Number Of Metal Atoms Research Articles

Molecular Interactions in Atomically Precise Metal Nanoclusters.

For nanochemistry, precise manipulation of nanoscale structures and the accompanying chemical properties at atomic precision is one of the greatest challenges today. The scientific community strives to develop and design customized nanomaterials, while molecular interactions often serve as key tools or probes for this atomically precise undertaking. In this Perspective, metal nanoclusters, especially gold nanoclusters, serve as a good platform for understanding such nanoscale interactions. These nanoclusters often have a core size of about 2 nm, a defined number of core metal atoms, and protecting ligands with known crystal structure. The atomically precise structure of metal nanoclusters allows us to discuss how the molecular interactions facilitate the systematic modification and functionalization of nanoclusters from their inner core, through the ligand shell, to the external assembly. Interestingly, the atomic packing structure of the nanocluster core can be affected by forces on the surface. After discussing the core structure, we examine various atomic-level strategies to enhance their photoluminescent quantum yield and improve nanoclusters' catalytic performance. Beyond the single cluster level, various attractive or repulsive molecular interactions have been employed to engineer the self-assembly behavior and thus packing morphology of metal nanoclusters. The methodological and fundamental insights systemized in this review should be useful for customizing the cluster structure and assembly patterns at the atomic level.

Single Particle Analysis-Enhanced DNA Walking Machine for Sensitive miRNA Detection.

DNA walking machines have achieved significant breakthroughs in areas such as biosensing, bioimaging, and early cancer diagnosis, facilitated by the self-assembly of DNA or its combination with other materials, such as magnetic beads and metal nanoparticles. However, current DNA walking machine strategies are constantly challenged by inadequate analytical sensitivity, while sophisticated signal amplification procedures are often indispensable. Single-particle inductively coupled plasma mass spectrometry (SP-ICPMS) provides superior sensitivity and can effectively discriminate between background noise and detected signals due to the large number of metal atoms in a nanoparticle and the concentrating effect of single nanoparticle detection. In this study, we present a novel approach utilizing single nanoparticle counting and duplex-specific nuclease (DSN)-assisted signal amplification to construct a 3D DNA walking machine for detecting the aggressive prostate cancer (PCa) biomarker miRNA-200c. The proposed strategy showed an improvement in sensitivity with a detection limit (LOD) of 0.93 pM (28 amol) and was successfully applied in human serum samples. To the best of our knowledge, this is the first report of the DNA walking machine with single nanoparticle counting study.

Theoretical Study of Catalytic Performance of Pristine M2C and Oxygen-Functionalized M2CO2 MXenes as Cathodes for Li-N2 Batteries.

Li-N2 batteries are a promising platform for electrochemical energy storage, but their performance is limited by the low activity of the cathode catalysts. In this work, density functional theory was used to study the catalytic activity of the pristine M2C and oxygen-functionalized M2CO2 MXenes (M = Sc, Ti, and V) as cathodes for Li-N2 batteries. The calculated results suggest that the pristine M2C MXenes (M = Sc, Ti, and V) show high electrical conductivity due to the Fermi level crossing the metal 3d states. The stable adsorption of N2 occurs on M2C MXenes via a side-on model and strengthens gradually with decreasing metal atomic number. Furthermore, the kinetics of N2 dissociation can be significantly accelerated by the coadsorption of Li on M2C MXenes. However, adsorption and dissociation of N2 on the M2CO2 surfaces are too difficult to occur due to strong electrostatic repulsion. The Li-mediated nitrogen reduction reaction during discharge proceeds favorably via (N + N)* → (LiN + N)* → (LiN + LiN)* → (Li2N + LiN)* → (Li2N + Li2N)* → (Li3N + Li2N)* → (Li3N + Li3N)* to form two isolated Li3N* on M2C MXenes. The calculated charge-discharge overpotentials decrease in the order of Sc2C < Ti2C < V2C. Notably, the Sc2C MXene has great potential as a cathode catalyst for Li-N2 batteries because of its high electrical conductivity, strong N2 adsorption, favorable Li-mediated N2 dissociation, and ultralow discharging, charging, and total overpotentials (0.07, 0.06, and 0.13 V). This study offers a theoretical foundation for future research on Li-N2 batteries.

Assessing the matrix effects on MALDI-MS in the positive and negative ion mode detection for protein-protected metal nanoclusters

Protein-protected metal nanoclusters (MNCs) represent a new class of highly photoluminescent nanomaterials that have wide applications. Suitable reaction conditions combining protein and metal precursors can produce a vast range of different NC sizes (i.e. different number of metal atoms). The average number of metal atoms per protein can be determined by mass spectrometry (MS). MS coupled with matrix-assisted laser desorption ionization (MALDI) presents a number of advantages such as detection with high sensitivity of nanoclusters with high molecular weights. Although many protein-protected MNCs have been characterized by MALDI-MS, a large dispersion in the number of metal atoms has been reported mainly due to sample preparation. In this work, we optimized the protocols for negative and positive ion detection mode as a general MALDI-MS sample preparation method for protein-protected MNCs (bovine serum albumin and lysozyme and with gold and silver). Negative and positive ion mode detection was compared, showing that negative ion mode detection in MALDI-MS can also be used with acidic matrices. Obvious matrix effects on ion signals and peak positions by MALDI-MS were observed. The average metal numbers of MNCs embedded in proteins are different depending on the MALDI matrix. The matrix effects give a warning for more serious consideration on MALDI-MS measurement and spectra analysis of MNCs.

Structure Effects of Ligands in Gold-Ligand Complexes for Controlled Formation of Gold Nanoclusters.

Metal nanoclusters (NCs) are a special class of nanoparticles composed of a precise number of metal atoms and ligands. Because the proportion of ligands to metal atoms is high in metal NCs, the ligand type determines the physical properties of metal NCs. Furthermore, ligands presumably govern the entire formation process of the metal NCs. However, their roles in the synthesis, especially as factors in the uniformity of metal NCs, are not understood. It is because the synthetic procedure of metal NCs is highly convoluted. The synthesis is initiated by the formation of various metal-ligand complexes, which have different numbers of atoms and ligands, resulting in different coordinations of metal. Moreover, these complexes, as actual precursors to metal NCs, undergo sequential transformations into a series of intermediate NCs before the formation of the desired NCs. Thus, to resolve the complicated synthesis of metal NCs and achieve their uniformity, it is important to investigate the reactivity of the complexes. Herein, we utilize a combination of mass spectrometry, density functional theory, and electrochemical measurements to understand the ligand effects on the reactivity of AuI-thiolate complexes toward the reductive formation of Au NCs. We discover that the stability of the complexes can be increased by either van der Waals interactions induced by the long carbon chain of ligands or by non-thiol functional groups in the ligands, which additionally coordinate with AuI in the complexes. Such structural effects of thiol ligands determine the reduction reactivity of the complexes and the amount of NaBH4 required for the controlled synthesis of the Au NCs.

Analyzing Stabilities of Metal-Organic Frameworks: Correlation of Stability with Node Coordination to Linkers and Degree of Node Metal Hydrolysis.

Among the important properties of metal-organic frameworks (MOFs) is stability, which may limit applications, for example, in separations and catalysis. Many MOFs consist of metal oxo cluster nodes connected by carboxylate linkers. Addressing MOF stability, we highlight connections between metal oxo cluster chemistry and MOF node chemistry, including results characterizing Keggin ions and biological clusters. MOF syntheses yield diverse metal oxo cluster node structures, with varying numbers of metal atoms (3-13) and the tendency to form chains. MOF stabilities reflect a balance between the number of node-linker connections and the degree of node hydrolysis. We summarize literature results showing how MOF stability (the temperature of decomposition in air) depends on the degree of hydrolysis/condensation of the node metals, which is correlated to their degree of substitution with linkers. We suggest that this correlation may help guide the discovery of stable new MOFs, and we foresee opportunities for progress in MOF chemistry emerging from progress in metal oxo cluster chemistry.

Prediction of a new 2D Janus monolayer MX2Si2Y2 (M = Mo, W and V; X/Y = N, P; X ≠ Y) from density functional theory

We devised the Janus monolayer MX2A2Y2 (M = Mo, W, V, Nb, Ta, Ti, Zr, Hf and Cr; X/Y = N, P and As; A = Si and Ge) and systematically investigated the structural parameters, phonon vibrations, thermal stability, the electronic and mechanical properties. Among the 26 systems, there are six stable Janus monolayers at room temperature: MoN2Si2P2, WN2Si2P2, VN2Si2P2, MoP2Si2N2, WP2Si2N2, CrN2Si2P2. Intriguingly, the MoP2Si2N2 and WP2Si2N2 show non-magnetic semiconductor properties. The MoN2Si2P2 and WN2Si2P2 demonstrate non-magnetic metallic ground states. The VN2Si2P2 and CrN2Si2P2 are magnetic metal with magnetic moments of 1.24 μB and 0.53 μB. Furthermore, the elastic constants of the MSi2N4 and five Janus monolayer MX2Si2Y2 (M = Mo, W and V; X/Y = N, P) meet the stability criteria, indicating they are mechanically stable. The in-plane stiffness of the MX2Si2Y2 increases with the increase of the number of metal atoms and are greatly reduced, compared with the corresponding MSi2N4. In addition, according to Poisson's ratio, the MN2Si2P2 with metallic characteristics are ductile, whereas the MP2Si2N2 with semiconductor characteristic are brittle. In short, the Janus monolayer MX2Si2Y2 enriches the family members of 2D materials. The rich electronic and mechanical properties make the MX2Si2Y2 have high application prospects for future novel mechanical electronic device applications.

Magnetism and electronic properties of ConMoP (n = 1 ~ 5) cluster: a DFT study.

Hydrogen has emerged as a promising clean energy carrier, underscoring the imperative need to comprehend its adsorption mechanisms. This study delves into the magnetic and electronic properties of Co-Mo-P clusters, aiming to unveil their catalytic potential in hydrogen production. Employing density functional theory (DFT), we optimized cluster configurations and scrutinized their magnetic behaviors. Our investigation unveiled 16 stable configurations of the ConMoP (n = 1 ~ 5) cluster, predominantly in steric forms. The magnetic attributes were primarily ascribed to the d orbitals of Co metal atoms, with Co3MoP exhibiting exceptional magnetic characteristics. Analysis of density of state diagrams revealed the prevalence of spin-up α-electrons in d orbitals, while spin-down β-electrons attenuated overall magnetic properties. Localized orbital (LOL) analysis highlighted stable covalent bonds within the clusters, affirming their catalytic potential. Orbital delocalization index (ODI) analysis revealed diverse spatial distribution ranges for orbitals across different configurations, suggesting a progressive attenuation of off-domain properties with increasing cluster size. Furthermore, infrared spectroscopy unveiled distinct vibrational peaks in various configurations, indicative of unique infrared activities. These findings contribute to a nuanced theoretical understanding of Co-Mo-P clusters and pave the path for future research aimed at augmenting their catalytic efficiency in hydrogen production. This study underscores the viability of Co-Mo-P clusters as alternatives to conventional Pt catalysts, offering insights into the design of novel materials for sustainable energy applications. Further research is warranted to explore the behavior of the Co-Mo-P system under diverse reaction conditions, fostering advancements in materials and energy science. In this study, we harnessed the ConMoP (n = 1 ~ 5) cluster as a simulation platform for probing the local structure of the material. Our aim was to scrutinize the magnetism, electronic characteristics influenced by the varying metal atoms within these clusters. A systematic exploration involved incrementing the number of metal atoms and expanding the cluster size to elucidate the corresponding property variations. Density functional theory (DFT) calculations were pivotal to our methodology, employing the B3LYP hybrid functional implemented in the Gaussian16 software package. The ConMoP (n = 1 ~ 5) cluster underwent optimization calculations and vibrational analysis at the def2-tzvp quantization level, yielding optimized configurations with diverse spin multiplet degrees. To comprehensively characterize and visually represent the stability, electronic features, and catalytic attributes of these configurations, we employed a suite of computational tools. Specifically, quantum chemistry software GaussView and wave function analysis software Multiwfn played integral roles. Through the integrated use of these computational tools, we acquired valuable insights into the magnetism, electronic characteristics of the ConMoP (n = 1 ~ 5) cluster, shedding light on their dependency on distinct metal atoms.

A Metal Coordination Number Determined Catalytic Performance in Manganese Borides for Ambient Electrolysis of Nitrogen to Ammonia.

A new strategy that can effectively increase the nitrogen reduction reaction performance of catalysts is proposed and verified by tuning the coordination number of metal atoms. It is found that the intrinsic activity of Mn atoms in the manganese borides (MnBx) increases in tandem with their coordination number with B atoms. Electron-deficient boron atoms are capable of accepting electrons from Mn atoms, which enhances the adsorption of N2 on the Mn catalytic sites (*) and the hydrogenation of N2 to form *NNH intermediates. Furthermore, the increase in coordination number reduces the charge density of Mn atoms at the Fermi level, which facilitates the desorption of ammonia from the catalyst surface. Notably, the MnB4 compound with a Mn coordination number of up to 12 exhibits a high ammonia yield rate (74.9 ± 2.1µg h-1 mgcat -1) and Faradaic efficiency (38.5 ± 2.7%) at -0.3V versus reversible hydrogen electrode (RHE) in a 0.1 m Li2SO4 electrolyte, exceeding those reported for other boron-related catalysts.

How spin state and oxidation number of transition metal atoms determine molecular adsorption: a first-principles case study for NH3.

Understanding how the electronic state of transition metal atoms can influence molecular adsorption on a substrate is of great importance for many applications. Choosing NH3 as a model molecule, its adsorption behavior on defected SnS2 monolayers is investigated. The number of valence electrons n is controlled by decorating the monolayer with different transition metal atoms, ranging from Sc to Zn. Density-Functional Theory based calculations show that the adsorption energy of NH3 molecules oscillates with n and shows a clear odd-even pattern. There is also a mirror symmetry of the adsorption energies for large and low electron numbers. This unique behavior is mainly governed by the oxidation state of the TM ions. We trace back the observed trends of the adsorption energy to the orbital symmetries and ligand effects which affect the interaction between the 3σ orbitals (NH3) and the 3d orbitals of the transition metals. This result unravels the role which the spin state of TM ions plays in different crystal fields for the adsorption behavior of molecules. This new understanding of the role of the electronic structure on molecular adsorption can be useful for the design of high efficiency nanodevices in areas such as sensing and photocatalysis.

Graphitic carbon nitride supported Ni-Co dual-atom catalysts beyond Ni1(Co1) single-atom catalysts for hydrogen production: a density functional theory study.

Using density functional theory calculations we investigate the formation, structure and electronic properties of gh-C3N4-supported Ni-Co (Ni-Co/gh-C3N4) dual-atom catalysts and Ni1(Co1) single-metal catalysts, as a paradigmatic example of single-atom versus few-atom catalysts. An inverted mold assumption is proposed to identify the factors determining the number, shape and packing manner of metal atoms inside the pores of gh-C3N4. The area matching between virtual fragments and metal fillers and lattice inheritance from N coordination and metal aggregates allow for a stable Ni-Co/gh-C3N4, which would possess more active sites and a more complex structure-activity relation than single-atom doping. The hydrogen production behavior and catalytic activity of this catalyst are comprehensively discussed. Ni-Co/gh-C3N4 exhibits higher hydrogen evolution activity than Ni1(Co1)/gh-C3N4 at an appropriate H coverage, which is comparable to Pt under analogous conditions. This strategy, derived from the inverted mold assumption, is deemed to be a simple and easy-to-operate method for designing and building metal aggregates confined inside the pores of two-dimensional materials and in the cavities of nanoparticles for few-atom catalysts.

Copper nanoclusters: emerging photoredox catalysts for organic bond formations.

Advancements in fine chemical synthesis and drug discovery continuously demand the development of new and more efficient catalytic systems. In this regard, numerous transition metal-based catalysts have been developed and successfully applied in industrial processes. However, the need for innovative catalyst systems to further enhance the efficiency of chemical transformations and industrial applications persists. Metal nanoclusters (NCs) represent a distinct class of ultra-small nanoparticles (<3 nm) characterized by a precise number of metal atoms coordinated with a defined number of ligands. This structure confers abundant unsaturated active sites and unique electronic and optical properties, setting them apart from conventional nanoparticles or bulk metals. The well-defined structure and monodisperse nature of NCs make them particularly attractive for catalytic applications. Among these, copper-based nanoclusters have emerged as versatile and sustainable catalysts for challenging organic bond-forming reactions. Their unique properties, including natural abundance, accessible oxidation states, diverse ligand architectures, and strong photophysical characteristics, contribute to their growing prominence in this field. In this review, we discuss the photocatalytic activities of Cu-based nanoclusters, focusing on their applications in cross-coupling reactions (C-C and C-N), click reactions, multicomponent couplings, and oxidation reactions.

Fully coated WS2 antioxidant film with mesoporous structure for enhancing the structural stability and CDI performance of Mxene

Two-dimensional (2D) layer material MXene (Ti3C2Tx) is a promising electrode material in capacitive deionization (CDI) because of its advantages of large capacitance, high conductivity and abundant active sites. However, MXene nanosheets have a large number of metastable metal atoms, which are easy to react with dissolved oxygen and form metal oxides, resulting in structural instability and attenuation of electrochemical performance of MXene. Moreover, the inherent defects of MXene layered structure that are easy to stack, seriously limiting its application in CDI. In this paper, MXene fully coated by WS2 antioxidant film with mesoporous structure was designed and successfully prepared by hydrothermal method to form a 3D mutually supported heterostructure, so as to improve the structural stability and CDI performance of MXene. The heterostructure performs abundant mesoporous, excellent electrical conductivity, good hydrophilicity and excellent cyclic stability. Therefore, the WS2@MXene composite demonstrates high specific capacitance (217.0 F g−1) and retention rate of 90.51 % after 1000 GCD cycles. The hybrid AC//WS2@MXene cell composed of AC anode and WS2@MXene cathode shows excellent desalination capacity (39.1 mg g−1). The retention rate of the cell is still 94.9 % after 40 desalting cycles, which is better than that of AC//MXene cell (84.4 %).

Computational and crystallographic study of hydrogen bonds in the second coordination sphere of chelated amino acids with a free water molecule: Influence of complex charge and metal ion

Hydrogen bonds of glycine complexes were calculated using quantum chemistry calculations at M06L-GD3/def2-TZVPP level and by analyzing the crystal structures from the Cambridge Structural Database (CSD). One hydrogen bond where amino acid plays the role of the H-donor (NH/O), and two where it plays the role of the H-acceptor (O1/HO, O1 is a coordinated oxygen atom, and, O2/HO, O2 is a non-coordinated oxygen atom) were investigated. The calculations were done on octahedral nickel(II), square pyramidal copper(II), square planar copper(II), palladium(II), and platinum(II) glycine complexes with different charges adjusted using water(s) and/or chlorine ion(s) as the remaining ligands. For NH/O hydrogen bond, interaction energies of neutral complexes are the weakest, from −5.2 to −7.2 kcal/mol for neutral, stronger for singly positive, from −8.3 to −12.1 kcal/mol, and the strongest for doubly positive complex, −16.9 kcal/mol. For O1/HO and O2/HO interactions, neutral complexes have weaker interaction energies (from −2.2 to −5.1 kcal/mol for O1/HO, and from −3.7 to −5.0 kcal/mol for O2/HO), than for singly negative complexes (from −6.9 to −8.2 kcal/mol for O1/HO, and from −8.0 to −9.0 kcal/mol for O2/HO). Additionally to the complex charge, metal oxidation number, coordination number, and metal atomic number also influence the hydrogen bond strength, however, the influence is smaller.

Precise Confinement and Position Distribution of Atomic Cu and Zn in ZSM-5 for CO2 Hydrogenation to Methanol

CuZn-based catalysts are widely used in CO2 hydrogenation, which may effectively convert CO2 to methanol and alleviate CO2 emission issues. The precise design of a model catalyst with a clear atomic structure is crucial in studying the relationship between structure and catalytic activity. In this work, a one-pot strategy was used to synthesize CuZn@ZSM-5 catalysts with approximately two Cu atoms and one Zn atom per unit cell. Atomic Cu and Zn species are confirmed to be located in the [54.6.102] and [62.104] tilings, respectively, by using magic-angle spinning nuclear magnetic resonance spectroscopy (MAS NMR), synchrotron X-ray powder diffraction (SXRD) and high-signal-to-noise-ratio annular dark field scanning transmission electron microscopy (High SNR ADF-STEM). Catalytic hydrogenation of CO2 to methanol was used as a model reaction to investigate the activity of the catalyst with confined active species. Compared to the Cu@ZSM-5, Zn@ZSM-5 and their mixture, the CuZn@ZSM-5 catalyst with a close Cu–Zn distance of 4.5 Å achieves a comparable methanol space–time yield (STY) of 92.0 mgmethanol·gcatal−1·h−1 at 533 K and 4 MPa with high stability. This method is able to confine one to three metal atoms in the zeolite channel and avoid migration and agglomeration of the atoms during the reaction, which maintains the stability of the catalyst and provides an efficient way for adjustment of the type and number of metal atoms along with the distances between them in zeolites.

Heterogeneous N-heterocyclic carbenes supported single-atom catalysts for nitrogen fixation: A combined density functional theory and machine learning study

Electrocatalytic nitrogen reduction reaction (NRR) has emerged as a sustainable and eco-friendly alternative for ammonia production at ambient conditions. Exploring highly efficient and selective electrocatalysts for NRR continues to gain significant attention, but remains a challenge. In this work, we conducted a series of single-atom catalysts (SACs) by embedding 29 kinds of transition metal (TM) atoms on the two-dimensional heterogeneous N-heterocyclic carbene, and systematically investigated their catalytic performance for NRR using density functional theory, high-throughput screening, and machine learning. Two promising candidates (TM = Mn and Ta) with high catalytic activity and selectivity were identified, with limiting potentials of - 0.51 and - 0.53 V, respectively. Moreover, considering solvation effects, the limiting potential for Mn was further reduced to -0.43 V. Machinelearning(ML)analysis revealedthat the adsorption energy of N2 emerged as an efficient descriptor for NRR activity, and transition metal atomic Mendeleev number (Nm), the molar volume of TM atoms (Vm) and the 1st ionization energy of TM atoms (Im) were intrinsic to the difference in NRR performance of these SACs. Our findings demonstrate a novel class of efficient SACs based on heterogeneous N-heterocyclic carbene, offering valuable insights for further design of NRR electrocatalysts with exceptional catalytic performance.

Machine Learning-Driven Discovery of Key Descriptors for CO2 Activation over Two-Dimensional Transition Metal Carbides and Nitrides.

Fusing high-throughput quantum mechanical screening techniques with modern artificial intelligence strategies is among the most fundamental ─yet revolutionary─ science activities, capable of opening new horizons in catalyst discovery. Here, we apply this strategy to the process of finding appropriate key descriptors for CO2 activation over two-dimensional transition metal (TM) carbides/nitrides (MXenes). Various machine learning (ML) models are developed to screen over 114 pure and defective MXenes, where the random forest regressor (RFR) ML scheme exhibits the best predictive performance for the CO2 adsorption energy, with a mean absolute error ± standard deviation of 0.16 ± 0.01 and 0.42 ± 0.06 eV for training and test data sets, respectively. Feature importance analysis revealed d-band center (εd), surface metal electronegativity (χM), and valence electron number of metal atoms (MV) as key descriptors for CO2 activation. These findings furnish a fundamental basis for designing novel MXene-based catalysts through the prediction of potential indicators for CO2 activation and their posterior usage.

The identification and quantification of metal atoms in proteins using microPIXE: A critical evaluation

Around one third of all known protein molecules contain a small number of metal atoms which are often crucial to the biological function of the molecule. Identifying and quantifying these is not possible using commonly available analysis tools and there is a growing awareness that a majority of the metal atoms in the over 38,000 metalloprotein structures deposited in the Protein Data Bank are misidentified, with major consequences for the interpretation of protein function and mechanism. In the 1990s the authors developed a method for the identification and quantification of metals in liquid and crystalline protein samples by combining microbeam Proton Induced X-ray Emission and Rutherford backscattering. This has been used on overexpressed and purified proteins and has addressed many critical metal identification problems in structural biology. The capability has recently been extended to provide high throughput capability.In this paper we give an overview of the methodology and provide a critical evaluation of accuracy and detection limit and provide guidance on the optimisation of sample preparation and analysis conditions for these measurements. The discussion will be illustrated using some recent results illustrating the power of this method to answer biological questions.

Programmable kernel structures of atomically precise metal nanoclusters for tailoring catalytic properties.

The unclear structures and polydispersity of metal nanoparticles (NPs) seriously hamper the identification of the active sites and the construction of structure-reactivity relationships. Fortunately, ligand-protected metal nanoclusters (NCs) with atomically precise structures and monodispersity have become an ideal candidate for understanding the well-defined correlations between structure and catalytic property at an atomic level. The programmable kernel structures of atomically precise metal NCs provide a fantastic chance to modulate their size, shape, atomic arrangement, and electron state by the precise modulating of the number, type, and location of metal atoms. Thus, the special focus of this review highlights the most recent process in tailoring the catalytic activity and selectivity over metal NCs by precisely controlling their kernel structures. This review is expected to shed light on the in-depth understanding of metal NCs' kernel structures and reactivity relationships.

Mass cytometry for the multiplexed quantification and characterization of target expression on circulating cells in whole blood.

Characterization of target abundance on cells has broad translational applications. Among the approaches for assessing membrane target expression is quantification of the number of target-specific antibody (Ab) bound per cell (ABC). ABC determination on relevant cell subsets in complex and limited biological samples necessitates multidimensional immunophenotyping, for which the high-order multiparameter capabilities of mass cytometry provide considerable advantages. In the present study, we describe the implementation of CyTOF® for the concomitant quantification of membrane markers on diverse types of immune cells in human whole blood. Specifically, our protocol relies on establishing Bmax of Ab saturable binding on cells, then converted into ABC according to a metal's transmission efficiency and number of metal atoms per Ab. Using this method, we calculated ABC values for CD4 and CD8 within the expected range for circulating T cells and in concordance with the ABC obtained in the same samples by flow cytometry. Furthermore, we successfully conducted multiplex measurements of the ABC for CD28, CD16, CD32a, and CD64, on >15 immune cell subsets in human whole blood samples. We developed a high-dimensional data analysis workflow enabling semi-automated Bmax calculation in all examined cell subsets to facilitate ABC reporting across populations. In addition, we investigated impacts of the type of metal isotope and acquisition batch effect on the ABC evaluation with CyTOF®. In summary, our findings demonstrate mass cytometry is a valuable tool for concurrent quantitative analysis of multiple targets in specific and rare cell types, thus increasing the numbers of biomeasures obtained from a single sample.