On-surface preparation of coordinated lanthanide-transition-metal clusters

Surface-supported metal-organic frameworks with geometric topological diversity via scanning tunneling microscopy

Surface-supported metal-organic frameworks (SMOFs) are long-range ordered periodic 2D lattice layers formed by inorganic metal nodes and organic ligands via coordination bonds on substrate surfaces. The atomic resolution STM lays a solid foundation for the conception and construction of SMOFs with large area, stable structure, and special function. In this review, the cutting-edge research of SMOFs from design strategy, preparation process, and how to accurately achieve structural and functional diversity are reviewed. Furthermore, we focus on the design and construction of novel and fascinating periodic and fractal structures, in which some typical honeycomb structures, Kagome lattice, hexagonal geometry, and Sierpiński triangles are summarized, and the related prospects for designing functional nanoscale systems and architectures are prospected. Finally, the challenges faced in the design and synthesis of SMOFs are denoted, and the application prospect and development trend of SMOFs are forecasted based on the current research status.

Automated Generation and Analysis of Molecular Images Using Generative Artificial Intelligence Models

The development of scanning probe microscopy (SPM) has enabled unprecedented scientific discoveries through high-resolution imaging. Simulations and theoretical analysis of SPM images are equally important as obtaining experimental images since their comparisons provide fruitful understandings of the structures and physical properties of the investigated systems. So far, SPM image simulations are conventionally based on quantum mechanical theories, which can take several days in tasks of large-scale systems. Here, we have developed a scanning tunneling microscopy (STM) molecular image simulation and analysis framework based on a generative adversarial model, CycleGAN. It allows efficient translations between STM data and molecular models. Our CycleGAN-based framework introduces an approach for high-fidelity STM image simulation, outperforming traditional quantum mechanical methods in efficiency and accuracy. We envision that the integration of generative networks and high-resolution molecular imaging opens avenues in materials discovery relying on SPM technologies.

Surface-confined alternating copolymerization with molecular precision by stoichiometric control

Keen desires for artificial mimicry of biological polymers and property improvement of synthesized ones have triggered intensive explorations for sequence-controlled copolymerization. However, conventional synthesis faces great challenges to achieve this goal due to the strict requirements on reaction kinetics of comonomer pairs and tedious synthetic processes. Here, sequence-controlled alternating copolymerization with molecular precision is realized on surface. The stoichiometric control serves as a thermodynamic strategy to steer the polymerization selectivity, which enables the selective alternating organometallic copolymerization via intermolecular metalation of 4,4"-dibromo-p-terphenyl (P-Br) and 2,5-diethynyl-1,4-bis(phenylethynyl)benzene (A-H) with Ag adatoms on Ag(111) at P-Br: A-H = 2, as verified by scanning tunneling microscopy and density functional theory studies. In contrast, homopolymerization yield increases as the stoichiometric ratio deviates from 2. The microscopic characterizations rationalize the mechanism, providing a delicate explanation of the stoichiometry-dependent polymerization. These findings pave a way to actualizing an efficient sequence control of copolymerization by surface chemistry.

Designed metal-organic π-clusters combining the aromaticity of the metal cluster and ligands for a third-order nonlinear optical response

The pivotal role of clusters and aromaticity in chemistry is undeniable, but there remains a gap in systematically understanding the aromaticity of metal-organic clusters. Herein, this article presents a novel metal-organic π-cluster, melding both metal-organic chemistry and aromaticity, to guide the construction of structurally stable Os-organic π-clusters. An in-depth analysis of these clusters reveals their bonding attributes, π-electronic composition, and origins of aromaticity, thereby confirming their unique metal-organic π-cluster properties. Furthermore, the Os5 cluster exhibits a promising third-order nonlinear optical (NLO) response, attributable to its narrow band gap and uniform electron/hole distribution, suggesting its potential as an optical switching material. This research introduces a fresh perspective on clusters, centered on delocalization, and broadens the domain of aromaticity studies. It also presents a novel method for designing efficient third-order NLO materials through consideration of the structure-activity relationship.

Order-Disorder Transition of Two-Dimensional Molecular Networks through a Stoichiometric Design

Materials with disordered structures may exhibit interesting properties. Metal-organic frameworks (MOFs) are a class of hybrid materials composed of metal nodes and coordinating organic linkers. Recently, there has been growing interest in MOFs with structural disorder and the investigations of amorphous structures on surfaces. Herein, we demonstrate a bottom-up method to construct disordered molecular networks on metal surfaces by selecting two organic molecule linkers with the same symmetry but different sizes for preparing two-component samples with different stoichiometric ratios. The amorphous networks are directly imaged by scanning tunneling microscopy under ultrahigh vacuum with a submolecular resolution, allowing us to quantify its degree of disorder and other structural properties. Furthermore, we resort to molecular dynamics simulations to understand the formation of the amorphous metal-organic networks. The results may advance our understanding of the mechanism of formation of monolayer molecular networks with structural disorders, facilitating the design and exploration of amorphous MOF materials with intriguing properties.

Applying a Deep-Learning-Based Keypoint Detection in Analyzing Surface Nanostructures

Scanning tunneling microscopy (STM) imaging has been routinely applied in studying surface nanostructures owing to its capability of acquiring high-resolution molecule-level images of surface nanostructures. However, the image analysis still heavily relies on manual analysis, which is often laborious and lacks uniform criteria. Recently, machine learning has emerged as a powerful tool in material science research for the automatic analysis and processing of image data. In this paper, we propose a method for analyzing molecular STM images using computer vision techniques. We develop a lightweight deep learning framework based on the YOLO algorithm by labeling molecules with its keypoints. Our framework achieves high efficiency while maintaining accuracy, enabling the recognitions of molecules and further statistical analysis. In addition, the usefulness of this model is exemplified by exploring the length of polyphenylene chains fabricated from on-surface synthesis. We foresee that computer vision methods will be frequently used in analyzing image data in the field of surface chemistry.

Structure transformation from Sierpiński triangles to chains assisted by gas molecules

Reversible transformations between fractals and periodic structures are of fundamental importance for understanding the formation mechanism of fractals. Currently, it is still a challenge to controllably achieve such a transformation. We investigate the effect of CO and CO2 molecules on Sierpiński triangles (STs) assembled from Fe atoms and 4,4″-dicyano-1,1':3',1″-terphenyl (C3PC) molecules on Au surfaces. Using scanning tunneling microscopy, we discover that the gas molecules induce a transition from STs into 1D chains. Based on density functional theory modeling, we propose that the atomistic mechanism involves the transformation of a stable 3-fold coordination Fe(C3PC)3 motif to Fe(C3PC)4 with an axially bonded CO molecule. CO2 causes the structural transformation through a molecular catassembly process.

High-Throughput Preparation of Supramolecular Nanostructures on Metal Surfaces

One of the contemporary challenges in materials science lies in the rapid materials screening and discovery. Experimental sample libraries can be generated by high-throughput parallel synthesis to map the composition space for rapid material discoveries. Molecular self-assembly on surfaces has proved a useful way to construct nanostructures with interesting topologies or properties. Despite the strong dependence of molecular stoichiometry on the structures, high-throughput preparations of supramolecular surface nanostructures have been far less explored. Here, by integrating a physical mask into the standard ultra-high-vacuum (UHV) molecular preparation system we show a high-throughput approach for preparing supramolecular nanostructures of continuous composition spreads on metal surfaces. The spatially addressable sample libraries of supramolecular self-assemblies are characterized by high-resolution scanning probe microscopy. We could explore different binary nanostructures of varying molecular ratios on one single substrate. Moreover, we use the minimum spanning tree approach to qualitatively and quantitatively study the structural properties of the formed nanostructures. This high-throughput approach may accelerate the screening and exploration of surface-supported, low-dimensional nanostructures not limited to supramolecular interactions.

Engineering Periodic Dinuclear Lanthanide-Directed Networks Featuring Tunable Energy Level Alignment and Magnetic Anisotropy by Metal Exchange

The design of lanthanide multinuclear networks is an emerging field of research due to the potential of such materials for nanomagnetism, spintronics, and quantum information. Therefore, controlling their electronic and magnetic properties is of paramount importance to tailor the envisioned functionalities. In this work, a multidisciplinary study is presented combining scanning tunneling microscopy, scanning tunneling spectroscopy, X-ray absorption spectroscopy, X-ray linear dichroism, X-ray magnetic circular dichroism, density functional theory, and multiplet calculations, about the supramolecular assembly, electronic and magnetic properties of periodic dinuclear 2D networks based on lanthanide-pyridyl interactions on Au(111). Er- and Dy-directed assemblies feature identical structural architectures stabilized by metal-organic coordination. Notably, despite exhibiting the same +3 oxidation state, there is a shift of the energy level alignment of the unoccupied molecular orbitals between Er- and Dy-directed networks. In addition, there is a reorientation of the easy axis of magnetization and an increment of the magnetic anisotropy when the metallic center is changed from Er to Dy. Thus, the results show that it is feasible to tune the energy level alignment and magnetic anisotropy of a lanthanide-based metal-organic architecture by metal exchange, while preserving the network design.

An intermetallic molecular nanomagnet with the lanthanide coordinated only by transition metals

Magnetic molecules known as molecular nanomagnets (MNMs) may be the key to ultra-high density data storage. Thus, novel strategies on how to design MNMs are desirable. Here, inspired by the hexagonal structure of the hardest intermetallic magnet SmCo₅, we have synthesized a nanomagnetic molecule where the central lanthanide (Ln) Er^III is coordinated solely by three transition metal ions (TM) in a perfectly trigonal planar fashion. This intermetallic molecule [Er^III(Re^ICp₂)₃] (ErRe₃) starts a family of molecular nanomagnets (MNM) with unsupported Ln-TM bonds and paves the way towards molecular intermetallics with strong direct magnetic exchange interactions-a promising route towards high-performance single-molecule magnets.

Monte Carlo Simulations of the Metal-Directed Self-Assembly of Y-Shaped Positional Isomers

The rational fabrication of low-dimensional materials with a well-defined topology and functions is an incredibly important aspect of nanotechnology. In particular, the on-surface synthesis (OSS) methods based on the bottom-up approach enable a facile construction of sophisticated molecular architectures unattainable by traditional methods of wet chemistry. Among such supramolecular constructs, especially interesting are the surface-supported metal–organic networks (SMONs), composed of low-coordinated metal atoms and π-aromatic bridging linkers. In this work, the lattice Monte Carlo (MC) simulation technique was used to extract the chemical information encoded in a family of Y-shaped positional isomers co-adsorbed with trivalent metal atoms on a flat metallic surface with (111) geometry. Depending on the intramolecular distribution of active centers (within the simulated molecular bricks, we observed a metal-directed self-assembly of two-dimensional (2D) openwork patterns, aperiodic mosaics, and metal–organic ladders. The obtained theoretical findings could be especially relevant for the scanning tunneling microscopy (STM) experimentalists interested in a surface-assisted construction of complex nanomaterials stabilized by directional coordination bonds.

Rotation in an Enantiospecific Self-Assembled Array of Molecular Raffle Wheels

Tailored nano-spaces can control enantioselective adsorption and molecular motion. We report on the spontaneous assembly of a dynamic system-a rigid kagome network with each pore occupied by a guest molecule-employing solely 2,6-bis(1H-pyrazol-1-yl)pyridine-4-carboxylic acid on Ag(111). The network cavity snugly hosts the chemically modified guest, bestows enantiomorphic adsorption and allows selective rotational motions. Temperature-dependent scanning tunnelling microscopy studies revealed distinct anchoring orientations of the guest unit switching with a 0.95 eV thermal barrier. H-bonding between the guest and the host transiently stabilises the rotating guest, as the flapper on a raffle wheel. Density functional theory investigations unravel the detailed molecular pirouette of the guest and how the energy landscape is determined by H-bond formation and breakage. The origin of the guest's enantiodirected, dynamic anchoring lies in the specific interplay of the kagome network and the silver surface.

Packing Biomolecules into Sierpiński Triangles with Global Organizational Chirality

Fractals are found in nature and play important roles in biological functions. However, it is challenging to controllably prepare biomolecule fractals. In this study, a series of Sierpiński triangles with global organizational chirality is successfully constructed by the coassembly of l-tryptophan and 1,3-bi(4-pyridyl)benzene molecules on Ag(111). The chirality is switched when replacing l-tryptophan by d-tryptophan. The fractal structures are characterized by low-temperature scanning tunneling microscopy at the single-molecule level. Density functional theory calculations reveal that intermolecular hydrogen bonds stabilize the Sierpiński triangles.