Dinuclear Research Articles

Mesoatomic Engineering for Programmable Spherical Packing Superlattices in Self-Assembly of Giant Molecular Clusters

Mesoatomic Engineering for Programmable Spherical Packing Superlattices in Self-Assembly of Giant Molecular Clusters

Solvent-Regulated Formation of Metal/Metal-Oxo Nodes in Two Indium Metal-Organic Frameworks: Syntheses, Structures, Selective Gas Adsorption and Fluorescence Sensor Properties.

Two water-stable indium metal-organic frameworks, (NH2Me2)3[In3(BTB)4] ⋅ 12DMA ⋅ 4.5H2O (In-MOF-1) and (NH2Me2)9[In9O6(BTB)8(H2O)4(DMSO)4] ⋅ 27DMSO ⋅ 21H2O (In-MOF-2) (BTB=4,4',4''-benzene-1,3,5-tribenzoate) with 3D interpenetrated structure has been constructed by regulating solvents. Structure analysis revealed that In-MOF-1 has a three-dimensional (3D) structure with a single metal core, while In-MOF-2 features an octahedron cage constructed by three kinds of metal clusters to further form a 3D structure. The fluorescence investigations showed that In-MOF-1 and In-MOF-2 are potential MOF-based fluorescent sensors to detect acetone and Fe3+ ions in EtOH or water with high sensitivity, excellent selectivity, recyclability and a low limit of detection. Moreover, the fluorescence mechanisms of In-MOF-1 and In-MOF-2 toward acetone and Fe3+ ions were further explained. In addition, In-MOF-2 has higher thermal and framework stability than In-MOF-1. The activated In-MOF-2 presents a high BET surface area of 998.82 m2g-1 and a pore size distribution of 8 to 16 Å. At the same time, In-MOF-2 exhibits high selective CO2 adsorption for CO2/CH4 and CO2/N2, respectively. Furthermore, the adsorption sites and adsorption isotherms were predicted using grand canonical Monte Carlo (GCMC) simulations, and the adsorption energy of the lowest-energy adsorption configuration was calculated using molecular dynamics (MD) simulations.

Borane-Mediated Polyhedral Expansion to Access Metal-Free Neutral and Cationic Derivatives of closo-Heptaboranes.

Boranes with closed polyhedral structures feature peculiar bonding and structural characteristics, rendering them widely applicable in diverse research areas ranging from basic functionalization reactions to applications such as medicine, nanomaterials, molecular electronics, and neutron capture therapy. Among the closed borane family, the neutral and cationic heptaborane B7 clusters have been missing in contemporary boron cluster chemistry to date. Herein, we report a polyhedral expansion protocol to construct a neutral derivative of closo-heptaborane (B7) from closo-hexaborane (B6) mediated by borane. Conversion of the neutral derivative of closo-heptaborane to a cationic derivative is also demonstrated. X-ray crystallographic and spectroscopic analyses with the aid of quantum chemical calculations reveal that both neutral and cationic derivatives of closo-heptaborane exhibit a pentagonal-bipyramidal geometry and involve the delocalized σ skeletal electrons, leading to three-dimensional aromaticity. Moreover, the B7 core of the former undergoes a complexation reaction with silver tetrafluoroborate, representing the first experimental demonstration of the nucleophilic nature of the closo-heptaborane.

Cuproptosis-related signature predicts prognosis and indicates tumor immune infiltration in bladder cancer.

Cuproptosis is a newly identified form of cell death that is dependent on copper (Cu) ions, termed Cu-dependent cytotoxicity. This process is distinct from other forms of cell death such as apoptosis, necrosis, and ferroptosis. The accumulation of copper is known to play a significant role in various biological processes, including angiogenesis (the formation of new blood vessels) and metastasis (the spread of cancer cells to different parts of the body). These processes are crucial for tumor growth and progression, indicating that copper and the cuproptosis-related genes (CPRGs) might be indispensable in the context of cancer development and progression. Given this background, we aimed to explore the relationship between CPRGs and both prognostic predictions and tumor microenvironment (TME) infiltration in bladder cancer (BLCA). For this study, we utilized data from The Cancer Genome Atlas (TCGA) to identify CPRGs and subsequently divided BLCA patients into three distinct molecular clusters based on these genes. To assess the proportions of various immune cell types within the TME, we employed single-sample gene set enrichment analysis (ssGSEA) and the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) method. These computational techniques allowed us to quantify the infiltration of different immune cells, providing insights into the immune landscape of the tumors. Furthermore, we developed a risk score model using CPRGs to predict the survival prospects of BLCA patients. Our analysis identified three molecular clusters of BLCA patients, each exhibiting unique clinical features and patterns of TME infiltration. Among these clusters, cluster 1 was associated with a poor prognosis. Interestingly, this cluster also showed significant infiltration of activated CD4+ (ssGSEA P<0.001) and CD8+ T (ssGSEA P<0.05) cells, which are crucial components of the immune response against tumors. This finding suggests a complex interaction between the immune system and the tumor, where a high presence of T cells does not necessarily correlate with better outcomes. Additionally, our risk score model revealed that the high-risk group, characterized by a specific expression pattern of CPRGs, also had enhanced infiltration of CD4+ and CD8+ T cells. This indicates that the cuproptosis-based risk model has a robust ability to predict patient prognosis and can guide immunotherapy decisions. Our study sheds light on the biological functions of CPRGs within the TME of BLCA and their correlations with clinical parameters and patient prognosis. The identification of distinct molecular clusters with varying prognoses and immune cell infiltrations highlights the heterogeneity of BLCA and underscores the potential of CPRGs as biomarkers for prognosis and therapeutic targets. These findings offer new perspectives for the development of immunotherapeutic strategies in the treatment of BLCA patients, potentially leading to more personalized and effective cancer therapies.

Characterizing the surface compositions of supported bimetallic PtSn clusters: Effects of cluster-support interactions and surface adsorbates

PtSn bimetallic clusters on TiO2(110) and highly oriented pyrolytic graphite (HOPG) surfaces have been characterized by scanning tunneling microscopy, low energy ion scattering (LEIS), X-ray photoelectron spectroscopy, and temperature programmed desorption (TPD); density functional theory (DFT) calculations have also been performed to better understand adsorption of CO and D2 on the PtSn surfaces. On TiO2 at coverages of 2 ML of Pt and 2 ML of Sn, exclusively bimetallic clusters are formed for both orders of deposition because clusters of the first metal completely cover the surface such that all atoms of the second metal are incorporated into the existing clusters. In contrast, on HOPG, the high mobility and weak cluster-support interactions on HOPG result in much larger 2 ML monometallic clusters (∼30 Å high) that do not completely cover the surface, and deposition of the second metal produces larger clusters as well as smaller ones. Despite the difference in cluster morphologies for the different orders of deposition and supports, the LEIS experiments demonstrate that in all cases, the PtSn clusters are rich in Sn at the surface, as expected based on the lower surface free energy for Sn compared to Pt. Furthermore, the +0.2 eV shift in the Sn(3d5/2) binding energy observed on all surfaces in the presence of Pt is consistent with PtSn alloy formation. Deposition of 2 ML of Sn on TiO2 produces two-dimensional clusters with oxidation of Sn and reduction of titania at the cluster-support interface, but addition of Pt to the Sn clusters causes Sn to diffuse away from this interface, leaving Sn in the metallic state. TPD experiments on 2 ML Pt/TiO2 with increasing coverages of Sn show that the number of adsorption sites for D2 sharply decreases to nearly zero at 0.5 ML, while CO adsorption decreases to zero only at much higher Sn coverages of 2 ML. DFT studies for Sn modified Pt surfaces and bulk structures demonstrate that for CO adsorption at low Sn coverages (≤0.25 ML), the strong Pt-CO interactions induce diffusion of Pt to the cluster surface and the formation of a bulk Pt3Sn alloy, whereas D2 adsorption does not lead to interactions with the Pt surface that are strong enough to induce alloy formation. A single Sn adatom prevents D2 adsorption on four neighboring Pt atoms via site-blocking and the donation of electron density to Pt.

Theoretical investigation of graphdiyne-supported single-cluster catalysts for electroreduction of nitric oxide

The electrochemical NO reduction reaction (NORR) to NH3 offers an efficient, environmentally friendly strategy for NO removal and NH3 production, but developing effective catalysts to facilitate the conversion of NO into NH3 remains a challenge. Single-cluster catalysts (SCCs) with multi-metallic sites show promise due to the synergistic interactions among the active atoms. Herein, utilizing density functional theory (DFT) and grand-canonical DFT (GC-DFT), we systematically investigated the potential of late transition metal (TM = Fe, Co, Ni, Cu, Ru, Rh, Pd, Pt) clusters on graphdiyne (TMx/GDY, x = 1–5) for NORR. Ni3/GDY, Pd3/GDY, and Pt3/GDY emerged as the most promising candidates, demonstrating stability, excellent NORR activity, and HER suppression. Their outstanding performance is attributed to the moderate adsorption of NO, with the dxz/dyz orbitals playing a key role in NO activation. GC-DFT results highlight nonlinear variation of intermediate grand free energies with the applied potential. Detailed electronic property analyses were conducted to reveal the charge effects induced by the applied chemical potential. This study provides valuable insights into SCC-catalyzed NO reduction and highlights the significance of potential effects in theoretical simulations of electrochemical systems.

The role of irradiation-enhanced interstitial diffusion in over-pressurizing fission gas bubbles in UO2

Fission gas bubbles in UO2 nuclear fuel have been observed to exhibit pressures in excess of the equilibrium bubble pressure; however, the cause of bubble over-pressurization has not yet been demonstrated. The mechanical interaction between a bubble and the surrounding matrix or grain boundary depends on the internal pressure of the bubble and local stress state, such that over-pressurized bubbles are thought to be responsible for fragmentation and pulverization, when exposed to a temperature ramp. Here, we investigate the role of U interstitials, produced through irradiation, in over-pressurizing bubbles by using a combined molecular dynamics (MD) and cluster dynamics approach. Firstly, the energies for the capture of interstitials and vacancies by bubbles have been determined from MD as a function of the ratio of gas atoms to vacancies that make up the bubble. Secondly, these reaction energies have been implemented in the cluster dynamics code Centipede to predict bubble over-pressurization as a function of temperature for typical fission rates. It was found that there is a transition from low pressure bubbles (at high temperatures) to high pressure bubbles (at lower temperatures). The cause of this behavior was shown to be the creation of irradiation-induced interstitials that are highly mobile relative to vacancies at low temperature; whereas, vacancies are sufficiently mobile at high temperatures to limit bubble pressures. This result supports the hypothesis that over-pressurized bubbles form during steady-state operation and that this behavior is highly sensitive to the local pellet temperature.

The dibenzoterrylene-C60 composite structure as a possible new single-photon source - growth and optical analysis

Abstract A sample fabrication approach based on organic molecular beam deposition creating a new molecule-based emitter structure and its optical analysis is presented. The polycyclic aromatic hydrocarbon dibenzoterrylene (DBT, C38H20) was deposited between layers of C60-fullerenes, which serve as a protective matrix. It was found that this structure maintains the DBT’s optical properties [1, 2], but a potentially quenching impact cannot be excluded. Raman spectra of the composite were collected proving the molecules’ preserved integrity after being evaporated at high temperatures. Finally, the results of confocal laser scanning microscopy show fluorescent molecular clusters.

Fluxional halogen bonds in linear complexes of tetrafluorodiiodobenzene with dinitrobenzene.

The fluxional nature of halogen bonds (XBs) in small molecular clusters, supramolecules, and molecular crystals has received considerable attention in recent years. In this work, based on extensive density-functional theory calculations and detailed electrostatic potential (ESP), natural bonding orbital (NBO), non-covalent interactions-reduced density gradient (NCI-RDG), and quantum theory of atoms in molecules (QTAIM) analyses, we unveil the existence of fluxional halogen bonds (FXBs) in a series of linear (IC6F4I)m(OONC6H4NOO)n (m + n = 2-5) complexes of tetrafluorodiiodobenzene with dinitrobenzene which appear to be similar to the previously reported fluxional hydrogen bonds (FHBs) in small water clusters (H2O)n (n = 2-6). The obtained fluxional mechanisms involve one FXB in the systems which fluctuates reversibly between two linear CI···O XBs in the ground states (GS and GS') via a bifurcated CI O2N van der Waals interaction in the transition state (TS). The cohesive energies (Ecoh) of these complexes with up to four XBs exhibit an almost perfect linear relationship with the numbers of XBs in the systems, with the average calculated halogen bond energy of Ecoh/XB = 3.48 kcal·mol-1 in the ground states which appears to be about 55% of the average calculated hydrogen bond energy (Ecoh/HB = 6.28 kcal·mol-1) in small water clusters.

Isolation of the Secondary Building Unit of a 3D Metal-Organic Framework through Clip-Off Chemistry, and Its Reuse To Synthesize New Frameworks by Dynamic Covalent Chemistry.

Herein, we present a novel methodology for synthesizing metal clusters or secondary building units (SBUs) that are subsequently employed to construct innovative metal-organic frameworks (MOFs) via dynamic covalent chemistry. Our approach entails extraction of SBUs from preformed MOFs through complete disassembly by clip-off chemistry. The initial MOF precursor is designed to incorporate the desired SBU, connected exclusively by cleavable linkers (in this study, with olefinic bonds). Cleavage of all the organic linkers (in this study, via ozonolysis under reductive conditions) liberates the SBUs functionalized with aldehyde groups. Once synthesized, these SBUs can be further reacted with amines in dynamic covalent chemistry to build new, rationally designed MOFs.

Research on the microscale effects of fuel pellets carrying chemical pesticide distillation residues

To effectively deal with organic hazardous wastes generated in the production processes of chemical pesticide industries. In this study, the strong shear force generated by high-speed rotating blades was utilized to fully mix and stir pasty or viscous liquid organic hazardous wastes with porous solid fuels. The wastes were broken down into small molecular clusters and evenly distributed on the surfaces of the pores of porous solid fuel particles. This study then investigated the thermal characteristics of fuel particles carrying the distillation residues of chemical pesticides under microscale effects, the volatilization and destruction removal characteristics, the formation of pollutants, and the migration and transformation of F and Cl elements. The results showed that when the average diameter of the fuel particles was 6 mm and the mass ratio of the chemical pesticide distillation residue to the fuel particles was 2:3, small molecular clusters of the residue were evenly distributed on the surfaces of the fuel particles, with a dispersity of 67 %. The volatilization rate of the irritating odors in the coated particles was less than 2 %. With an increase in the proportion of the chemical pesticide distillation residue, the ignition temperature of the particles decreased, the thermal stability increased, the burnout temperature rose, and the maximum weight loss rate first increased and then decreased. The Ca and alkali metal oxides in the fuel particles had a significant effect on fixing chlorine and fluorine.

Unlocking high photosensitivity direct laser writing and observing atomic clustering in glass

The direct laser writing (DLW) of photoluminescent metal clusters is inspiring intensive research in functional glasses. However, understanding the influence of the host structure on cluster formation and visualizing DLW-induced clusters at the atomic scale remains challenging. In this work, we develop a highly photosensitive fluorophosphate glass through fluorine incorporation. The addition of fluorine establishes a conducive environment for Ag+ ions before DLW and enhances the availability of reducing agents and diffusion pathways during DLW. These advantages facilitate the formation of Ag clusters under low-energy single-pulsed DLW. Increasing laser energy results in a combination of Ag clusters and glasses defect, forming a dot + ring photoluminescent pattern. Atom probe tomography (APT), a technique capable of mapping the elemental spatial distribution and identifying clustering, is employed to gain more information on laser-induced clusters. Comparison of APT results between samples without and with DLW reveals the formation of Ag clusters after laser writing. The design concept and characterization enrich the understanding of Ag cluster behavior in glasses. This knowledge opens the possibility of rational design of clusters confined in glasses and inspires their synthesis for various applications.

Massive Assessment of the Geometries of Atmospheric Molecular Clusters.

Atmospheric molecular clusters are important for the formation of new aerosol particles in the air. However, current experimental techniques are not able to yield direct insight into the cluster geometries. This implies that to date there is limited information about how accurately the applied computational methods depict the cluster structures. Here we massively benchmark the molecular geometries of atmospheric molecular clusters. We initially assessed how well different DF-MP2 approaches reproduce the geometries of 45 dimer clusters obtained at a high DF-CCSD(T)-F12b/cc-pVDZ-F12 level of theory. Based on the results, we find that the DF-MP2/aug-cc-pVQZ level of theory best resembles the DF-CCSD(T)-F12b/cc-pVDZ-F12 reference level. We subsequently optimized 1283 acid-base cluster structures (up to tetramers) at the DF-MP2/aug-cc-pVQZ level of theory and assessed how more approximate methods reproduce the geometries. Out of the tested semiempirical methods, we find that the newly parametrized atmospheric molecular cluster extended tight binding method (AMC-xTB) is most reliable for locating the correct lowest energy configuration and yields the lowest root mean square deviation (RMSD) compared to the reference level. In addition, we find that the DFT-3c methods show similar performance as the usually employed ωB97X-D/6-31++G(d,p) level of theory at a potentially reduced computational cost. This suggests that these methods could prove to be valuable for large-scale screening of cluster structures in the future.

Comprehensive analysis of multiple regulated cell death risk signatures in lung adenocarcinoma

BackgroundRegulated cell death (RCD) has considerable impact on tumor progress and sensitivity of treatment. Lung adenocarcinoma (LUAD) show a high resistance for conventional radiotherapies and chemotherapies. Currently, regulation of cancer cell death has been emerging as a new promising therapeutic avenue for LUAD patients. However, the crosstalk in each pattern RCD is unclear. MethodsWe integrated collected the hub-genes of 12 RCD subroutines and compressively analyzed these hub-genes synergistic effect in LUAD. The characters of RCD genes expression and prognosis were developed in The Cancer Genome Atlas (TCGA)-LUAD data. We developed and validated an RCD risk model based on TCGA and GSE70294 data set, respectively. Functional annotation and tumor immunotherapy based on the risk model were also investigated. Results28 RCD-related genes and two LUAD molecular cluster were identified. Survival analysis revealed that the prognosis in high-risk group was worser than those in low-risk group. Functional enrichment analysis indicated that the RCD risk model correlated with immune responses. Further analysis indicated that the high-risk group in RCD risk model exhibited an immunosuppressive microenvironment and a lowly immunotherapy responder ratio. ConclusionsWe present an RCD risk model which have a promising ability in predicting LUAD prognosis and immunotherapy response.

Metal clusters modified hexagonal boron nitride for adsorption and sensing of lithium batteries thermal runaway gases

Developing efficient gas sensing materials for monitoring lithium batteries thermal runaway gases is essential for human safety. In this study, a detailed examination of the CH4, CO2, CO, and H2 adsorption property for the h-BN with metal clusters modification was conducted utilizing density functional theory. The incorporation of metal clusters (Pd4, Rh4, and Ru4) significantly improved the adsorption energy and charge transfer of h-BN towards gases compared to the unmodified h-BN. The Ru4/h-BN system demonstrated the highest adsorption capacity across all four gases, while the Pd4/h-BN system displayed remarkable recovery ability at room temperature (298 K). Furthermore, studying the adsorption mechanism via DOS revealed enhanced gas adsorption due to orbital hybridization. The work offers reliable theoretical foundation for the detection and prevention of thermal runaway gases in lithium batteries through the use of h-BN modified with metal clusters.

Fully Exposed Ru Clusters for the Efficient Multi-Step Toluene Hydrogenation Reaction.

Liquid organic hydrogen carriers (LOHCs) are attractive platform molecules that play an important role in hydrogen energy storage and utilization. The multi-step hydrogenation of toluene (TOL) to methylcyclohexane (MCH) has been widely studied in the LOCHs systems, due to their relatively low toxicity and reasonable hydrogen storage capacity. Noble metal catalysts such as Ru has exhibited good performance in multi-step hydrogenation reactions, while the application is still hindered by their high cost and low specific activity. Therefore, the primary challenge lies in the development of noble metal catalysts with both robust activity and efficient atomic utilization. In this study, a series of Ru species ranging from single atoms, fully exposed clusters to nanoparticles were fabricated to investigate their structural evolution in the TOL multi-step hydrogenation reaction. The fully exposed and atomically dispersed Ru clusters, composed of an average of 3 Ru atoms, exhibit superior catalytic performance and recycle ability in TOL multi-step hydrogenation. Moreover, it delivers a high turnover frequency of 9850.3 h-1 under the relatively mild reaction (100 °C, 1.5 MPa), compared with those of single atoms and nanoparticles, and shows a notable advantage over catalysts reported in previous studies. From density functional theory (DFT) calculations, the overall barrier of the TOL multi-step hydrogenation reaction over the fully exposed Ru clusters is significantly lower than that of single atoms and nanoparticles, resulting in its higher activity. The present work provides an efficient strategy to regulate the reaction pathway of multi-step complicated catalytic reactions by designing fully exposed metal cluster catalysts.

Nanozymes in Biomedical Applications: Innovations Originated From Metal-Organic Frameworks.

Nanozymes exhibit significant potential in medical theranostics, environmental protection, energy development, and biopharmaceuticals due to their exceptional catalytic performance. Compared with natural enzymes, nanozymes have the advantages of simple preparation and purification, convenient production and low cost. Therefore, it is very important to prepare nanozymes quickly and efficiently, which not only helps to expand their application scope, but also can further exert their great potential in various fields. Metal-organic frameworks (MOF) materials serve as versatile substrates for constructing nanozymes, offering unique advantages like adjustable structure, high specific surface area, and porous channels. MOF coordination nodes constructed from metal ions or metal clusters have unique properties that can be leveraged to tailor nanozyme characteristics for different applications. This review describes and analyzes recent methods for constructing nanozymes using MOF materials, and explores their application prospects in biomedicine. By expounding the preparation techniques and biomedical applications of nanozymes, this review aims to inspire researchers to develop innovative nanozyme materials and explore new application directions.

EPR spectroscopy: A versatile tool for exploring transition metal complexes in organometallic and bioinorganic chemistry

AbstractParamagnetic molecules, such as main‐group radicals and transition metal complexes, play crucial roles in catalytic and enzymatic reactions in organometallic and bioinorganic chemistry. Electron paramagnetic resonance (EPR) spectroscopy emerges as a powerful tool for probing the intricate electronic and geometric structures of these molecules. The application of EPR spectroscopy spans a wide spectrum of chemical entities, from simple radicals to transition metal complexes, metalloproteins, and metal clusters, emphasizing its versatility across various fields of chemistry. This review introduces the EPR spectra of transition metal complexes, offering a comprehensive theoretical foundation along with illustrative examples from both bioinorganic and organometallic chemistry. These examples highlight the effectiveness of EPR spectroscopy in characterizing transition metal complexes, reinforcing our understanding of their structure and reactivity.

Light-Induced Metallic and Paramagnetic Defects in Halide Perovskites from Magnetic Resonance.

Halide perovskites are promising next-generation solar cell materials, but their commercialization is hampered by their propensity to degrade under operating conditions, particularly under heat, humidity, and light. Identifying degradation products and linking them to the degradation mechanism at the atomic scale is necessary to design more stable perovskite materials. Here we use magnetic resonance methods to identify and characterize the formation of both metallic lead clusters and Pb3+ defects upon light-induced degradation of methylammonium lead halide perovskite using nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) measurements. Paramagnetic relaxation enhancement (PRE) of the 1H NMR resonances demonstrates the presence of localized paramagnetic Pb3+ defects, a large Knight shift of the 207Pb NMR proves the presence of lead metal, and their relative proportions are determined by the differing temperature dependence in variable-temperature EPR. This work reconciles previous conflicting literature results, enabling the use of EPR spectroscopy to monitor photodegradation of perovskite devices.

A semi-automated quantum-mechanical workflow for the generation of molecular monolayers and aggregates.

Organic electronics (OE) such as organic light-emitting diodes or organic solar cells represent an important and innovative research area to achieve global goals like environmentally friendly energy production. To accelerate OE material discovery, various computational methods are employed. For the initial generation of structures, a molecular cluster approach is employed. Here, we present a semi-automated workflow for the generation of monolayers and aggregates using the GFNn-xTB methods and composite density functional theory (DFT-3c). Furthermore, we present the novel D11A8MERO dye interaction energy benchmark with high-level coupled cluster reference interaction energies for the assessment of efficient quantum chemical and force-field methods. GFN2-xTB performs similar to low-cost DFT, reaching DFT/mGGA accuracy at two orders of magnitude lower computational cost. As an example application, we investigate the influence of the dye aggregate size on the optical and electrical properties and show that at least four molecules in a cluster model are needed for a qualitatively reasonable description.