In recent years, atomic resolution imaging of two-dimensional (2D) materials using scanning transmission electron microscopy (STEM) has become routine. Individual dopant atoms in 2D materials can be located and identified using their contrast in annular dark-field (ADF) STEM. However, in order to understand the effect of these dopant atoms on the host material, there is now the need to locate and quantify them on a larger scale. In this work, we analyze STEM images of MoS2 monolayers that have been ion-implanted with chromium at ultra-low energies. We use functions from the open-source TEMUL Toolkit to create and refine an atomic model of an experimental image based on the positions and intensities of the atomic columns in the image. We then use the refined model to determine the likely composition of each atomic site. Surface contamination stemming from the sample preparation of 2D materials can prevent accurate quantitative identification of individual atoms. We disregard atomic sites from regions of the image with hydrocarbon surface contamination to demonstrate that images acquired using contaminated samples can give significant atom statistics from their clean regions, and can be used to calculate the retention rate of the implanted ions within the host lattice. We find that some of the implanted chromium ions have been successfully integrated into the MoS2 lattice, with 4.1% of molybdenum atoms in the transition metal sublattice replaced with chromium.

The exotic internal structure of polar topologies in multiferroic materials offers a rich landscape for materials science research. As the spatial scale of these entities is often subatomic in nature, aberration-corrected transmission electron microscopy (TEM) is the ideal characterization technique. Software to quantify and visualize the slight shifts in atomic placement within unit cells is of paramount importance due to the now routine acquisition of images at such resolution. In the previous ~decade since the commercialization of aberration-corrected TEM, many research groups have written their own code to visualize these polar entities. More recently, open-access Python packages have been developed for the purpose of TEM atomic position quantification. Building on these packages, we introduce the TEMUL Toolkit: a Python package for analysis and visualization of atomic resolution images. Here, we focus specifically on the TopoTEM module of the toolkit where we show an easy to follow, streamlined version of calculating the atomic displacements relative to the surrounding lattice and thus plotting polarization. We hope this toolkit will benefit the rapidly expanding field of topology-based nano-electronic and quantum materials research, and we invite the electron microscopy community to contribute to this open-access project.

The digital twin concept has developed as a method for extracting value from data, and is being developed as a new technique for the design and asset management of high-value engineering systems such as aircraft, energy generating plant, and wind turbines. In terms of implementation, many proprietary digital twin software solutions have been marketed in this domain. In contrast, this paper describes a recently released open-source software framework for digital twins, which provides a browser-based operational platform using Python and Flask. The new platform is intended to maximize connectivity between users and data obtained from the physical twin. This paper describes how this type of digital twin operational platform (DTOP) can be used to connect the physical twin and other Internet-of-Things devices to both users and cloud computing services. The current release of the software—DTOP-Cristallo—uses the example of a three-storey structure as the engineering asset to be managed. Within DTOP-Cristallo, specific engineering software tools have been developed for use in the digital twin, and these are used to demonstrate the concept. At this stage, the framework presented is a prototype. However, the potential for open-source digital twin software using network connectivity is a very large area for future research and development.

Scanning transmission electron microscopy (STEM) is an extremely versatile method for studying materials on the atomic scale. Many STEM experiments are supported or validated with electron scattering simulations. However, using the conventional multislice algorithm to perform these simulations can require extremely large calculation times, particularly for experiments with millions of probe positions as each probe position must be simulated independently. Recently, the plane-wave reciprocal-space interpolated scattering matrix (PRISM) algorithm was developed to reduce calculation times for large STEM simulations. Here, we introduce a new method for STEM simulation: partitioning of the STEM probe into “beamlets,” given by a natural neighbor interpolation of the parent beams. This idea is compatible with PRISM simulations and can lead to even larger improvements in simulation time, as well requiring significantly less computer random access memory (RAM). We have performed various simulations to demonstrate the advantages and disadvantages of partitioned PRISM STEM simulations. We find that this new algorithm is particularly useful for 4D-STEM simulations of large fields of view. We also provide a reference implementation of the multislice, PRISM, and partitioned PRISM algorithms.

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

The ‘open approach’ is rooted in the open-source and free-software movements. Its application has spread to more fields than computer engineering. Product design is impacted as well: we observe new stakeholders and practices challenging current structured design processes and leading to industrial successes. Open-design appears to be promising yet disruptive. Moreover, its distinctive features remain unclear.

This paper aims to popularize this new concept, as well as to give both researchers and practitioners an overview of current research on open-design, and its consequences on design. For this, we conducted a systematic quantitative bibliometric analysis of 624 entries corresponding to the keyword ‘open-design’ in the Scopus database. This supports a qualitative synthesis of scientific literature, enabling us to summarize practices falling under the umbrella term ‘open-design’. As such, this paper traces the evolution of product design and the open approach. It also analyzes the impact of open-design on the design process as presented in the scientific literature. Finally, this paper develops a typology of open-design of tangible artifacts that distinguishes among three currently reported varieties of practice: do-it-yourself, meta-design, and industrial ecosystems. As the major contribution of this paper, this typology is developed as a final discussion.

Open science is a new concept for the practice of experimental laboratory-based research, such as drug discovery. The authors have recently gained experience in how to run such projects and here describe some straightforward steps others may wish to take towards more openness in their own research programmes. Existing and inexpensive online tools can solve many challenges, while some psychological barriers to the free sharing of all data and ideas are more substantial.

Objectives: The aim of this study was to examine open-source electronic health record (EHR) software to determine their level of functionalities according to the International Organization for Standardization (ISO) standards.

Methods: ISO standards were used as a guideline to determine and describe the reference architecture and functionalities of a standard electronic health record system as well the environmental context for which the software has been built. Twelve open-source EHR systems were selected and evaluated according to two-dimensional criteria based on ISO/TS 18308:2004 functional requirements and ISO/TR 20514:2005 context of the EHR system.

Results: Open EHR software programs mostly fulfill structural, procedural, evolutional, and medicolegal requirements at the minimal and full functionality levels. Communication, privacy, and security requirements are accomplished in less than 23 percent of the cases, mainly at minimal functional level. Ethical, cultural, and consumer requirements still need to be fulfilled by free and open-source EHR applications.

Conclusions: Most analyzed systems had several functional limitations. Nevertheless, especially for clinicians and decision makers in developing countries, open-source EHR systems are an option. The limited functionalities are likely to become requirements for further releases of open-source EHR systems.