Materials‐Informatics‐Assisted High‐Yield Synthesis of 2D Nanomaterials through Exfoliation

Molecular machines working at interfaces: physics, chemistry, evolution and nanoarchitectonics

As a post-nanotechnology concept, nanoarchitectonics combines nanotechnology with advanced materials science. Molecular machines made by assembling molecular units and their organizational bodies are also products of nanoarchitectonics. They can be regarded as the smallest functional materials. Originally, studies on molecular machines analyzed the average properties of objects dispersed in solution by spectroscopic methods. Researchers' playgrounds partially shifted to solid interfaces, because high-resolution observation of molecular machines is usually done on solid interfaces under high vacuum and cryogenic conditions. Additionally, to ensure the practical applicability of molecular machines, operation under ambient conditions is necessary. The latter conditions are met in dynamic interfacial environments such as the surface of water at room temperature. According to these backgrounds, this review summarizes the trends of molecular machines that continue to evolve under the concept of nanoarchitectonics in interfacial environments. Some recent examples of molecular machines in solution are briefly introduced first, which is followed by an overview of studies of molecular machines and similar supramolecular structures in various interfacial environments. The interfacial environments are classified into (i) solid interfaces, (ii) liquid interfaces, and (iii) various material and biological interfaces. Molecular machines are expanding their activities from the static environment of a solid interface to the more dynamic environment of a liquid interface. Molecular machines change their field of activity while maintaining their basic functions and induce the accumulation of individual molecular machines into macroscopic physical properties molecular machines through macroscopic mechanical motions can be employed to control molecular machines. Moreover, research on molecular machines is not limited to solid and liquid interfaces; interfaces with living organisms are also crucial.

Machine Learning-Assisted Exploration and Identification of Aqueous Dispersants in the Vast Diversity of Organic Chemicals

Dispersion represents a central processing method in the organization of nanomaterials; however, the strong interparticle interaction represents a significant obstacle to fabricating homogeneous and stable dispersions. While dispersants can greatly assist in overcoming this obstacle, the appropriate type is dependent on such factors as nanomaterial, solvent, experimental conditions, etc., and there is no general guide to assist in the selection from the vast number of possibilities. We report a strategy and successful demonstration of the machine-learning-based "Dispersant Explorer", which surveys and identifies suitable dispersants from open databases. Through the combined use of experimental and molecular descriptors derived from SMILES databases, the model showed exceptional predictive accuracy in surveying about ∼1000 chemical compounds and identifying those that could be applied as dispersants. Furthermore, fabrication of transparent conducting films using the predicted and previously unknown dispersant exhibited the highest sheet resistance and transmittance compared with those of other reported undoped films. This result highlights that, in addition to opening new avenues for novel dispersant discovery, machine learning has a potential to elucidate the chemical structures essential for optimal dispersion performance to assist in the advancement of the complex topic of nanomaterial processing.

Molybdenum Disulfide as Tunable Electrochemical and Optical Biosensing Platforms for Cancer Biomarker Detection: A Review

Cancer is a common illness with a high mortality. Compared with traditional technologies, biomarker detection, with its low cost and simple operation, has a higher sensitivity and faster speed in the early screening and prognosis of cancer. Therefore, extensive research has focused on the development of biosensors and the construction of sensing interfaces. Molybdenum disulfide (MoS2) is a promising two-dimensional (2D) nanomaterial, whose unique adjustable bandgap shows excellent electronic and optical properties in the construction of biosensor interfaces. It not only has the advantages of a high catalytic activity and low manufacturing costs, but it can also further expand the application of hybrid structures through different functionalization, and it is widely used in various biosensors fields. Herein, we provide a detailed introduction to the structure and synthesis methods of MoS2, and explore the unique properties and advantages/disadvantages exhibited by different structures. Specifically, we focus on the excellent properties and application performance of MoS2 and its composite structures, and discuss the widespread application of MoS2 in cancer biomarkers detection from both electrochemical and optical dimensions. Additionally, with the cross development of emerging technologies, we have also expanded the application of other emerging sensors based on MoS2 for early cancer diagnosis. Finally, we summarized the challenges and prospects of MoS2 in the synthesis, functionalization of composite groups, and applications, and provided some insights into the potential applications of these emerging nanomaterials in a wider range of fields.

Selective Syntheses of Thick and Thin Nanosheets Based on Correlation between Thickness and Lateral-Size Distribution

Exfoliation of layered materials, a typical route to obtain 2D materials, is not easily controlled because of the unpredictable downsizing processes. In particular, the thickness control remains as a complex challenge. Here, we found a correlation between the thickness and lateral size distribution of the exfoliated nanosheets, such as transition metal oxides and graphene oxide. The layered composites of the host metal oxides and interlayer organic guests are delaminated into the surface-modified nanosheets in organic dispersion media. The exfoliation behavior varies by combination of the hosts, guests, and dispersion media. Here, we found that the thick and thin nanosheets were obtained on the monodispersed and polydispersed conditions, respectively. The selective syntheses of the thick and thin nanosheets were achieved using a prediction model of the lateral size distribution. The correlation between the thickness and lateral size distribution can be applied to thickness-selective syntheses of 2D materials.

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Surface-modified nanosheets are obtained by exfoliation of layered composites

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Thickness of 2D materials has a correlation with the lateral size distribution

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Thick and thin nanosheets are selectively synthesized under the predicted conditions

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A prediction model of lateral size distribution is applied to the selective syntheses

Recent advances in biomedical applications of 2D nanomaterials with peroxidase-like properties

Significant progress has been made in developing two-dimensional (2D) nanomaterials owing to their ultra-thin structure, high specific surface area, and many other advantages. Recently, 2D nanomaterials with enzyme-like properties, especially peroxidase (POD)-like activity, are highly desirable for many biomedical applications. In this review, we first classify the types of 2D POD-like nanomaterials and then summarize various strategies for endowing 2D nanomaterials with POD-like properties. Representative examples of biomedical applications are reviewed, emphasizing in antibacterial, biosensing, and cancer therapy. Last, the future challenges and prospects of 2D POD-like nanomaterials are discussed. This review is expected to provide an in-depth understanding of 2D POD-like materials for biomedical applications.

Fast and efficient shear-force assisted production of covalently functionalized oxide nanosheets

HYPOTHESIS

While controlled and efficient exfoliation of layered oxides often remains a time consuming challenge, the surface modification of inorganic nanosheets is of outmost importance for future applications. The functionalization of the bulk material prior to exfoliation should allow the application of tools developped for Van der Waals materials to directly produce functionalized oxide nanosheets.

EXPERIMENTS

The Aurivillius phase Bi₂SrTa₂O₉ is functionalized by a linear aliphatic phosphonic acid via microwave-assisted reactions. The structure of the hybrid material and the coordination of the phosphonate group is scrutinized, notably by Pair Distribution Function. This functionalized layered oxide is then exfoliated in one hour in organic solvent, using high shear force dispersion. The obtained nanosheets are characterized in suspension and as deposits to check their chemical integrity.

FINDINGS

The covalent functionalization decreases the electrostatic cohesion between the inorganic layers leading to an efficient exfoliation in short time under shearing. The functionalization of the bulk material is preserved on the nanosheets upon exfoliation and plays a major role to enable liquid-phase exfoliation and in the stability of the resulting suspensions. This strategy is very promising for the straighforward preparation of functionalized nanosheets, paving the way for versatile design of new (multi)functional hybrid nanosheets for various potential applications.

Yield-prediction models for efficient exfoliation of soft layered materials into nanosheets

Yield-prediction models were studied for efficient exfoliation of soft layered materials stacked via van der Waals interactions with the assistance of machine learning on small experimental data. High-yield exfoliation of graphite and layered organic polymer was achieved under the conditions guided by the models in a limited number of experiments.

Generative Models for Extrapolation Prediction in Materials Informatics

We report a deep generative model for regression tasks in materials informatics. The model is introduced as a component of a data imputer and predicts more than 20 diverse experimental properties of organic molecules. The imputer is designed to predict material properties by "imagining" the missing data in the database, enabling the use of incomplete material data. Even removing 60% of the data does not diminish the prediction accuracy in a model task. Moreover, the model excels at extrapolation prediction, where target values of the test data are out of the range of the training data. Such an extrapolation has been regarded as an essential technique for exploring novel materials but has hardly been studied to date due to its difficulty. We demonstrate that the prediction performance can be improved by >30% by using the imputer compared with traditional linear regression and boosting models. The benefit becomes especially pronounced with few records for an experimental property (<100 cases) when prediction would be difficult by conventional methods. The presented approach can be used to more efficiently explore functional materials and break through previous performance limits.

Lateral-size control of exfoliated transition-metal-oxide 2D materials by machine learning on small data

A wide variety of nanosheets including monolayers and few-layers have attracted much interest as two-dimensional (2D) materials for the unique anisotropic structures and properties. On the other hand, one of the significant remaining and challenging issues is the lateral-size control. Since 2D materials are generally synthesized by the exfoliation of layered materials, the lateral size is not easily controlled in the breaking-down processes. The experimental factors have not been found for the control and prediction. In the present work, lateral sizes of the exfoliated transition-metal-oxide nanosheets were predicted and controlled by the assistance of machine learning. Layered composites of host inorganic layers and guest organic molecules were exfoliated into nanosheets in organic dispersion media. The lateral size of the nanosheets was estimated by dynamic light scattering (DLS), instead of microscopy methods, to achieve high-throughput analyses. Factors governing the lateral size are explored on the small experimental data by the assistance of sparse modeling, a method of machine learning. The eight physicochemical parameters of the organic guests and dispersion media were extracted by sparse modeling for the construction of the size-prediction model. The size-prediction model accelerated the selective syntheses of the nanosheets with large and small lateral sizes in a limited number of experiments. The results indicate that the prediction model is a guideline to find suitable exfoliation conditions for size control. Size-selective syntheses of a variety of 2D materials can be achieved by similar methods using sparse modeling on small experimental data. Moreover, sparse modeling is applicable to control the design and exploration of other materials and their processing based on small data.

Intercalation and flexibility chemistries of soft layered materials

Layered materials, alternate stackings of two or more components, are found in a wide range of scales. Chemists can design and synthesize layered structures containing functional units. The soft-type layered materials exhibit characteristic dynamic functions originating from two-dimensional (2D) anisotropy and structure flexibility. This feature article focuses on "intercalation" and "flexibility" as two new perspectives for designing soft layered materials. Intercalation of guests is a characteristic approach for design of layered structures. Flexibility is an important factor to control the dynamic functions of the layered structures. As a model case, the intercalation-induced tunable stimuli-responsive color-change properties of layered polydiacetylene (PDA) are introduced to study the impact of the intercalation and flexibility on the dynamic functions. Recently, layered materials have drastically expanded the research area from conventional rigid inorganic compounds to new self-assembled nanostructures consisting of organic components, such as polymers, metal-organic frameworks, and covalent-organic frameworks. These new layered architectures have potentials for exhibiting dynamic functions originating from the structure flexibility beyond the static properties originating from classical intercalation and host-guest chemistries. Therefore, intercalation and flexibility chemistries of soft layered materials are regarded as new perspectives for design of advanced dynamic functional materials.

Rapid and high-concentration exfoliation of montmorillonite into high-quality and mono-layered nanosheets

After montmorillonite (MTM) was first exfoliated into nanosheets as a reinforcing filler in the 1980s, layered clay became a hotspot of interest. However, to date, the exfoliation of the resource-rich and inexpensive layered MTM into high-quality nanosheets still remains a significant challenge. Herein, a simple and effective strategy to exfoliate layered MTM into mono-layered sheets via the aggregation of polyethyl-phosphate glycol ester (Exolit OP 550) is proposed. A significant decrease in exfoliation time from 120 min to 3 min was observed at room temperature only via a gentle stirring process. Moreover, various factors that reduce the viscosity of the mixture could be utilized to boost the exfoliated concentration to a record high value of 100 wt%, which is an increase of 460-2400% compared with that in other works. A tentative model was also proposed to illustrate the exfoliation mechanism based on the detection of segmental confined movement, structural evolution, and polymer-clay interaction. Particularly, the as-observed critical concentration of 200 wt% MTM indicated a saturation effect for the surface-adsorbed polymer. The critical concentration for the onset of exfoliation was 150 wt%. In addition, the structure of the exfoliated nanosheets in Exolit OP 550 underwent a temperature-sensitive and irreversible transformation. Thus, our study may provide new insight for the exfoliation of clay.

Amorphous flexible covalent organic networks containing redox-active moieties: a noncrystalline approach to the assembly of functional molecules

The organization states of functional molecules have a significant impact on the properties of materials. A variety of approaches have been studied to obtain well-organized molecular assemblies. The present work shows a new non-organized state of isolated and dispersed functional molecules in amorphous flexible covalent organic networks. Redox-active quinone molecules are embedded in the amorphous network polymers. Consecutive reactions between benzoquinone (BQ) and linker molecules generate random network structures through polymerization at different rates and in multiple directions. The low-crystalline stackings of the amorphous network polymers facilitate the formation of nanoflakes through exfoliation in dispersion media. Enhanced electrochemical performances, one of the highest specific capacities in recent studies, were achieved by efficient redox reactions of the quinone moiety. The present noncrystalline approach, low-crystalline stacking of designer amorphous covalent organic networks, can be applied to construct similar nanostructured polymer materials containing functional units.

Formation processes, size changes, and properties of nanosheets derived from exfoliation of soft layered inorganic-organic composites

Exfoliation is a general route to obtain two-dimensional (2D) nanomaterials. A variety of methods have been developed for controlled exfoliation of layered materials based on stacking via van der Waals interaction, such as graphite and transition-metal dichalcogenides. On the other hand, rigid layered materials consisting of inorganic layers and interlayer metal ions stacked via electrostatic interaction, such as transition-metal oxides and clays, have a limited number of exfoliation methods. Here we studied a new exfoliation route through formation of soft layered composites. Intercalation of guest organic molecules changed rigid inorganic layered compounds into soft layered composites with stacking via van der Waals interaction. The soft layered inorganic-organic composites were exfoliated into surface-modified nanosheets in organic media. The layered composites showed swelling with dispersion in organic media. The time-course analyses suggest that the layered composites were simultaneously exfoliated in the vertical direction and fractured in the lateral direction. Thinner and smaller nanosheets were obtained with an increase in the exfoliation time. Although the resultant nanosheets gradually aggregated in the colloidal liquid, the original dispersion state was recovered with sonication for 5 min at room temperature. This exfoliation route using soft layered composites can be used in the synthesis and application of a variety of 2D nanomaterials.