A method for structure prediction of metal-ligand interfaces of hybrid nanoparticles

Machine-learning accelerated structure search for ligand-protected clusters

Finding low-energy structures of ligand-protected clusters is challenging due to the enormous conformational space and the high computational cost of accurate quantum chemical methods for determining the structures and energies of conformers. Here, we adopted and utilized a kernel rigid regression based machine learning method to accelerate the search for low-energy structures of ligand-protected clusters. We chose the Au25(Cys)18 (Cys: cysteine) cluster as a model system to test and demonstrate our method. We found that the low-energy structures of the cluster are characterized by a specific hydrogen bond type in the cysteine. The different configurations of the ligand layer influence the structural and electronic properties of clusters.

Insights into the Interactions of Peptides with Monolayer-Protected Metal Nanoclusters

Monolayer-protected atomically precise metal nanoclusters (MPCs) have potential applications in catalysis, imaging, and drug delivery. Understanding their interactions with biomolecules such as peptides is of paramount interest for their use in cell imaging and drug delivery. Here we have carried out atomistic molecular dynamics simulations to investigate the interactions between MPCs and an anticancer peptide, melittin. Melittin gets attached to the MPCs surface by the formation of multiple hydrogen bonds between its amino acid residues with MPCs ligands. Additionally, the positively charged Lys, Arg, and peptide's N-terminal strongly anchor the peptide to the MPC metal surface, providing extra stabilization.

Smart Nanozymes for Cancer Therapy: The Next Frontier in Oncology

Nanomaterials that mimic the catalytic activity of natural enzymes in the complex biological environment of the human body are called nanozymes. Recently, nanozyme systems have been reported with diagnostic, imaging, and/or therapeutic capabilities. Smart nanozymes strategically exploit the tumor microenvironment (TME) by the in situ generation of reactive species or by the modulation of the TME itself to result in effective cancer therapy. This topical review focuses on such smart nanozymes for cancer diagnosis, and therapy modalities with enhanced therapeutic effects. The dominant factors that guide the rational design and synthesis of nanozymes for cancer therapy include an understanding of the dynamic TME, structure-activity relationships, surface chemistry for imparting selectivity, and site-specific therapy, and stimulus-responsive modulation of nanozyme activity. This article presents a comprehensive analysis of the subject including the diverse catalytic mechanisms of different types of nanozyme systems, an overview of the TME, cancer diagnosis, and synergistic cancer therapies. The strategic application of nanozymes in cancer treatment can well be a game changer in future oncology. Moreover, recent developments may pave the way for the deployment of nanozyme therapy into other complex healthcare challenges, such as genetic diseases, immune disorders, and ageing.

Exploring the Conformers of an Organic Molecule on a Metal Cluster with Bayesian Optimization

Finding low-energy conformers of organic molecules is a complex problem due to the flexibilities of the molecules and the high dimensionality of the search space. When such molecules are on nanoclusters, the search complexity is exacerbated by constraints imposed by the presence of the cluster and other surrounding molecules. To address this challenge, we modified our previously developed active learning molecular conformer search method based on Bayesian optimization and density functional theory. Especially, we have developed and tested strategies to avoid steric clashes between a molecule and a cluster. In this work, we chose a cysteine molecule on a well-studied gold-thiolate cluster as a model system to test and demonstrate our method. We found that cysteine conformers in a cluster inherit the hydrogen bond types from isolated conformers. However, the energy rankings and spacings between the conformers are reordered.

Phosphine-Stabilized Hidden Ground States in Gold Clusters Investigated via a Aun(PH3)m Database

Nanoclusters are promising materials for catalysis and sensing due to their large surface areas and unique electronic structures which can be tailored through composition, geometry, and chemistry. However, relationships correlating synthesis parameters directly to outcomes are limited. While previous computational studies have mapped the potential energy surface of specific systems of bare nanoclusters by generating and calculating the energies of reasonable structures, it is known that environmental ions and ligands crucially impact the final shape and size. In this work, phosphine-stabilized gold is considered as a test system and DFT calculations are performed for clusters with and without ligands, producing a database containing >10000 structures for Aun(PH3)m (n ≤ 12). We find that the ligation of phosphines affects the thermodynamic stability, bonding, and electronic structure of Au nanoclusters, specifically such that "hidden" ground state cluster geometries are stabilized that are dynamically unstable in the pure gold system. Further, the addition of phosphine introduces steric effects that induce a transition from planar to nonplanar structures at 4-5 Au atoms rather than up to 13-14 Au atoms, as previously predicted for bare clusters. This work highlights the importance of considering the ligand environment in the prediction of nanocluster morphology and functionality, which adds complexity as well as a rich opportunity for tunability.

Three-dimensional atomic mapping of ligands on palladium nanoparticles by atom probe tomography

Capping ligands are crucial to synthesizing colloidal nanoparticles with functional properties. However, the synergistic effect between different ligands and their distribution on crystallographic surfaces of nanoparticles during colloidal synthesis is still unclear despite powerful spectroscopic techniques, due to a lack of direct imaging techniques. In this study, atom probe tomography is adopted to investigate the three-dimensional atomic-scale distribution of two of the most common types of these ligands, cetrimonium (C₁₉H₄₂N) and halide (Br and Cl) ions, on Pd nanoparticles. The results, validated using density functional theory, demonstrate that the Br anions adsorbed on the nanoparticle surfaces promote the adsorption of the cetrimonium cations through electrostatic interactions, stabilizing the Pd {111} facets. In contrast, the Cl anions are not strongly adsorbed onto the Pd surfaces. The high density of adsorbed cetrimonium cations for Br anion additions results in the formation of multiple-twinned nanoparticles with superior oxidation resistance.

Correlating structural rules with electronic properties of ligand-protected alloy nanoclusters

Thiolate protected gold nanoclusters (TPNCs) are a unique class of nanomaterials finding applications in various fields, such as biomedicine, optics, and catalysis. The atomic precision of their structure, characterized through single crystal x-ray diffraction, enables the accurate investigation of their physicochemical properties through electronic structure calculations. Recent experimental efforts have led to the successful heterometal doping of TPNCs, potentially unlocking a large domain of bimetallic TPNCs for targeted applications. However, how TPNC size, bimetallic composition, and location of dopants influence electronic structure is unknown. To this end, we introduce novel structure-property relationships (SPRs) that predict electronic properties such as ionization potential (IP) and electron affinity (EA) of AgAu TPNCs based on physically relevant descriptors. The models are constructed by first generating a hypothetical AgAu TPNC dataset of 368 structures with sizes varying from 36 to 279 metal atoms. Using our dataset calculated with density functional theory (DFT), we employed systematic analyses to unravel size, composition, and, importantly, core-shell effects on TPNC EA and IP behavior. We develop generalized SPRs that are able to predict electronic properties across the AgAu TPNC materials space. The models leverage the same three fundamental descriptors (i.e., size, composition, and core-shell makeup) that do not require DFT calculations and rely only on simple atom counting, opening avenues for high throughput bimetallic TPNC screening for targeted applications. This work is a first step toward finely controlling TPNC electronic properties through heterometal doping using high throughput computational means.

Toward Controlling the Electronic Structures of Chemically Modified Superatoms of Gold and Silver

Atomically precise gold/silver clusters protected by organic ligands L, [(Au/Ag)_x L_y ]^z , have gained increasing interest as building units of functional materials because of their novel photophysical and physicochemical properties. The properties of [(Au/Ag)_x L_y ]^z are intimately associated with the quantized electronic structures of the metallic cores, which can be viewed as superatoms from the analogy of naked Au/Ag clusters. Thus, establishment of the correlation between the geometric and electronic structures of the superatomic cores is crucial for rational design and improvement of the properties of [(Au/Ag)_x L_y ]^z . This review article aims to provide a qualitative understanding on how the electronic structures of [(Au/Ag)_x L_y ]^z are affected by geometric structures of the superatomic cores with a focus on three factors: size, shape, and composition, on the basis of single-crystal X-ray diffraction data. The knowledge accumulated here will constitute a basis for the development of ligand-protected Au/Ag clusters as new artificial elements on a nanometer scale.

Selectivity in the Ligand Functionalization of Photocatalytic Metal Oxide Nanoparticles for Phase Transfer and Self-Assembly Applications

The functionalization of photocatalytic metal oxide nanoparticles of TiO₂ , ZnO, WO₃ and CuO with amine-terminated (oleylamine) and thiol-terminated (dodecane-1-thiol) alkyl-chain ligands was studied under ambient conditions. A high selectivity was observed in the binding specificity of a ligand towards nanoparticles of these different oxides. It was observed that oleylamine binds stably to only TiO₂ and WO₃ , whereas dodecane-1-thiol binds stably only to ZnO and CuO. Similarly, polar-to-nonpolar solvent phase transfer of TiO₂ and WO₃ nanoparticles could be achieved by using oleylamine, but not dodecane-1-thiol, whereas the opposite holds for ZnO and CuO. The surface chemistry of ligand-functionalized nanoparticles was probed by attenuated total reflectance (ATR)-FTIR spectroscopy, which enabled the occupation of the ligands at the active sites to be elucidated. The photostability of the ligands on the nanoparticle surface was determined by the photocatalytic self-cleaning properties of the material. Although TiO₂ and WO₃ degrade the ligands within 24 h under both UV and visible light, ligands on ZnO and CuO remain unaffected. The gathered insights are also highly relevant from an application point of view. As an example, because the ligand-functionalized nanoparticles are hydrophobic in nature, they can be self-assembled at the air-water interface to give nanoparticle films with demonstrated photocatalytic as well as anti-fogging properties.

Endosomal pH-Responsive Fe-Based Hyaluronate Nanoparticles for Doxorubicin Delivery

In this study, we report pH-responsive metal-based biopolymer nanoparticles (NPs) for tumor-specific chemotherapy. Here, aminated hyaluronic acid (aHA) coupled with 2,3-dimethylmaleic anhydride (DMA, as a pH-responsive moiety) (aHA-DMA) was electrostatically complexed with ferrous chloride tetrahydrate (FeCl₂/4H₂O, as a chelating metal) and doxorubicin (DOX, as an antitumor drug model), producing DOX-loaded Fe-based hyaluronate nanoparticles (DOX@aHA-DMA/Fe NPs). Importantly, the DOX@aHA-DMA/Fe NPs improved tumor cellular uptake due to HA-mediated endocytosis for tumor cells overexpressing CD44 receptors. As a result, the average fluorescent DOX intensity observed in MDA-MB-231 cells (with CD44 receptors) was ~7.9 × 10² (DOX@HA/Fe NPs, without DMA), ~8.1 × 10² (DOX@aHA-DMA_0.36/Fe NPs), and ~9.3 × 10² (DOX@aHA-DMA_0.60/Fe NPs). Furthermore, the DOX@aHA-DMA/Fe NPs were destabilized due to ionic repulsion between Fe²⁺ and DMA-detached aHA (i.e., positively charged free aHA) in the acidic environment of tumor cells. This event accelerated the release of DOX from the destabilized NPs. Our results suggest that these NPs can be promising tumor-targeting drug carriers responding to acidic endosomal pH.

Prospects and challenges for computer simulations of monolayer-protected metal clusters

Precise knowledge of chemical composition and atomic structure of functional nanosized systems, such as metal clusters stabilized by an organic molecular layer, allows for detailed computational work to investigate structure-property relations. Here, we discuss selected recent examples of computational work that has advanced understanding of how these clusters work in catalysis, how they interact with biological systems, and how they can make self-assembled, macroscopic materials. A growing challenge is to develop effective new simulation methods that take into account the cluster-environment interactions. These new hybrid methods are likely to contain components from electronic structure theory combined with machine learning algorithms for accelerated evaluations of atom-atom interactions.

Dynamics of weak interactions in the ligand layer of meta-mercaptobenzoic acid protected gold nanoclusters Au68(m-MBA)32 and Au144(m-MBA)40

Atomically precise metal nanoclusters, stabilized and functionalized by organic ligands, are emerging nanomaterials with potential applications in plasmonics, nano-electronics, bio-imaging, nanocatalysis, and as therapeutic agents or drug carriers in nanomedicine. The ligand layer has an important role in modifying the physico-chemical properties of the clusters and in defining the interactions between the clusters and the environment. While this role is well recognized from a great deal of experimental studies, there is very little theoretical information on dynamical processes within the layer itself. Here, we have performed extensive molecular dynamics simulations, with forces calculated from the density functional theory, to investigate thermal stability and dynamics of the ligand layer of the meta-mercaptobenzoic acid (m-MBA) protected Au68 and Au144 nanoclusters, which are the first two gold nanoclusters structurally solved to atomic precision by electron microscopy [Azubel et al., Science, 2014, 345, 909 and ACS Nano, 2017, 11, 11866]. We visualize and analyze dynamics of three distinct non-covalent interactions, viz., ligand-ligand hydrogen bonding, metal-ligand O[double bond, length as m-dash]C-OHAu interaction, and metal-ligand Ph(π)Au interaction. We discuss their relevance for defining, at the same time, the dynamic stability and reactivity of the cluster. These interactions promote the possibility of ligand addition reactions for bio-functionalization or allow the protected cluster to act as a catalyst where active sites are dynamically accessible inside the ligand layer.

Ligand-protected gold/silver superatoms: current status and emerging trends

Monolayer-protected gold/silver clusters have attracted much interest as nano-scale building units for novel functional materials owing to their nonbulk-like structures and size-specific properties. They can be viewed as ligand-protected superatoms because their magic stabilities and fundamental properties are well explained in the framework of the jellium model. In the last decade, the number of ligand-protected superatoms with atomically-defined structures has been increasing rapidly thanks to the well-established synthesis and structural determination by X-ray crystallography. This perspective summarizes the current status and emerging trends in synthesis and characterization of superatoms. The topics related to synthesis include (1) development of targeted synthesis based on transformation, (2) enhancement of robustness and synthetic yield for practical applications, and (3) development of controlled fusion and assembly of well-defined superatoms to create new properties. New characterization approaches are also introduced such as (1) mass spectrometry and laser spectroscopies in the gas phase, (2) determination of static and dynamic structures, and (3) computational analysis by machine learning. Finally, future challenges and prospects are discussed for further promotion and development of materials science of superatoms.

This perspective summarizes the current status and emerging trends in synthesis and characterization of ligand-protected gold/silver superatoms.

Monte Carlo Simulations of Au38(SCH3)24 Nanocluster Using Distance-Based Machine Learning Methods

We present an implementation of distance-based machine learning (ML) methods to create a realistic atomistic interaction potential to be used in Monte Carlo simulations of thermal dynamics of thiolate (SR) protected gold nanoclusters. The ML potential is trained for Au₃₈(SR)₂₄ by using previously published, density functional theory (DFT) based, molecular dynamics (MD) simulation data on two experimentally characterized structural isomers of the cluster and validated against independent DFT MD simulations. This method opens a door to efficient probing of the configuration space for further investigations of thermal-dependent electronic and optical properties of Au₃₈(SR)₂₄. Our ML implementation strategy allows for generalization and accuracy control of distance-based ML models for complex nanostructures having several chemical elements and interactions of varying strength.

Towards elucidating structure of ligand-protected nanoclusters

Developing a centralized database for ligand-protected nanoclusters can fuel machine learning and data-science-based approaches towards theoretical structure prediction.