Scanning Probe Microscopy Research Articles

Ferroelectric Domain Modulation with Tip-Poling Engineering in BiFeO3 Films

BiFeO3 (BFO) films with ferroelectricity are the most promising candidates regarding the next generation of storage devices and sensors. The comprehensive understanding of ferroelectric switchable properties is challenging and critical to robust domain wall nanoelectronics. Herein, the domain dynamic was explored in detail under external bias conditions using scanning probe microscopy, which is meaningful for the understanding of domain dynamics and the foundation of ferroelectric devices. The results show that domain reversal occurred under external electric fields with sufficient energy excitation, combined with the existence of a charged domain wall. These findings extend the domain dynamic and current paths in ferroelectric films and shed light on the potential applications for ferroelectric devices.

Recent Progress of Imaging Chemical Bonds by Scanning Probe Microscopy: A Review.

In the past decades, the invention of scanning probe microscopy (SPM) as the versatile surface-based characterization of organic molecules has triggered significant interest throughout multidisciplinary fields. In particular, the bond-resolved imaging acquired by SPM techniques has extended its fundamental function of not only unraveling the chemical structure but also allowing us to resolve the structure-property relationship. Here, we present a systematical review on the history of chemical bonds imaged by means of noncontact atomic force microscopy (nc-AFM) and bond-resolved scanning tunneling microscopy (BR-STM) techniques. We first summarize the advancement of real-space imaging of covalent bonds and the investigation of intermolecular noncovalent bonds. Beyond the bond imaging, we also highlight the applications of the bond-resolved SPM techniques such as on-surface synthesis, the determination of the reaction pathway, the identification of molecular configurations and unknown products, and the generation of artificial molecules created via tip manipulation. Lastly, we discuss the current status of SPM techniques and highlight several key technical challenges that must be solved in the coming years. In comparison to the existing reviews, this work invokes researchers from surface science, chemistry, condensed matter physics, and theoretical physics to uncover the bond-resolved SPM technique as an emerging tool in exploiting the molecule/surface system and their future applications.

Unearthing Atomic Dynamics in Nanocatalysts.

Being able to access the rich atomic-scale phenomenology, which occurs during the reactions pathways, is a pressing need toward the pursued knowledge-based design of more efficient nanocatalysts, precisely tailored atom by atom for each reaction. However, to reach this goal of achieving maximum optimization, it is mandatory, first, to address how exposure to the experimental conditions, which will be needed to activate the processes, affects the internal configuration of the nanoparticles at the atomic level. In particular, the most critical experimental parameter is probably the temperature, which among other unwanted effects can induce nanocatalyst aggregation. This work highlights the high potential of experimental techniques such as the scanning probe microscopies, which are able to investigate matter in real space with atomic resolution, to reach the key challenge in heterogeneous catalysis of achieving access to the atomic-scale processes taking place in the nanocatalysts. Specifically, the phenomenology occurring in a nanoparticle system during annealing is studied with atomic precision by scanning tunneling microscopy. As a result, the existence of an internal atomic restructuring, occurring already at relatively low temperatures, within Ir nanoparticles grown over h-BN/Ru(0001) surfaces is demonstrated. Such restructuration, which reduces the undercoordination of the outer Ir atoms, is expected to have a significant effect on the reactivity of the nanoparticles. Going a step further, an internal restructuring of the nanoparticles during their involvement as catalysts has also been also identified.

Atomic Force Microscopy and Scanning Ion-Conductance Microscopy for Investigation of Biomechanical Characteristics of Neutrophils

Scanning probe microscopy (SPM) is a versatile tool for studying a wide range of materials. It is well suited for investigating living matter, for example, in single-cell neutrophil studies. SPM has been extensively utilized to analyze cell physical properties, providing detailed insights into their structural and functional characteristics at the nanoscale. Its long-standing application in this field highlights its essential role in cell biology and immunology research, significantly contributing to understanding cellular mechanics and interactions. In this review, we discuss the application of SPM techniques, specifically atomic force microscopy (AFM) and scanning ion-conductance microscopy (SICM), to study the fundamental functions of neutrophils. In addition, recent advances in the application of SPM in single-cell immunology are discussed. The application of these techniques allows for obtaining data on the morphology, topography, and mechanical and electrochemical properties of neutrophils with high accuracy.

Phonon-polariton Bragg generation at the surface of silicon carbide

Phonon-polaritons are known to emerge at the surface of solids under infrared (IR) irradiation at frequencies close to the optical phonon resonance. Metal, patterned on the top of the polariton-active surface, locally blocks the excitation of surface waves due to plasmonic screening and can be used for the design of wave patterns. We excite polaritonic waves at the surface of SiC under the irradiation of a CO2 laser (λ∼10μm) and visualize them using apertureless near-field interference scanning probe microscopy. From the near-field scans in the vicinity of gold film periodical strip structures, we identify the Bragg scattering (diffraction) outside the grating with the contribution from separate strips coherently summed up, provided that the wavelength matching condition is fulfilled. The observed phenomena agree with wavefield calculations. Our observations demonstrate the potential of metal-patterned silicon carbide for the fabrication of on-chip polaritonic IR circuits.

LOCAL DIELECTRIC SPECTROSCOPY AND ITS APPLICATION TO POLYMERS

ABSTRACT The advent of nanodielectrics, nanocomposite materials based on a polymeric matrix, and materials with physical properties ruled by interfacial effects in general demands techniques to characterize functional properties on a local scale with high spatial resolution. Scanning probe microscopies (SPMs), in their electrical modes, have emerged as indispensable tools to access physical quantities such as dielectric constant, surface potential, and static charge, with nanometer-scale lateral resolution and with surface selectivity, being influenced mainly by the outermost layer of the specimen. In this tribute, the development of various SPM electrical modes is illustrated, focusing on the measurement of dielectric permittivity and its spectroscopic extension to access the local, frequency-dependent dielectric function (local dielectric spectroscopy [LDS]). The application to nanostructured polymers in the form of ultrathin films, nanometer-scale–separated blends, and self-assembled block copolymer structures is described. LDS appears to be a promising technique for characterizing the electric properties of polymers and their composites as well as other glass formers and nanostructured systems.

On-Surface Atomic Scale Qubit Platform.

Recent advances in scanning probe microscopy combined with electron spin resonance have revealed that localized electron spins on or near surfaces can be utilized as building blocks for the bottom-up assembly of functional quantum-coherent nanostructures. In this perspective, we review the recent advances, lay out advantages of this platform and outline the challenges that lie ahead on the way to the application of on-surface atomic spins to quantum information science and quantum computing.

Autonomous Scanning Tunneling Microscopy Imaging via Deep Learning.

Scanning tunneling microscopy (STM) is a powerful technique that provides the ability to manipulate and characterize individual atoms and molecules with atomic-level precision. However, the processes of scanning samples, operating the probe, and analyzing data are typically labor-intensive and subjective. Deep learning (DL) techniques have shown immense potential in automating complex tasks and solving high-dimensional problems. In this study, we developed an autonomous STM framework powered by DL to enable autonomous operations of the STM without human interventions. Our framework employs a convolutional neural network (CNN) for real-time evaluation of STM image quality, a U-net model for identifying bare surfaces, and a deep Q-learning network (DQN) agent for autonomous probe conditioning. Additionally, we integrated an object recognition model for the automated recognition of different adsorbates. This autonomous framework enables the acquisition of space-averaging information using STM techniques without compromising the high-resolution molecular imaging. We achieved measuring an area of approximately 1.9 μm2 within 48 h of continuous measurement and automatedly generated the statistics on the molecular species present within the mesoscopic area. We demonstrate the high robustness of the framework by conducting measurements at the liquid nitrogen temperature (∼78 K). We envision that the integration of DL techniques and high-resolution microscopy will not only extend the functionality and capability of scanning probe microscopes but also accelerate the understanding and discovery of new materials.

Stitching accuracy in large area scanning probe microscopy

Stitching accuracy in large area scanning probe microscopy

Nonlinear Modeling of a Piezoelectric Actuator-Driven High-Speed Atomic Force Microscope Scanner Using a Variant DenseNet-Type Neural Network

Piezoelectric actuators (PEAs) are extensively used for scanning and positioning in scanning probe microscopy (SPM) due to their high precision, simple construction, and fast response. However, there are significant challenges for instrument designers due to their nonlinear properties. Nonlinear properties make precise and accurate control difficult in cases where position feedback sensors cannot be employed. However, the performance of PEA-driven scanners can be significantly improved without position feedback sensors if an accurate mathematical model with low computational costs is applied to reduce hysteresis and other nonlinear effects. Various methods have been proposed for modeling PEAs, but most of them have limitations in terms of their accuracy and computational efficiencies. In this research, we propose a variant DenseNet-type neural network (NN) model for modeling PEAs in an AFM scanner where position feedback sensors are not available. To improve the performance of this model, the mapping of the forward and backward directions is carried out separately. The experimental results successfully demonstrate the efficacy of the proposed model by reducing the relative root-mean-square (RMS) error to less than 0.1%.

Epitaxy of GaSe Coupled to Graphene: From In Situ Band Engineering to Photon Sensing.

2D semiconductors can drive advances in quantum science and technologies. However, they should be free of any contamination; also, the crystallographic ordering and coupling of adjacent layers and their electronic properties should be well-controlled, tunable, and scalable. Here, these challenges are addressed by a new approach, which combines molecular beam epitaxy and in situ band engineering in ultra-high vacuum of semiconducting gallium selenide (GaSe) on graphene. In situ studies by electron diffraction, scanning probe microscopy, and angle-resolved photoelectron spectroscopy reveal that atomically-thin layers of GaSe align in the layer plane with the underlying lattice of graphene. The GaSe/graphene heterostructure, referred to as 2semgraphene, features a centrosymmetric (group symmetry D3d) polymorph of GaSe, a charge dipole at the GaSe/graphene interface, and a band structure tunable by the layer thickness. The newly-developed, scalable 2semgraphene is used in optical sensors that exploit the photoactive GaSe layer and the built-in potential at its interface with the graphene channel. This proof of concept has the potential for further advances and device architectures that exploit 2semgraphene as a functional building block.

Machine learning approaches for improving atomic force microscopy instrumentation and data analytics

Atomic force microscopy (AFM) is a part of the scanning probe microscopy family. It provides a platform for high-resolution topographical imaging, surface analysis as well as nanomechanical property mapping for stiff and soft samples (live cells, proteins, and other biomolecules). AFM is also crucial for measuring single-molecule interaction forces and important parameters of binding dynamics for receptor-ligand interactions or protein-protein interactions on live cells. However, performing AFM measurements and the associated data analytics are tedious, laborious experimental procedures requiring specific skill sets and continuous user supervision. Significant progress has been made recently in artificial intelligence (AI) and deep learning (DL), extending into microscopy. In this review, we summarize how researchers have implemented machine learning approaches so far to improve the performance of atomic force microscopy (AFM), make AFM data analytics faster, and make data measurement procedures high-throughput. We also shed some light on the different application areas of AFM that have significantly benefited from applications of machine learning frameworks and discuss the scope and future possibilities of these crucial approaches.

Design of an FPGA-Based Controller for Fast Scanning Probe Microscopy.

Atomic-scale imaging using scanning probe microscopy is a pivotal method for investigating the morphology and physico-chemical properties of nanostructured surfaces. Time resolution represents a significant limitation of this technique, as typical image acquisition times are on the order of several seconds or even a few minutes, while dynamic processes-such as surface restructuring or particle sintering, to be observed upon external stimuli such as changes in gas atmosphere or electrochemical potential-often occur within timescales shorter than a second. In this article, we present a fully redesigned field programmable gate array (FPGA)-based instrument that can be integrated into most commercially available standard scanning probe microscopes. This instrument not only significantly accelerates the acquisition of atomic-scale images by orders of magnitude but also enables the tracking of moving features such as adatoms, vacancies, or clusters across the surface ("atom tracking") due to the parallel execution of sophisticated control and acquisition algorithms and the fast exchange of data with an external processor. Each of these measurement modes requires a complex series of operations within the FPGA that are explained in detail.

Structure and Defect Identification at Self-Assembled Islands of CO2 Using Scanning Probe Microscopy.

Understanding how carbon dioxide (CO2) behaves and interacts with surfaces is paramount for the development of sensors and materials to attempt CO2 mitigation and catalysis. Here, we combine simultaneous atomic force microscopy (AFM) and scanning tunneling microscopy (STM) using CO-functionalized probes with density functional theory (DFT)-based simulations to gain fundamental insight into the behavior of physisorbed CO2 molecules on a gold(111) surface that also contains one-dimensional metal-organic chains formed by 1,4-phenylene diisocyanide (PDI) bridged by gold (Au) adatoms. We resolve the structure of self-assembled CO2 islands, both confined between the PDI-Au chains as well as free-standing on the surface and reveal a chiral arrangement of CO2 molecules in a windmill-like structure that encloses a standing-up CO2 molecule and other foreign species existing at the surface. We identify these species by the comparison of height-dependent AFM and STM imaging with DFT-calculated images and clarify the origin of the kagome tiling exhibited by this surface system. Our results show the complementarity of AFM and STM using functionalized probes and their potential, when combined with DFT, to explore greenhouse gas molecules at surface-supported model systems.

Theoretical study on the effect of temperature gradient on contact-free scanning for scanning ion conductance microscopy

Scanning ion-conductance microscopy (SICM) is a non-contact, high-resolution, and in-situ scanning probe microscope technique, it can be operated in probing the physical and chemical properties of biological samples such as living cells. Recently, using SICM to study the effects of microenvironment changes such as temperature changes on response of the biological samples has attracted significant attention. However, in this temperature gradient condition, one of the crucial but still unclear issues is the scanning feedback types and safe threshold. In this paper, a theoretical study of effect of the temperature gradient in electrolyte or sample surface on the SICM safe ion-current threshold is conducted using three-dimensional Poisson-Nernst-Planck, Navier-Stokes and energy equations. Two temperature gradient types, sample surface and two types of pipettes with different ratio of inner and outer radii are included, respectively. The results demonstrate that the local temperature of the electrolyte and then sample surface significantly affect the ion flow, shape of the approach curves and thus safe threshold in SICM pipette probe for contact-free scanning. There is a current-increased and decreased phases for approaching the surface with higher temperature and two current-decreased phases for surface with lower temperature. Based on this shape feature of approach curves, the change rate of current is analysis to illustrate the possibility for contact-free scanning of slope object. The results indicate that with the decrease of the normalized tip-surface distance, the coupling effect of large slope angle and local high temperature makes the increase in change rate of ion current not significant and then it challenging to realize contact-free scanning especially for higher surface temperature.

Optimization of Zn-Cr proportions for hybrid multilayer electroplating of AISI 1045 steel – towards super-hydrophobicity and anti-corrosive nature

Localized corrosion in steel heat exchangers is a major concern, occurring mostly during operational shutdowns. Due to the absence of flow and moisture content availability, corrosion reduces operation efficiency. A study aimed to optimize the proportions of Zinc and Chromium (Zn-Cr) for developing a hybrid multi-layer electroplating method to inhibit corrosion in hypo-eutectoid carbon steel commonly used in heat exchangers. The Zn-Cr coating was performed using the amperometric method in an electrochemical workstation, producing coatings of varying thicknesses by varying the potential and time. The surface morphology was characterized using Scanning Electron Microscopy (SEM) and X-ray Diffraction (XRD) analysis. The average thickness of the Zn-Cr coating was found to be 2.5 µm using the scanning probe microscope analysis. The corrosive action of a standard 3.5% NaCl solution was investigated on both coated and uncoated specimens through open circuit potential measurement and electrochemical impedance spectroscopy. The results indicated that the Zn-Cr coating effectively resisted corrosion. Contact angle measurement of water particles with the Zn-Cr coated specimen revealed a near-super hydrophobic nature with the highest contact angle of 146.8°.

Physical phenomena during nanoindentation deformation of amorphous glassy polymers

We identify for visco-elasto-plastic (VEP) glassy polymers, physical phenomena during Berkovich nanoindentation, a locally imposed deformation. Live visuals via in situ nanoindentation indicate mainly sink-in during loading, with pile-up after unloading. Scanning Probe Microscopy (SPM) indicates significant volume conserving upflow below the tip, for these high ν, compliant materials, with compliance correlated high geometric fractional contact, hcΔhmΔ∼0.86−0.95. We adapt the ideal conical indentation framework to VEP Berkovich nanoindentation, to calculate the contact area and visually depict the upflow and the displacement paths, in the material. The combination of SPM and P−h data, indicates a mixed comparison with uniaxial modulus and yield stress, with conventionally defined hardness, H<3σy, and nanoindentation modulus, EN>E. By rationally removing viscoelastic (VE) effects from the loading P−h data, we find instant, zero-time hardness HL0>3σy. We apply the power law model to only the recovery onset, to estimate pure elastic recovery. We then deconvolute the VEP nanoindentation into the conventional EP (elasto-plastic) and elastic contributions, isolating the VE component. Constraint-induced sink-in, pile-up and VE recovery of the highly yielded tip-apex region, mirror the converse constrained deformation effects, governing the trends in the conventional EP EN and HL0 estimates for glassy polymers.

Quantitative photocurrent scanning probe microscopy on PbS quantum dot monolayers.

Photoconductive atomic force microscopy can probe monolayers of PbS/perovskite quantum dots (QDs) with a contact area of 1-3 QDs in stable and reproducible acquisition conditions for I/V curves and photocurrent maps. From the measurements, quantitative values for the barrier height, built-in voltage, diffusion constant and ideality factor are deduced with high precision. The data analysis is based on modelling a superposition of the drift current of the photo-excited charges and a diffusion current across the interface barriers, providing physical insight into the underlying processes. Besides looking into PbS/perovskite on an indium tin oxide substrate, it is shown how the photocurrent is modified by changing either the QD ligand (to thiocyanate) or the substrate (to micro- and nanostructured gold). The dependence of the photocurrent on the light irradiance is found to follow a power law with an exponent of 0.64. Generally, quantitative measurements with high spatial resolution (on the single QD level) can provide significant insight into the processes in nanostructured hybrid optoelectronic components.

Chirality Detection in Scanning Tunneling Microscopy Data Using Artificial Intelligence.

Enantiospecific effects play an uprising role in chemistry and technical applications. Chiral molecular networks formed by self-assembly processes at surfaces can be imaged by scanning probe microscopy (SPM). Low contrast and high noise in the topography map often interfere with the automatic image analysis using classical methods. The long SPM image acquisition times restrain Artificial Intelligence-based methods requiring large training sets, leaving only tedious manual work, inducing human-dependent errors and biased labeling. By generating realistic looking synthetic images, the acquisition of real datasets is avoided. Two state-of-the-art object detection architectures are trained to localize and classify chiral unit-cells in a regular molecular chiral network formed by self-assembly of linear molecular bricks. The comparison of different architectures and datasets demonstrates that the training on purely synthetic data outperforms models trained using augmented datasets. A Faster R-CNN model trained solely on synthetic data achieved an excellent mean average precision of 99% on real data. Hence this approach and the transfer to real data show high success, also highlighting the high robustness against experimental noise and different zoom levels across the full experimentally reasonable parameter range. The generalizability of this idea is demonstrated by achieving equally high performance on a different structure,too.

Enhancement of therapeutic efficacy of Brinzolamide for Glaucoma by nanocrystallization and tyloxapol addition

BackgroundBrinzolamide (BRI) suspensions are used for the treatment of glaucoma; however, sufficient drug delivery to the target tissue after eye drop administration is hampered by poor solubility. To address this issue, we focused on nanocrystal technology, which is expected to improve the bioavailability of poor-solubility drugs, and investigated the effect of BRI nanocrystal formulations on corneal permeability and intraocular pressure (IOP)-reducing effect.MethodsBRI nanocrystal formulations were prepared by the wet-milling method with beads and additives. The particle size was measured by NANOSIGHT LM10, and the morphology was determined using a scanning probe microscope (SPM-9700) and a scanning electron microscope (SEM). Corneal permeability was evaluated in vitro using a Franz diffusion cell with rat corneas and in vivo using rabbits, and the IOP-reducing effect was investigated using a rabbit hypertensive model.ResultsThe particle size range for prepared BRI nanocrystal formulation was from 50 to 300 nm and the mean particle size was 135 ± 4 nm. The morphology was crystalline, and the nanoparticles were uniformly dispersed. In the corneal permeability study, BRI nanocrystallization exhibited higher corneal permeability than non-milled formulations. This result may be attributed to the increased solubility of BRI by nanocrystallization and the induction of energy-dependent endocytosis by the attachment of BRI nanoparticles to the cell membrane. Furthermore, the addition of tyloxapol to BRI nanocrystal formulation further improved the intraocular penetration of BRI and showed a stronger IOP-reducing effect than the commercial product.ConclusionsThe combination of BRI nanocrystallization and tyloxapol is expected to be highly effective in glaucoma treatment and a useful tool for new ophthalmic drug delivery.