Understanding the Dynamic Aggregation in Single-Atom Catalysis.

The dynamic response of single-atom catalysts to a reactive environment is an increasingly significant topic for understanding the reaction mechanism at the molecular level. In particular, single atoms may experience dynamic aggregation into clusters or nanoparticles driven by thermodynamic or kinetic factors. Herein, the inherent mechanistic nuances that determine the dynamic profile during the reaction will be uncovered, including the intrinsic stability and site-migration barrier of single atoms, external stimuli (temperature, voltage, and adsorbates), and the influence of catalyst support. Such dynamic aggregation can be beneficial or deleterious on the catalytic performance depending on the optimal initial state. Those examples will be highlighted where in situ formed clusters, rather than single atoms, serve as catalytically active sites for improved catalytic performance. This is followed by the introduction of operando techniques to understand the structural evolution. Finally, the emerging strategies via confinement and defect-engineering to regulate dynamic aggregation will be briefly discussed.

LiDAR-camera-system-based unsupervised and weakly supervised 3D object detection.

LiDAR camera systems are now becoming an important part of autonomous driving 3D object detection. Due to limitations in time and resources, only a few critical frames of the synchronized camera data and acquired LiDAR points may be annotated. However, there is still a large amount of unannotated data in practical applications. Therefore, we propose a LiDAR-camera-system-based unsupervised and weakly supervised (LCUW) network as a novel 3D object-detection method. When unannotated data are put into the network, we propose an independent learning mode, which is an unsupervised data preprocessing module. Meanwhile, for detection tasks with high accuracy requirements, we propose an Accompany Construction mode, which is a weakly supervised data preprocessing module that requires only a small amount of annotated data. Then, we generate high-quality training data from the remaining unlabeled data. We also propose a full aggregation bridge block in the feature-extraction part, which uses a stepwise fusion and deepening representation strategy to improve the accuracy. Our comparative, ablation, and runtime test experiments show that the proposed method performs well while advancing the application of LiDAR camera systems.

Optimized dithering approach for 3D shape measurement using a phase-based chaos genetic algorithm.

A binary defocusing method has a significant impact on improving 3D shape measurement quality for digital fringe projector (DFP) techniques. In this paper, an optimization framework using the dithering method is presented. This framework utilizes genetic algorithm and chaos maps to optimize the bidirectional error-diffusion coefficients. It can effectively avoid quantization errors of binary patterns in a specific direction and obtain the fringe patterns with better symmetry and higher quality. In the process of the optimization, chaos initialization algorithms are used to generate a series of bidirectional error-diffusion coefficients as initial individuals. Additionally, mutation factors generated by chaotic maps, compared with the mutation rate, determine whether the individual position will mutate. Both simulations and experiments demonstrate that the proposed algorithm can improve the quality of phase and reconstruction at different defocus levels.

Modulating Catalytic Activity and Stability of Atomically Precise Gold Nanoclusters as Peroxidase Mimics via Ligand Engineering.

Metal nanoclusters (NCs), composed of a metal core and protecting ligands, show promising potentials as enzyme mimics for producing fuels, pharmaceuticals, and valuable chemicals, etc. Herein, we explore the critical role of ligands in modulating the peroxidase mimic activity and stability of Au NCs. A series of Au15(SR)13 NCs with various thiolate ligands [SR = N-acetyl-l-cysteine (NAC), 3-mercaptopropionic acid (MPA), or 3-mercapto-2-methylpropanoic acid (MMPA)] are utilized as model catalysts. It is found that Au15(NAC)13 shows higher structural stability than Au15(MMPA)13 and Au15(MPA)13 against external stimuli (e.g., pH, oxidants, and temperature) because of the intramolecular hydrogen bonds. More importantly, detailed enzymatic kinetics data show that the catalytic activity of Au15(NAC)13 is about 4.3 and 2.7 times higher than the catalytic activity of Au15(MMPA)13 and Au15(MPA)13, respectively. Density functional theory (DFT) calculations reveal that the Au atoms on the motif of Au NCs should be the active centers, whereas the superior peroxidase mimic activity of Au15(NAC)13 should originate from the emptier orbitals of Au atoms because of the electron-withdrawing effect of acetyl amino group in NAC. This work demonstrates the ligand-engineered electronic structure and functionality of atomically precise metal NCs, which afford molecular and atomic level insights for artificial enzyme design.

Supercrystal engineering of atomically precise gold nanoparticles promoted by surface dynamics.

The controllable packing of functional nanoparticles (NPs) into crystalline lattices is of interest in the development of NP-based materials. Here we demonstrate that the size, morphology and symmetry of such supercrystals can be tailored by adjusting the surface dynamics of their constituent NPs. In the presence of excess tetraethylammonium cations, atomically precise [Au25(SR)18]- NPs (where SR is a thiolate ligand) can be crystallized into micrometre-sized hexagonal rod-like supercrystals, rather than as face-centred-cubic superlattices otherwise. Experimental characterization supported by theoretical modelling shows that the rod-like crystals consist of polymeric chains in which Au25 NPs are held together by a linear SR-[Au(I)-SR]4 interparticle linker. This linker is formed by conjugation of two dynamically detached SR-[Au(I)-SR]2 protecting motifs from adjacent Au25 particles, and is stabilized by a combination of CH⋯π and ion-pairing interactions between tetraethylammonium cations and SR ligands. The symmetry, morphology and size of the resulting supercrystals can be systematically tuned by changing the concentration and type of the tetraalkylammonium cations.

Cation polymer-induced aggregation of water-soluble Au(I)-thiolate complexes and their photoluminescence properties.

Au(I)-thiolate complexes are a new class of aggregation-induced emission (AIE) material. Here we demonstrate a new aggregation strategy of water-soluble Au(I)-thiolate complexes induced by cationic polymers at optimized pH values. The generated AIE shows longer wavelengths than the emission induced by other methods.

Engineering Au Nanoclusters for Relay Luminescence Enhancement with Aggregation-Induced Emission.

The research of aggregation-induced emission (AIE) has been growing rapidly for the design of highly luminescent materials, as exemplified by the library of AIE-active materials (or AIEgens) fabricated and explored for diverse applications in different fields. Herein, we reported a relay luminescence enhancement of luminescent Au nanoclusters (Au NCs) through AIE. In addition, we demonstrated the emergence of reduced aggregation-caused luminescence by adjusting the temperature of the Au NC solution. The key to induce this effect is to attach a thermosensitive polymer poly(N-isopropylacrylamide) (PNIPAAm) on the surface of Au NCs, which will shrink at high temperature. More interestingly, the as-synthesized Au NCs-PNIPAAm can self-assemble into vesicles, resulting in an obvious decrease in the luminescence intensity in aqueous solution. The combination of relay luminescence enhancement (by AIE) and luminescence decrease (induced by thermosensitive polymers) will be beneficial to the understanding and manipulation of the optical properties of Au NCs, paving the way for their practical applications.

Interactions of Metal Nanoclusters with Light: Fundamentals and Applications.

The interactions of materials with light determine their applications in various fields. In the past decade, ultrasmall metal nanoclusters (NCs) have emerged as a promising class of optical materials due to their unique molecular-like properties. Herein, the basic principles of optical absorption and photoluminescence of metal NCs, their interactions with polarized light, and light-induced chemical reactions, are discussed, highlighting the roles of the core and protecting ligands/motifs of metal NCs in their interactions with light. The metal core and protecting ligands/motifs determine the electronic structures of metal NCs, which are closely related to their optical properties. In addition, the protecting ligands/motifs of metal NCs contribute to their photoluminescence and chiral origin, further promoting the interactions of metal NCs with light through various pathways. The fundamentals of light-NC interactions provide guidance for the design of metal NCs in optical applications, which are discussed in the second part. In the last section, some strategies are proposed to further understand light-NC interactions, highlighting the challenges and opportunities. It is hoped that this work will stimulate more research on the optical properties of metal NCs and their applications in various fields.

Diversification of Metallic Molecules through Derivatization Chemistry of Au25 Nanoclusters.

Derivatization is the fine chemistry that can produce chemical compounds from similar precursors and has been widely used in the field of organic synthesis to achieve diversification of molecular properties and functionalities. Ligand-protected metal nanoclusters (NCs) are metallic molecules with a definite molecular formula, well-defined molecular structure, and molecular-like physical and chemical properties. Unlike organic compounds, which have almost infinite species, until now only hundreds of metal NC species have been discovered, and only a few of them have been structurally resolved. Therefore, the diversification of NC species and functions is highly desirable in nanoscience and nanochemistry. As an efficient approach for generating a library of compounds from a given precursor, derivatization chemistry is not only applicable in producing new organic compounds but also a promising strategy for generating new metal NC species with intriguing properties and functions. The key to the derivatization of metal NCs is to design an efficient derivatization reaction suitable for metal NCs and spontaneously realize the customization of this special macromolecule (metallic molecule) at the atomic and molecular level.In this Account, we use the flagship thiolate-protected NC Au25SR18 (SR denotes a thiolate ligand) as a model to illustrate the derivatization chemistry of metal NCs. In the past 3 years we have developed various derivatization reactions of Au25SR18, including isomerization, redox, ligand addition, alloying, and self-assembly reactions. We discuss the mechanisms that govern these reactions to realize precise customization of the NC structure, size, surface, composition, and interactions. It is particularly noteworthy that advanced techniques such as real-time electrospray ionization mass spectrometry and NMR spectroscopy enable us to have an atomic- and molecular-level understanding of the reaction mechanisms, which will further promote our efforts to design derivatization reactions for metal NCs. Through these delicate derivatization reactions, we can produce Au25SR18 derivatives with new physical, chemical, and biological properties, including electronic structures, photoluminescence, surface reactivity, and antimicrobial properties. Finally, we provide our perspectives on the opportunities and challenges of metal NC derivatization.The derivatization chemistry of metal NCs can not only diversify the properties and functions of metal NCs but also help us understand the structure-property relationship and design principles of metal nanomaterials, which will help advance the research frontier of nanoscience toward atomic precision.

Revealing the etching process of water-soluble Au25 nanoclusters at the molecular level.

Etching (often considered as decomposition) is one of the key considerations in the synthesis, storage, and application of metal nanoparticles. However, the underlying chemistry of their etching process still remains elusive. Here, we use real-time electrospray ionization mass spectrometry to study the reaction dynamics and size/structure evolution of all the stable intermediates during the etching of water-soluble thiolate-protected gold nanoclusters (Au NCs), which reveal an unusual "recombination" process in the oxidative reaction environment after the initial decomposition process. Interestingly, the sizes of NC species grow larger and their ligand-to-metal ratios become higher during this recombination process, which are distinctly different from that observed in the reductive growth of Au NCs (e.g., lower ligand-to-metal ratios with increasing sizes). The etching chemistry revealed in this study provides molecular-level understandings on how metal nanoparticles transform under the oxidative reaction environment, providing efficient synthetic strategies for new NC species through the etching reactions.

Prediction of the Age at Onset of Spinocerebellar Ataxia Type 3 with Machine Learning.

BACKGROUND: In polyglutamine (polyQ) disease, the investigation of the prediction of a patient's age at onset (AAO) facilitates the development of disease-modifying intervention and underpins the delay of disease onset and progression. Few polyQ disease studies have evaluated AAO predicted by machine-learning algorithms and linear regression methods. OBJECTIVE: The objective of this study was to develop a machine-learning model for AAO prediction in the largest spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD) population from mainland China. METHODS: In this observational study, we introduced an innovative approach by systematically comparing the performance of 7 machine-learning algorithms with linear regression to explore AAO prediction in SCA3/MJD using CAG expansions of 10 polyQ-related genes, sex, and parental origin. RESULTS: Similar prediction performance of testing set and training set in each models were identified and few overfitting of training data was observed. Overall, the machine-learning-based XGBoost model exhibited the most favorable performance in AAO prediction over the traditional linear regression method and other 6 machine-learning algorithms for the training set and testing set. The optimal XGBoost model achieved mean absolute error, root mean square error, and median absolute error of 5.56, 7.13, 4.15 years, respectively, in testing set 1, with mean absolute error (4.78 years), root mean square error (6.31 years), and median absolute error (3.59 years) in testing set 2. CONCLUSION: Machine-learning algorithms can be used to predict AAO in patients with SCA3/MJD. The optimal XGBoost algorithm can provide a good reference for the establishment and optimization of prediction models for SCA3/MJD or other polyQ diseases. © 2020 International Parkinson and Movement Disorder Society.

Control of single-ligand chemistry on thiolated Au25 nanoclusters.

Diverse methods have been developed to tailor the number of metal atoms in metal nanoclusters, but control of surface ligand number at a given cluster size is rare. Here we demonstrate that reversible addition and elimination of a single surface thiolate ligand (-SR) on gold nanoclusters can be realized, opening the door to precision ligand engineering on atomically precise nanoclusters. We find that oxidative etching of [Au25SR18]- nanoclusters adds an excess thiolate ligand and generates a new species, [Au25SR19]0. The addition reaction can be reversed by CO reduction of [Au25SR19]0, leading back to [Au25SR18]- and eliminating precisely one surface ligand. Intriguingly, we show that the ligand shell of Au25 nanoclusters becomes more fragile and rigid after ligand addition. This reversible addition/elimination reaction of a single surface ligand on gold nanoclusters shows potential to precisely control the number of surface ligands and to explore new ligand space at each nuclearity.

Ligand-protected atomically precise gold nanoclusters as model catalysts for oxidation reactions.

Catalytic oxidation is an important reaction in the fine chemical industry, environment, and energy. In the past few decades, many kinds of catalysts have been produced with promising catalytic performance for oxidation reactions; however, the understanding of the mechanisms is still insufficient due to the complexity of the composition and structure of conventional catalysts. In the past several years, the community has tried to address this problem by using ligand-protected atomically precise gold nanoclusters as model catalysts. Ligand-protected gold nanoclusters possess well-defined molecular formulas and structures, and they could serve as ideal model catalysts to understand the correlations between the composition/structure and the catalytic properties at the atomic level. This feature article provides a systematic overview of the related oxidation reactions and the understanding of the mechanisms based on atomically precise gold nanoclusters.

Engineering ultrasmall metal nanoclusters for photocatalytic and electrocatalytic applications.

In view of many of the fundamental properties of ultrasmall noble metal nanoclusters progressively being uncovered, it has become increasingly clear that this class of materials has enormous potential for photocatalytic and electrocatalytic applications due to their unique electronic and optical properties. In this Minireview, we highlight the key electronic and optical properties of metal nanoclusters which are essential to photocatalysis and electrocatalysis. We further use these properties as the basis for our discussion to map out directions or principles for the rational design of high performance photocatalysts and electrocatalysts, highlighting several successful attempts along this direction.

Aurophilic Interactions in the Self-Assembly of Gold Nanoclusters into Nanoribbons with Enhanced Luminescence.

Aurophilic interactions (AuI ⋅⋅⋅AuI ) are crucial in directing the supramolecular self-assembly of many gold(I) compounds; however, this intriguing chemistry has been rarely explored for the self-assembly of nanoscale building blocks. Herein, we report on studies on aurophilic interactions in the structure-directed self-assembly of ultrasmall gold nanoparticles or nanoclusters (NCs, <2 nm) using [Au25 (SR)18 ]- (SR=thiolate ligand) as a model cluster. The self-assembly of NCs is initiated by surface-motif reconstruction of [Au25 (SR)18 ]- from short SR-[AuI -SR]2 units to long SR-[AuI -SR]x (x>2) staples accompanied by structure modification of the intrinsic Au13 kernel. Such motif reconstruction increases the content of AuI species in the protecting shell of Au NCs, providing the structural basis for directed aurophilic interactions, which promote the self-assembly of Au NCs into well-defined nanoribbons in solution. More interestingly, the compact structure and effective aurophilic interactions in the nanoribbons significantly enhance the luminescence intensity of Au NCs with an absolute quantum yield of 6.2 % at room temperature.

Electrospray Ionization Mass Spectrometry: A Powerful Platform for Noble-Metal Nanocluster Analysis.

Electrospray ionization mass spectrometry (ESI-MS) is an analytical technique that measures the mass of a sample through "soft" ionization. Recent years have witnessed a rapid growth of its application in noble-metal nanocluster (NC) analysis. ESI-MS is able to provide the mass of a noble-metal NC analyte for the analysis of their composition (n, m, q values in a general formula [Mn Lm ]q ), which is crucial in understanding their properties. This review attempts to present various developed techniques for the determination of the composition of noble metal NCs by ESI-MS. Additionally, advanced applications that use ESI-MS to further understand the reaction mechanism, complexation behavior, and structure of noble metal NCs are introduced. From the comprehensive applications of ESI-MS on noble-metal NCs, more possibilities in nanochemistry can be opened up by this powerful technique.

Hydride-induced ligand dynamic and structural transformation of gold nanoclusters during a catalytic reaction.

Quasi-homogeneous ligand-protected gold nanoclusters (Au NCs) with atomic precision and well-defined structure offer great opportunity for exploring the catalytic nature of nanogold catalysts at a molecular level. Herein, using real-time electrospray ionization mass spectrometry (ESI-MS), we have successfully identified the desorption and re-adsorption of p-mercaptobenzoic acid (p-MBA) ligands from Au25(p-MBA)18 NC catalysts during the hydrogenation of 4-nitrophenol in solution. This ligand dynamic (desorption and re-adsorption) would initiate structural transformation of Au25(p-MBA)18 NC catalysts during the reaction, forming a mixture of smaller Au NCs (Au23(p-MBA)16 as the major species) at the beginning of catalytic reaction, which could further be transformed into larger Au NCs (Au26(p-MBA)19 as the major species). The adsorption of hydrides (from NaBH4) is identified as the determining factor that could induce the ligand dynamic and structural transformation of NC catalysts. This study provides fundamental insights into the catalytic nature of Au NCs, including catalytic mechanism, active species and stability of Au NC catalysts during a catalytic reaction.

Unique size-dependent nanocatalysis revealed at the single atomically precise gold cluster level.

Atomically precise metal clusters have attracted increasing interest owing to their unique size-dependent properties; however, little has been known about the effect of size on the catalytic properties of metal clusters at the single-cluster level. Here, by real-time monitoring with single-molecule fluorescence microscopy the size-dependent catalytic process of individual Au clusters at single-turnover resolution, we study the size-dependent catalytic behaviors of gold (Au) clusters at the single-cluster level, and then observe the strong size effect on the catalytic properties of individual Au clusters, in both catalytic product formation and dissociation processes. Surprisingly, indicated by both experiments and density functional theory (DFT) calculations, due to such a unique size effect, besides observing the different product dissociation behaviors on different-sized Au clusters, we also observe that small Au clusters [i.e., Au15(MPA)13; here, MPA denotes 3-mercaptopropionic acid] catalyze the product formation through a competitive Langmuir-Hinshelwood mechanism, while those relatively larger Au clusters [e.g., Au18(MPA)14 and Au25(MPA)18] or nanoparticles catalyze the same process through a noncompetitive Langmuir-Hinshelwood mechanism. Such a size effect on the nanocatalysis could be attributed intrinsically to the size-dependent electronic structure of Au clusters. Further analysis of dynamic activity fluctuation of Au clusters reveals more different catalytic properties between Au clusters and traditional Au nanoparticles due to their different size-dependent structures.

Synthesis of Water-Soluble [Au25(SR)18]- Using a Stoichiometric Amount of NaBH4.

Determination of the stoichiometry of reactions is a pivotal step for any chemical reactions toward a desirable product, which has been successfully achieved in organic synthesis. Here, we present the first precise determination of the stoichiometry for the reactions toward gold nanoparticle formation in the sodium borohydride reduction method. Leveraging on the real-time mass spectrometry technique, we have determined a precise balanced reaction, 32/ x [Au(SR)] x + 8 e- = [Au25(SR)18]- + 7 [Au(SR)2]- (here SR denotes a thiolate ligand), toward a stoichiometric synthesis of water-soluble [Au25(SR)18]-, where 8 electrons (from reducing agents) are sufficient to react with every 32 Au atoms, leading to the formation of high-purity [Au25(SR)18]-. More interestingly, by real-time monitoring of the growth process of thiolate-protected Au nanoclusters, we have successfully identified an important yet missing byproduct, [Au(SR)2]-. This study not only provides a new method for Au nanocluster synthesis using only a stoichiometric amount of reducing agent in aqueous solutions (although the synthesis of organic-soluble Au nanoclusters might require a more delicate design of synthetic chemistry) but also promotes the mechanistic understandings of the Au nanocluster growth process.

Engineering Functional Metal Materials at the Atomic Level.

With continuous research efforts devoted into synthesis and characterization chemistry of functional nanomaterials in the past decades, the development of metal materials is stepping into a new era, where atom-by-atom customization of property-dictating structural attributes is expected. Herein, the state-of-the-art modulation of functional metal nanomaterials at the atomic level, by size- and structure-controlled synthesis of thiolate-protected metal (e.g., Au and Ag) nanoclusters (NCs), is exemplified. Metal NCs are ultrasmall (<3 nm) particles with hierarchical primary, secondary, and tertiary structures, reminiscent of natural proteins or enzymes. Given the proven dependence of their physicochemical properties on their size and structure, documented synthetic methodologies delivering NCs with atomic-level monodispersity and tailorable size and structural attributes at individual hierarchical levels are categorized and discussed. Such assured atomic-level modulation could confer metal NCs with novel application opportunities in diverse fields, which are also exemplified by their size- and structure-dictated catalytic and biomedical performance. The precise synthesis and application chemistry developed based on the hierarchical structure scheme of metal NCs could increase the acceptance of metal NCs as a new family of functional materials.