Quantitative Subsurface Atomic Structure Fingerprint for 2D Materials and Heterostructures by First-Principles-Calibrated Contact-Resonance Atomic Force Microscopy

Anomalous Correlation between Thermal Conductivity and Elastic Modulus in Two-Dimensional Hybrid Metal Halide Perovskites

Device-level implementation of soft materials for energy conversion and thermal management demands a comprehensive understanding of their thermal conductivity and elastic modulus to mitigate thermo-mechanical challenges and ensure long-term stability. Thermal conductivity and elastic modulus are usually positively correlated in soft materials, such as amorphous macromolecules, which poses a challenge to discover materials that are either soft and thermally conductive or hard and thermally insulative. Here, we show anomalous correlations of thermal conductivity and elastic modulus in two-dimensional (2D) hybrid organic-inorganic perovskites (HOIP) by engineering the molecular interactions between organic cations. By replacing conventional alkyl-alkyl and aryl-aryl type organic interactions with mixed alkyl-aryl interactions, we observe an enhancement in elastic modulus with a reduction in thermal conductivity. This anomalous dependence provides a route to engineer thermal conductivity and elastic modulus independently and a guideline to search for better thermal management materials. Further, introducing chirality into the organic cation induces a molecular packing that leads to the same thermal conductivity and elastic modulus regardless of the composition across all half-chiral 2D HOIPs. This finding provides substantial leeway for further investigations in chiral 2D HOIPs to tune optoelectronic properties without compromising thermal and mechanical stability.

Imaging beyond the surface region: Probing hidden materials via atomic force microscopy

Probing material properties at surfaces down to the single-particle scale of atoms and molecules has been achieved, but high-resolution subsurface imaging remains a nanometrology challenge due to electromagnetic and acoustic dispersion and diffraction. The atomically sharp probe used in scanning probe microscopy (SPM) has broken these limits at surfaces. Subsurface imaging is possible under certain physical, chemical, electrical, and thermal gradients present in the material. Of all the SPM techniques, atomic force microscopy has entertained unique opportunities for nondestructive and label-free measurements. Here, we explore the physics of the subsurface imaging problem and the emerging solutions that offer exceptional potential for visualization. We discuss materials science, electronics, biology, polymer and composite sciences, and emerging quantum sensing and quantum bio-imaging applications. The perspectives and prospects of subsurface techniques are presented to stimulate further work toward enabling noninvasive high spatial and spectral resolution investigation of materials including meta- and quantum materials.

Tautomerism unveils a self-inhibition mechanism of crystallization

Modifiers are commonly used in natural, biological, and synthetic crystallization to tailor the growth of diverse materials. Here, we identify tautomers as a new class of modifiers where the dynamic interconversion between solute and its corresponding tautomer(s) produces native crystal growth inhibitors. The macroscopic and microscopic effects imposed by inhibitor-crystal interactions reveal dual mechanisms of inhibition where tautomer occlusion within crystals that leads to natural bending, tunes elastic modulus, and selectively alters the rate of crystal dissolution. Our study focuses on ammonium urate crystallization and shows that the keto-enol form of urate, which exists as a minor tautomer, is a potent inhibitor that nearly suppresses crystal growth at select solution alkalinity and supersaturation. The generalizability of this phenomenon is demonstrated for two additional tautomers with relevance to biological systems and pharmaceuticals. These findings offer potential routes in crystal engineering to strategically control the mechanical or physicochemical properties of tautomeric materials.

Intelligent Identification of MoS2 Nanostructures with Hyperspectral Imaging by 3D-CNN

Increasing attention has been paid to two-dimensional (2D) materials because of their superior performance and wafer-level synthesis methods. However, the large-area characterization, precision, intelligent automation, and high-efficiency detection of nanostructures for 2D materials have not yet reached an industrial level. Therefore, we use big data analysis and deep learning methods to develop a set of visible-light hyperspectral imaging technologies successfully for the automatic identification of few-layers MoS₂. For the classification algorithm, we propose deep neural network, one-dimensional (1D) convolutional neural network, and three-dimensional (3D) convolutional neural network (3D-CNN) models to explore the correlation between the accuracy of model recognition and the optical characteristics of few-layers MoS₂. The experimental results show that the 3D-CNN has better generalization capability than other classification models, and this model is applicable to the feature input of the spatial and spectral domains. Such a difference consists in previous versions of the present study without specific substrate, and images of different dynamic ranges on a section of the sample may be administered via the automatic shutter aperture. Therefore, adjusting the imaging quality under the same color contrast conditions is unnecessary, and the process of the conventional image is not used to achieve the maximum field of view recognition range of ~1.92 mm². The image resolution can reach ~100 nm and the detection time is 3 min per one image.

Subsurface imaging of rigid particles buried in a polymer matrix based on atomic force microscopy mechanical sensing

Several subsurface imaging methods based on atomic force microscopy (AFM) linear nanomechanical mapping, namely contact resonance (CR), bimodal and harmonic AFMs, are investigated and compared. Their respective subsurface detection capability is estimated and evaluated on a model specimen, which is prepared by embedding SiO₂ microparticles in a PDMS elastomer. The measured CR frequency, bimodal and harmonic amplitudes are related to local mechanical properties by analyzing cantilever dynamics and further linked to subsurface depths of the particles by finite element analysis. The maximum detectable depths are obtained from the apparent particle diameters in subsurface image channels via employing a simple geometrical model. Under common experimental settings, results demonstrate that the depth limits reach up to about 812 nm, 212 nm and 127 nm for CR, bimodal and harmonic AFM modes, respectively. The depth sensitivity can be tuned and optimized by using either different cantilever eigenmodes in CR-AFM or spectroscopy analysis in bimodal and harmonic AFMs. The three imaging methods have their own suitable application situations. The comparisons can advance a further step into understanding the subsurface image contrast via AFM mechanical sensing.

Stretching and Breaking of Ultrathin 2D Hybrid Organic-Inorganic Perovskites

Two-dimensional (2D) hybrid organic-inorganic perovskites (HOIPs) are recent members of the 2D materials family with wide tunability, highly dynamic structural features, and excellent physical properties. Ultrathin 2D HOIPs and their heterostructures with other 2D materials have been exploited for study of physical phenomena and device applications. The in-plane mechanical properties of 2D ultrathin HOIPs are critical for understanding the coupling between mechanical and other physical fields and for integrated devices applications. Here we report the in-plane mechanical properties of ultrathin freestanding 2D lead iodide perovskite membranes and their dependence on the membrane thickness. The in-plane Young's moduli of 2D HOIPs are smaller than that of conventional covalently bonded 2D materials. As the thickness increases from monolayer to three-layer, both the Young's modulus and breaking strength decrease, while three-layer and four-layer 2D HOIPs have almost identical in-plane mechanical properties. These thickness-dependent mechanical properties can be attributed to interlayer slippage during deformation. Our results show that ultrathin 2D HOIPs exhibit outstanding breaking strength/Young's modulus ratio compared to many other widely used engineering materials and polymeric flexible substrates, which renders them suitable for application into flexible electronic devices.

Interface Characterization and Control of 2D Materials and Heterostructures

2D materials and heterostructures have attracted significant attention for a variety of nanoelectronic and optoelectronic applications. At the atomically thin limit, the material characteristics and functionalities are dominated by surface chemistry and interface coupling. Therefore, methods for comprehensively characterizing and precisely controlling surfaces and interfaces are required to realize the full technological potential of 2D materials. Here, the surface and interface properties that govern the performance of 2D materials are introduced. Then the experimental approaches that resolve surface and interface phenomena down to the atomic scale, as well as strategies that allow tuning and optimization of interfacial interactions in van der Waals heterostructures, are systematically reviewed. Finally, a future outlook that delineates the remaining challenges and opportunities for 2D material interface characterization and control is presented.

Out-of-Plane Mechanical Properties of 2D Hybrid Organic-Inorganic Perovskites by Nanoindentation

Two-dimensional (2D) layered hybrid organic-inorganic perovskites (HOIPs) have demonstrated improved stability and promising photovoltaic performance. The mechanical properties of such functional materials are both fundamentally and practically important to achieve both high performance and mechanically stable (flexible) devices. Here, we report the mechanical properties of a series of 2D layered lead iodide HOIPs and investigate the role of structural subunits (e.g., variation of the length of the organic spacer molecules, R and the number of inorganic layers, n) in the mechanical properties. Although 2D HOIPs have much lower nominal elastic modulus and hardness than 3D HOIPs, larger n number and shorter R lead to stiffer materials. Density functional theory simulations showed a trend similar to the experimental results. We compared these findings with other 2D layered crystals and shed light on routes to further tune the out-of-plane mechanical properties of 2D layered HOIPs.

Identification of nanoparticles and nanosystems in biological matrices with scanning probe microscopy

Identification of nanoparticles and nanosystems into cells and biological matrices is a hot research topic in nanobiotechnologies. Because of their capability to map physical properties (mechanical, electric, magnetic, chemical, or optical), several scanning probe microscopy based techniques have been proposed for the subsurface detection of nanomaterials in biological systems. In particular, atomic force microscopy (AFM) can be used to reveal stiff nanoparticles in cells and other soft biomaterials by probing the sample mechanical properties through the acquisition of local indentation curves or through the combination of ultrasound-based methods, like contact resonance AFM (CR-AFM) or scanning near field ultrasound holography. Magnetic force microscopy can detect magnetic nanoparticles and other magnetic (bio)materials in nonmagnetic biological samples, while electric force microscopy, conductive AFM, and Kelvin probe force microscopy can reveal buried nanomaterials on the basis of the differences between their electric properties and those of the surrounding matrices. Finally, scanning near field optical microscopy and tip-enhanced Raman spectroscopy can visualize buried nanostructures on the basis of their optical and chemical properties. Despite at a still early stage, these methods are promising for detection of nanomaterials in biological systems as they could be truly noninvasive, would not require destructive and time-consuming specific sample preparation, could be performed in vitro, on alive samples and in water or physiological environment, and by continuously imaging the same sample could be used to dynamically monitor the diffusion paths and interaction mechanisms of nanomaterials into cells and biological systems. This article is categorized under: Diagnostic Tools > In Vivo Nanodiagnostics and Imaging Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.

Fast, High Resolution, and Wide Modulus Range Nanomechanical Mapping with Bimodal Tapping Mode

Tapping mode atomic force microscopy (AFM), also known as amplitude modulated (AM) or AC mode, is a proven, reliable, and gentle imaging mode with widespread applications. Over the several decades that tapping mode has been in use, quantification of tip-sample mechanical properties such as stiffness has remained elusive. Bimodal tapping mode keeps the advantages of single-frequency tapping mode while extending the technique by driving and measuring an additional resonant mode of the cantilever. The simultaneously measured observables of this additional resonance provide the additional information necessary to extract quantitative nanomechanical information about the tip-sample mechanics. Specifically, driving the higher cantilever resonance in a frequency modulated (FM) mode allows direct measurement of the tip-sample interaction stiffness and, with appropriate modeling, the set point-independent local elastic modulus. Here we discuss the advantages of bimodal tapping, coined AM-FM imaging, for modulus mapping. Results are presented for samples over a wide modulus range, from a compliant gel (∼100 MPa) to stiff materials (∼100 GPa), with the same type of cantilever. We also show high-resolution (subnanometer) stiffness mapping of individual molecules in semicrystalline polymers and of DNA in fluid. Combined with the ability to remain quantitative even at line scan rates of nearly 40 Hz, the results demonstrate the versatility of AM-FM imaging for nanomechanical characterization in a wide range of applications.

Nanoscale subsurface imaging

The ability to probe structures and functional properties of complex systems at the nanoscale, both at their surface and in their volume, has drawn substantial attention in recent years. Besides detecting heterogeneities, cracks and defects below the surface, more advanced explorations of chemical or electrical properties are of great interest. In this article, we review some approaches developed to explore heterogeneities below the surface, including recent progress in the different aspects of metrology in optics, electron microscopy, and scanning probe microscopy. We discuss the principle and mechanisms of image formation associated with each technique, including data acquisition, data analysis and modeling for nanoscale structural and functional imaging. We highlight the advances based on atomic force microscopy (AFM). Our discussion first introduces methods providing structural information of the buried structures, such as position in the volume and geometry. Next we present how functional properties including conductivity, capacitance, and composition can be extracted from the modalities available to date and how they could eventually enable tomography reconstructions of systems such as overlay structures in transistors or living systems. Finally we propose a perspective regarding the outstanding challenges and needs to push the field forward.

Interfacial Mechanical Properties of Graphene on Self-Assembled Monolayers: Experiments and Simulations

Self-assembled monolayers (SAMs) have been widely used to engineer the electronic properties of substrate-supported graphene devices. However, little is known about how the surface chemistry of SAMs affects the interfacial mechanical properties of graphene supported on SAMs. Fluctuations and changes in these properties affect the stress transfer between substrate and the supported graphene and thus the performance of graphene-based devices. The changes in interfacial mechanical properties can be characterized by measuring the out-of-plane elastic properties. Combining contact resonance atomic force microcopy experiments with molecular dynamics simulations, we show that the head group chemistry of a SAM, which affects the interfacial interactions, can have a significant effect on the out-of-plane elastic modulus of the graphene-SAM heterostructure. Graphene supported on hydrophobic SAMs leads to heterostructures stiffer than those of graphene supported on hydrophilic SAMs, which is largely due to fewer water molecules present at the graphene-SAM interface. Our results provide an important, and often overlooked, insight into the mechanical properties of substrate-supported graphene electronics.