In recent years, there has been a remarkable progress in research methods in thin film and surface physics. The spread of research methods is not only in the traditional categories of theory and experiment, but also in the new category of digital transformation (DX). In this special issue, the world's most advanced researchers in these three categories explain their methods in an easy-to-understand manner. We hope you will find the articles in this special issue useful for your research.

Automation of synchrotron radiation powder diffraction experiments at SPring-8 is described, focusing on the BL02B2 powder diffractometer and the BL13XU high-resolution instrument. The development of automation, including data acquisition, sample exchange, and instrument switching, has greatly improved experimental efficiency ; the integration of the MYTHEN detector and automated systems for temperature control, sample preparation, and gas handling has improved measurement speed and accuracy. These developments enable high-throughput, in-situ, and operando measurements that support further materials innovation and facilitate the application of data-driven analysis to large experimental data sets.

X-ray Photoelectron Spectroscopy (XPS) is widely used to investigate the chemical composition and electronic states of surfaces in thin films, particularly in semiconductor applications where non-destructive, fast, and multidimensional analysis is increasingly needed. However, the growing complexity of surface structures and experimental conditions generates large amounts of spectral data, requiring more efficient processing techniques. In this study, we present a novel approach that combines high-speed processing of multidimensional XPS big data with the Noise2Noise denoising technique using deep learning. This integration enables the extraction of highly accurate parameters from noisy spectra, providing a powerful tool for visualizing spatiotemporal data and enhancing precision in surface analysis.

In recent years, the automation of materials research has become a crucial challenge. Powder X-ray diffraction (PXRD) is essential for characterizing material properties, but current methods face issues with reproducibility and efficiency. To address this, we have developed an autonomous experimental system using robotics and machine learning. This article introduces the configuration and workflow of the developed system. Additionally, we discuss the performance evaluation of this system and compare it with conventional manual experiments.

The van der Waals density functional is a method that can describe the dispersion forces within the density functional theory framework in a nonempirical fashion. This article provides a brief overview of the van der Waals density functional and its applications to the problems relevant to surfaces and interfaces. Recent progress of the method is also discussed.

The energy conversion processes occurring at solid-liquid interfaces play a critical role in the performance in rechargeable batteries, solar cells, fuel cells, and catalysts. However, the buried nature of these interfaces and the need for high spatial resolution in analysis have historically hindered a detailed understanding, often leaving discussions reliant on speculation. Recent advancements in surface and interface sciences techniques have enabled the investigation of physical properties and reaction mechanisms at these interfaces. This paper highlights significant findings from such advancements, with a focus on the electrode/electrolyte interface in rechargeable batteries. Using single crystal of LiCoO_x as a model electrode, scanning tunneling microscopy (STM) and first-principles calculations revealed that the arrangement of Li vacancies influences the electronic conductivity, introducing a novel perspective on electrode performance. Furthermore, advanced techniques such as frequency-modulated atomic force microscopy (FM-AFM) and in-situ X-ray and neutron analysis have elucidated the structural and electronic state changes occurring during charge and discharge cycles. The research also will explore new battery systems, including fluoride shuttle batteries, which offer unique advantages such as multivalent electron reactions and high energy density. Additionally, This review introduces cutting-edge methods for evaluating interface properties like viscosity, temperature effects, and humidity influences, with implications for understanding and optimizing interfacial reactions. These findings underscore the potential of surface and interface science techniques to unveil critical insights into energy materials, paving the way for the design of high-performance devices in the future.

Total-reflection high-energy positron diffraction (TRHEPD) is a positron version of reflection high-energy electron diffraction (RHEED). Due to the electrostatic repulsion between the positive charge of the positron and the crystal potential of the material, the penetration depth of the incident positron beam is limited to a few layers of the material surface. In particular, total reflection occurs at low grazing incidence and the penetration depth is less than about 1 Å, which corresponds to the thickness of one atomic layer. Therefore, TRHEPD is useful for the structure determination of material surfaces and two-dimensional materials. In this paper, we report recent results of structure determination using TRHEPD (intercalated graphene and graphene quasicrystals), together with the characteristics of the TRHEPD technique.

Low-energy electron microscopy (LEEM) is a powerful tool for investigating the structures of 2D materials at the nanoscale. In this paper, following a review of structural information obtained from LEEM characterizations, the growth of hexagonal boron nitride (hBN) and its heterostructures with graphene is investigated in detail using LEEM. We have demonstrated that unidirectional hBN islands grow on inclined Cu(101) surfaces, and that the orientation of these islands changes in response to the orientation of steps on the vicinal Cu(101) surface. This indicates that the Cu substrate steps play a key role in determining the orientation of hBN. Additionally, we have successfully controlled the growth of both lateral and vertical heterostructures of graphene and hBN on Cu substrates by adjusting the supply sequence of their precursors.