Machine Learning-Accelerated High-Throughput Computational Screening: Unveiling Bimetallic Nanoparticles with Peroxidase-Like Activity.

Bimetallic nanoparticles (NPs) with peroxidase-like (POD-like) activity play a crucial role in biosensing, disease treatment, environmental management, and other fields. However, their development is impeded by a vast range of tunable properties in components and structures, making the establishment of structure-effect relationships and the discovery of active materials challenging. Addressing this, we established robust scaling relationships by meticulously analyzing the catalytic reaction networks of pure metal NPs, which laid the volcano-shaped correlation between the activity and O* adsorption energy. Utilizing these relationships, we introduced an innovative and versatile descriptor of the NPs, which was then integrated into a machine learning-accelerated high-throughput computational workflow, significantly boosting the predictive accuracy for the POD-like activity of bimetallic NPs. Our methodological approach enabled the successful prediction of activities for 1260 bimetallic NPs, leading to the identification of several highly effective catalysts. Furthermore, we distilled several strategies for designing efficient bimetallic NPs based on our screening results.

Steering the Reconstruction of Oxide-Derived Cu by Secondary Metal for Electrosynthesis of n-Propanol from CO.

As fuel and an important chemical feedstock, n-propanol is highly desired in electrochemical CO2/CO reduction on Cu catalysts. However, the precise regulation of the Cu localized structure is still challenging and poorly understood, thus hindering the selective n-propanol electrosynthesis. Herein, by decorating Au nanoparticles (NPs) on CuO nanosheets (NSs), we present a counterintuitive transformation of CuO into undercoordinated Cu sites locally around Au NPs during CO reduction. In situ spectroscopic techniques reveal the Au-steered formation of abundant undercoordinated Cu sites during the removal of oxygen on CuO. First-principles accuracy molecular dynamic simulation demonstrates that the localized Cu atoms around Au tend to rearrange into disordered layer rather than a Cu (111) close-packed plane observed on bare CuO NSs. These Au-steered undercoordinated Cu sites facilitate CO binding, enabling selective electroreduction of CO into n-propanol with a high Faradaic efficiency of 48% in a flow cell. This work provides new insight into the regulation of the oxide-derived catalysts reconstruction with a secondary metal component.

Regulating reconstruction of oxide-derived Cu for electrochemical CO2 reduction toward n-propanol.

Oxide-derived copper (OD-Cu) is the most efficient and likely practical electrocatalyst for CO2 reduction toward multicarbon products. However, the inevitable but poorly understood reconstruction from the pristine state to the working state of OD-Cu under strong reduction conditions largely hinders the rational construction of catalysts toward multicarbon products, especially C3 products like n-propanol. Here, we simulate the reconstruction of CuO and Cu2O into their derived Cu by molecular dynamics, revealing that CuO-derived Cu (CuOD-Cu) intrinsically has a richer population of undercoordinated Cu sites and higher surficial Cu atom density than the counterpart Cu2O-derived Cu (Cu2OD-Cu) because of the vigorous oxygen removal. In situ spectroscopes disclose that the coordination number of CuOD-Cu is considerably lower than that of Cu2OD-Cu, enabling the fast kinetics of CO2 reaction and strengthened binding of *C2 intermediate(s). Benefiting from the rich undercoordinated Cu sites, CuOD-Cu achieves remarkable n-propanol faradaic efficiency up to ~17.9%, whereas the Cu2OD-Cu dominantly generates formate.

Construction of High Accuracy Machine Learning Interatomic Potential for Surface/Interface of Nanomaterials-A Review.

The inherent discontinuity and unique dimensional attributes of nanomaterial surfaces and interfaces bestow them with various exceptional properties. These properties, however, also introduce difficulties for both experimental and computational studies. The advent of machine learning interatomic potential (MLIP) addresses some of the limitations associated with empirical force fields, presenting a valuable avenue for accurate simulations of these surfaces/interfaces of nanomaterials. Central to this approach is the idea of capturing the relationship between system configuration and potential energy, leveraging the proficiency of machine learning (ML) to precisely approximate high-dimensional functions. This review offers an in-depth examination of MLIP principles and their execution and elaborates on their applications in the realm of nanomaterial surface and interface systems. The prevailing challenges faced by this potent methodology are also discussed.

An accurate interatomic potential for the TiAlNb ternary alloy developed by deep neural network learning method.

The complex phase diagram and bonding nature of the TiAl system make it difficult to accurately describe its various properties and phases by traditional atomistic force fields. Here, we develop a machine learning interatomic potential with a deep neural network method for the TiAlNb ternary alloy based on a dataset built by first-principles calculations. The training set includes bulk elementary metals and intermetallic structures with slab and amorphous configurations. This potential is validated by comparing bulk properties-including lattice constant and elastic constants, surface energies, vacancy formation energies, and stacking fault energies-with their respective density functional theory values. Moreover, our potential could accurately predict the average formation energy and stacking fault energy of γ-TiAl doped with Nb. The tensile properties of γ-TiAl are simulated by our potential and verified by experiments. These results support the applicability of our potential under more practical conditions.

Surface-Mediated Production of Complexed •OH Radicals and FeO Species as a Mechanism for Iron Oxide Peroxidase-Like Nanozymes.

Fe3 O4 nanoparticles (NPs) with intrinsic peroxidase-like properties have attracted significant interest, although limited information is available on the definite catalytic mechanism. Here, it is shown that both complexed hydroxyl radicals (•OH) and high-valent FeO species are attributed primarily to the peroxidase-like catalytic activity of Fe3 O4 NPs under acid conditions rather than only being caused by free •OH radicals generated through the iron-driven Fenton/Haber-Weiss reactions as previously thought. The low energy barrier of OO bond dissociation of H2 O2 /•OOH (0.14 eV) and the high oxidation activity of surface FeO (0 eV) due to the reduced state of Fe on the surface of Fe3 O4 NPs thermodynamically favor both the •OH and FeO pathways. By contrast, high-valent FeO species are the key intermediates in the catalytic cycles of natural peroxidase enzymes. Moreover, it is demonstrated that the enzyme-like activity of Fe3 O4 NPs can be rationally regulated by modulating the size, surface structure, and valence of active metal atoms in the light of this newly proposed nanozyme catalytic mechanism.

Polyethylenimine-Poly(lactic-co-glycolic acid)2 Nanoparticles Show an Innate Targeting Ability to the Submandibular Salivary Gland via the Muscarinic 3 Receptor.

Polymeric nanoparticles have been extensively explored for biomedical applications, especially as framework materials for the construction of functional nanostructures. However, less attention has been paid to the inherent biological activities of those polymers. In this work, one of the commonly used polymers in gene and protein delivery, polyethylenimine-poly(lactic-co-glycolic acid)2 (PEI-PLGA), was discovered by accident to be able to mediate the nanoparticles to target the submandibular salivary glands of mice after intravenous injection. PEI-PLGA nanoparticles with an unmodified PEI surface selectively accumulated in submandibular salivary glands with ex vivo and in vitro study, suggesting that a ligand-receptor interaction between PEI and muscarinic acetylcholine receptor subtype 3 (M3 receptor) contributed to this affinity. Docking computation for the molecular binding mode between PEI segments and M3 receptor indicated the way they interacted was similar to that of the FDA-approved specific M3 receptor antagonist, tiotropium. The key amino acids mediated this specific interaction between PEI-PLGA nanoparticles and M3 receptor were identified via a simulated alanine mutation study. This work demonstrates the unique characteristic of PEI-PLGA nanoparticles, which may be useful for the development of muscarinic receptor targeted nanomedicines and should be taken into consideration when PEI-based nanoparticles are applied in gene delivery.

The role of supported dual-atom on graphitic carbon nitride for selective and efficient CO2electrochemical reduction.

The electrochemical reduction of CO2into value-added fuels and chemicals using single atom (SACs) or dual-atom catalysts (DACs) has been extensively studied, but the reaction mechanism and design rules are still unclear. Here, we studied the role of dual-metal atoms on graphite carbon nitride (M1M2@g-CN, M1M2 = CuCu, FeFe, RuRu, RuCu, RuFe, CuFe) for selective and efficient CO2electrochemical reduction based on density functional theory. Our results show that CO2RR on RuRu@g-CN catalyst prefers the *COOH pathway, while for CuCu@g-CN, FeFe@g-CN, RuCu@g-CN, RuFe@g-CN, CuFe@g-CN catalysts, the *OCHO pathway is more suitable. Among all the DACs combinations, we found that RuCu@g-CN and RuFe@g-CN are the most promising electrocatalysts for CO2RR with a lower limiting potential, which is attributed to the synergistic effect of different O- and C-affinity of the heterocenters in DACs. The selectivity of RuCu@g-CN and RuFe@g-CN to the production of CH4is better than that of H2evolution. In addition, we also found that the adsorption free energy of intermediate on heteroatomic DACs can be predicted by those on homoatomic DACs, which can be used to further predict the limiting potential.

Bamboo-like π-Nanotubes with Tunable Helicity and Circularly Polarized Luminescence.

We report the fabrication of an exotic bamboo-like π-nanotube via the hierarchical self-assembly of a dipeptide-substituted naphthalenediimide gelator with tunable helicity and circularly polarized luminescence (CPL). It was found that in the presence of trifluoroacetic acid (TFA) the gelator molecules self-assembled into a bamboo-like π-nanotube, which is composed of truncated nanocones and CPL active. When defining the diameter ratio of the lower to upper edge of each nanocone as a parameter to express the helicity of different nanotubes, it was found that both the helicity and CPL of these nanotubes can be adjusted by the amount of TFA. Moreover, the helicity of the nanotube can be conveyed to the achiral quantum dots (QDs) and produce a hybrid nanotube/QDs CPL active materials with adjustable dissymmetry factor. This work finds a new type self-assembled bamboo-like π-nanotube and unveils their helicity and CPL control.

Cofactor-free oxidase-mimetic nanomaterials from self-assembled histidine-rich peptides.

Natural oxidases mainly rely on cofactors and well-arranged amino acid residues for catalysing electron-transfer reactions but suffer from non-recovery of their activity upon externally induced protein unfolding. However, it remains unknown whether residues at the active site can catalyse similar reactions in the absence of the cofactor. Here, we describe a series of self-assembling, histidine-rich peptides, as short as a dipeptide, with catalytic function similar to that of haem-dependent peroxidases. The histidine residues of the peptide chains form periodic arrays that are able to catalyse H2O2 reduction reactions efficiently through the formation of reactive ternary complex intermediates. The supramolecular catalyst exhibiting the highest activity could be switched between inactive and active states without loss of activity for ten cycles of heating/cooling or acidification/neutralization treatments, demonstrating the reversible assembly/disassembly of the active residues. These findings may aid the design of advanced biomimetic catalytic materials and provide a model for primitive cofactor-free enzymes.

Chiral gold nanoparticles enantioselectively rescue memory deficits in a mouse model of Alzheimer's disease.

Preventing aggregation of amyloid beta (Aß) peptides is a promising strategy for the treatment of Alzheimer's disease (AD), and gold nanoparticles have previously been explored as a potential anti-Aß therapeutics. Here we design and prepare 3.3 nm L- and D-glutathione stabilized gold nanoparticles (denoted as L3.3 and D3.3, respectively). Both chiral nanoparticles are able to inhibit aggregation of Aß42 and cross the blood-brain barrier (BBB) following intravenous administration without noticeable toxicity. D3.3 possesses a larger binding affinity to Aß42 and higher brain biodistribution compared with its enantiomer L3.3, giving rise to stronger inhibition of Aß42 fibrillation and better rescue of behavioral impairments in AD model mice. This conjugation of a small nanoparticle with chiral recognition moiety provides a potential therapeutic approach for AD.

Organoplatinum-Substituted Polyoxometalate Inhibits ß-amyloid Aggregation for Alzheimer's Therapy.

Aggregated ß-amyloid (Aß) is widely considered as a key factor in triggering progressive loss of neuronal function in Alzheimer's disease (AD), so targeting and inhibiting Aß aggregation has been broadly recognized as an efficient therapeutic strategy for curing AD. Herein, we designed and prepared an organic platinum-substituted polyoxometalate, (Me4 N)3 [PW11 O40 (SiC3 H6 NH2 )2 PtCl2 ] (abbreviated as PtII -PW11 ) for inhibiting Aß42 aggregation. The mechanism of inhibition on Aß42 aggregation by PtII -PW11 was attributed to the multiple interactions of PtII -PW11 with Aß42 including coordination interaction of Pt2+ in PtII -PW11 with amino group in Aß42 , electrostatic attraction, hydrogen bonding and van der Waals force. In cell-based assay, PtII -PW11 displayed remarkable neuroprotective effect for Aß42 aggregation-induced cytotoxicity, leading to increase of cell viability from 49 % to 67 % at a dosage of 8 µm. More importantly, the PtII -PW11 greatly reduced Aß deposition and rescued memory loss in APP/PS1 transgenic AD model mice without noticeable cytotoxicity, demonstrating its potential as drugs for AD treatment.

Enzyme Mimic Based on a Self-Assembled Chitosan/DNA Hybrid Exhibits Superior Activity and Tolerance.

Nature has evolved enzymes with exquisite active sites that catalyze biotransformations with high efficiency. However, the exploitation of natural enzymes is often hampered by poor stability, and natural enzyme production and purification are costly. Supramolecular self-assembly allows the construction of biomimetic active sites, although it is challenging to produce such artificial enzymes with catalytic activity and stability that rival those of natural enzymes. We report herein a strategy to produce a horseradish peroxidase (HRP) mimic based on the assembly of chitosan with a G-quadruplex DNA (G-DNA)/hemin complex. A network-like morphology of the assembled nanomaterial was observed together with a remarkable enhancement of peroxidase activity induced by the chitosan and G-DNA components. The turnover frequency and catalytic efficiency of the enzyme-mimicking material reached or even surpassed those of HRP. Moreover, the catalytic complex exhibited higher tolerance than HRP to harsh environments, such as extremely low pH or high temperatures. In accord with the experimental and simulated results, it is concluded that the spatial distribution of the G-DNA and chitosan components and the exposure of the catalytic center may facilitate the coordination of substrates by the hemin iron, leading to the superior activity of the material. Our work provides a simple and affordable avenue to produce highly active and robust enzyme-mimicking catalytic nanomaterials.

A non-conjugated polyethylenimine copolymer-based unorthodox nanoprobe for bioimaging and related mechanism exploration.

Unconventional non-conjugated photoluminescent polymers have attracted increasing attention in bioimaging application, however their nonclassical photoluminescence mechanisms remain largely unclear. Herein, an amphiphilic copolymer polyethyleneimine-poly(d,l-lactide) (PEI-PDLLA) was synthesized and the obtained PEI-PDLLA copolymer exhibited intrinsic visible blue luminescence in the solid and concentrated solution states under 365 nm UV light irradiation. Using a computational assay approach, we investigated the unconventional photoluminescence mechanism of PEI-PDLLA. The results revealed that such photoluminescence should be related to the "clustered heteroatom chromophores" formed by through-space electronic interactions of N-heteroatoms in PEI. The copolymers can function as a fluorescent nanoprobe (PEI-PDLLA NPs) via a facile nanoprecipitation method and the self-assembly mechanism of PEI-PDLLA NPs was also investigated in-depth by molecular dynamics simulation. Intriguingly, the PEI-PDLLA NPs exhibited a remarkable excitation-dependent multi-wavelength emission characteristic, which was promising in acquiring a high precision imaging effect. Moreover, in contrast with conventional organic dyes with aggregation-caused quenching (ACQ), the fluorescence intensity of the PEI-PDLLA NPs was enhanced with increasing solution concentration. Furthermore, their applications in bioimaging indicated that PEI-PDLLA NPs could be utilized as a lysosome-specific and tumor-targeted nanoprobe with excellent photostability and good biocompatibility.

Recent Advances in Nanozyme Research.

As a new generation of artificial enzymes, nanozymes have the advantages of high catalytic activity, good stability, low cost, and other unique properties of nanomaterials. Due to their wide range of potential applications, they have become an emerging field bridging nanotechnology and biology, attracting researchers in various fields to design and synthesize highly catalytically active nanozymes. However, the thorough understanding of experimental phenomena and the mechanisms beneath practical applications of nanozymes limits their rapid development. Herein, the progress of experimental and computational research of nanozymes on two issues over the past decade is briefly reviewed: (1) experimental development of new nanozymes mimicking different types of enzymes. This covers their structures and applications ranging from biosensing and bioimaging to therapeutics and environmental protection. (2) The catalytic mechanism proposed by experimental and theoretical study. The challenges and future directions of computational research in this field are also discussed.

Enantioseparation of Au20 (PP3 )4 Cl4 Clusters with Intrinsically Chiral Cores.

Au20 (PP3 )4 Cl4 (PP3 =tris(2-(diphenylphosphino)ethyl) phosphine), abbreviated as Au20 , is the only Au nanocluster with an intrinsically chiral core without a chiral environment (chiral ligands or Au-thiolate staples), making it a unique object to understand chiral evolution and explore chiral applications. Unfortunately, the synthesized Au20 is racemic, and its enantiomers have not yet been separated. Herein, we report a supramolecular assembly strategy with α-cyclodextrin (α-CD) to afford enantiopure Au20 in bulk, and an enantiomer excess (ee) value of as-separated Au20 of 97 %. As a result of its high purity, the distinctive optical activity of Au20 , which originates from electronic transitions confined in chiral cores, is fully explored. Theoretical studies reveals that the enantioseparation results from the preferential self-assembly of α-CD with organic ligands on the surface of right-handed Au20 .