gradual decrease of ϵm* with n is ascribed to the appearance of an exposed surface region due to the bundle formation of long alkyl chains.

Gas-Phase Anion Photoelectron Spectroscopy of Alkanethiolate-Protected PtAu12 Superatoms: Charging Energy in Vacuum vs Solution.

The charging behavior of molecular Au clusters protected by alkanethiolate (SCnH2n+1=SCn) is, under electrochemical conditions, significantly affected by the penetration of solvents and electrolytes into the SCn layer. In this study, we estimated the charging energy EC(n) associated with [PtAu24(SCn)18]-+e-→[PtAu24(SCn)18]2- (n=4, 8, 12, and 16) in vacuum using mass-selected gas-phase anion photoelectron spectroscopy of [PtAu24(SCn)18]z (z=-1 and -2). The EC(n) values of PtAu24(SCn)18 in vacuum are significantly larger than those in solution and decrease with n in contrast to the behavior reported for Au25(SCn)18 in solution. The effective relative permittivity (ϵm*) of the SCn layer in vacuum is estimated to be 2.3-2.0 based on the double-concentric-capacitor model. Much smaller ϵm* values in vacuum than those in solution are explained by the absence of solvent/electrolyte penetration into the monolayer. The gradual decrease of ϵm* with n is ascribed to the appearance of an exposed surface region due to the bundle formation of long alkyl chains.

Octocrylene carboxylate as an antenna in a luminescent Europium(III) complex: Experimental and theoretical insights

A new carboxylic acid, 2-cyano-3,3-diphenyl-2-propenoic acid, CLN, a chromophore ligand, was obtained by an alkaline hydrolysis reaction from the octocrylene, a commercial type B ultraviolet (UVB) radiation absorber. The CLN structure was elucidated by single-crystal X-ray diffraction (SCXRD) as being tetragonal with space group P4‾21/c and the presence of a carboxylic acid group was confirmed by mass, infrared (IR), and proton nuclear magnetic resonance (1H NMR) spectroscopy. In this way, coordination compounds were developed between CLN and Ln(III), Ln = being Gadolinium (Gd) and Europium (Eu), with a stoichiometry of 4:13 metal:ligand, confirmed by thermal and elemental analyses, corroborating with the metal cluster predicted by Sparkle/AM1 semi-empirical model. Photoluminescence data indicated that Eu(III) is efficiently sensitized by CLN due to its triplet excited state, determined using the emission spectrum of the Gd(III) mimic complex (T = 25,477 cm−1), being suitable for this purpose. Therefore, the emission spectrum of the Eu(III) complex exhibited a 5D0 → 7FJ transitions characteristic of the lanthanide ion. Furthermore, the Judd-Ofelt intensity parameters, the radiative and non-radiative decay rates, and the intrinsic quantum yield evaluated using the software LUMPAC software were in good agreement with the experimental values.

Revealing and reconstructing the 3D Li-ion transportation network for superionic poly(ethylene) oxide conductor.

Understanding the Li-ions conduction network and transport dynamics in polymer electrolyte is crucial for developing reliable all-solid-state batteries. In this work, advanced nano- X-ray computed tomography combined with Raman spectroscopy and solid state nuclear magnetic resonance are used to multi-scale qualitatively and quantitatively reveal ion conduction network of poly(ethylene) oxide (PEO)-based electrolyte (from atomic, nano to macroscopic level). With the clear mapping of the microstructural heterogeneities of the polymer segments, aluminium-oxo molecular clusters (AlOC) are used to reconstruct a high-efficient conducting network with high available Li-ions (76.7%) and continuous amorphous domains via the strong supramolecular interactions. Such superionic PEO conductor (PEO-LiTFSI-AlOC) exhibites a molten-like Li-ion conduction behaviour among the whole temperature range and delivers an ionic conductivity of 1.87 × 10-4 S cm-1 at 35 °Ϲ. This further endows Li electrochemical plating/stripping stability under 50 μA cm-2 and 50 μAh cm-2 over 2000 h. The as-built Li|PEO-LiTFSI-AlOC|LiFePO4 full batteries show a high rate performance and a capacity retention more than 90% over 200 cycling at 250 μA cm-2, even enabling a high-loading LiFePO4 cathode of 16.8 mg cm-2 with a specific capacity of 150 mAh g-1 at 50 °Ϲ.

Solvent effects on the structures of the hydrated copper dication clusters

Understanding the solvation process requires an understanding of how the solvent affects the molecular cluster configurations. The current study examined the impact of solvents on the structures of the hydrated Cu2+ cation, as well as the temperature dependence, and the energetics of the hydrated Cu2+ cation clusters from sizes n=1 from n=10 (Cu2+(H2O)n=1−10). The potential energy surfaces (PESs) in the solvent phase (represented by a dielectric continuum medium) at the MP2/6-31++G(d,p) level of computation have been comprehensively investigated. We employed the integral equation formalism polarized continuum model (IEF-PCM) to describe the dielectric continuum medium. It is pointed out that changes in PESs of hydrated copper dication isomers and structural morphologies occur in the continuum medium. Thus, the relative energies are smallest at T=0 K and for the cluster populations of Cu2+(H2O)n=1−10 are modified. Thus, in the solvent phase, the competition between the conformers is more severe than in the gas phase. Furthermore, highly coordinated conformers are more favorable, and favored conformers in the gas phase are disfavored in the solvent phase. The structural investigations are validated by the analysis of Wiberg Bond Index (WBI) at 300 K. In the solvent phase, the WBIs of the most stable isomers are the smallest and the WBIs of axial bonds are lower than those of equatorial bonds. Concerning the energy analysis, the binding energies were predicted for enormous sizes (at saturation) using a fit function. Thus, the new values of the binding energies obtained are -5467.8 and ▪ in the gas and solvent phases respectively. All these observed differences are due to the effects of the implicit solvent.

Metal-Organic Framework with Dual Excitation Pathways as Efficient Bifunctional Catalyst for Photo-assisted Li-O2 Batteries.

Li-O2 batteries (LOBs) have sparked significant interest due to their fascinating high theoretical energy density. However, the large overpotential for the formation and oxidation of Li2O2 during charge and discharge process seriously hinders the further development and application of LOBs. In this work, metal-organic frameworks (MOFs) with different metal clusters (Fe, Ti, Zr) are successfully synthesized, and they are employed as the photoelectrodes for the photo-assisted LOBs. The special dual excitation pathways of Fe-MOF under illumination and the superior separation efficiency of photocarriers, which significantly enhance the activation of O2/Li2O2, improving the catalytic activity of oxygen reduction reaction and oxygen evolution reaction. Moreover, compared to traditional inorganic semiconductor crystals, Fe-MOF exhibits large specific surface area and excellent O2 adsorption ability. Therefore, the LOB with Fe-MOF as the cathode exhibits large specific capacity, ultralow charge/discharge overpotential of 0.22V at 0.05mA cm-2 and excellent stability of 195 cycles under illumination. This study provides an environmentally friendly and highly efficient photocatalyst for LOBs, and a new strategy for designing photoelectrodes.