Journal of microscopy最新文献

Optical microscopy is an indispensable tool in life sciences research, but conventional techniques require compromises between imaging parameters like speed, resolution, field of view and phototoxicity. To overcome these limitations, data-driven microscopes incorporate feedback loops between data acquisition and analysis. This review overviews how machine learning enables automated image analysis to optimise microscopy in real time. We first introduce key data-driven microscopy concepts and machine learning methods relevant to microscopy image analysis. Subsequently, we highlight pioneering works and recent advances in integrating machine learning into microscopy acquisition workflows, including optimising illumination, switching modalities and acquisition rates, and triggering targeted experiments. We then discuss the remaining challenges and future outlook. Overall, intelligent microscopes that can sense, analyse and adapt promise to transform optical imaging by opening new experimental possibilities.

This paper reports on the development of an open-source image analysis software ‘pipeline’ dedicated to petrographic microscopy. Using conventional rock thin sections and images from a standard polarising microscope, the pipeline can classify minerals and subgrains into objects and obtain information about optic-axis orientation. Five metamorphic rocks were chosen to test and illustrate the method. Thin sections were imaged using reflected and cross- and plane-polarised transmitted light. Images were taken at different angles of the polariser and analyser (360° with 10° steps), both with and without the full-lambda plate. The resulting image stacks were analysed with a modular pipeline for optic-axis mapping (POAM). POAM consists of external and internal software packages that register, segment, classify, and interpret the visible light spectra using object-based image analysis (OBIAS). The mapped fields-of-view and grain orientation stereonets of interest are presented in the context of whole-slide images.

Two innovations are reported. First, we used hierarchical tree region merging on blended multimodal images to classify individual grains of rock-forming minerals into objects. Second, we assembled a new optical mineralogy algorithm chain that identifies the mineral slow axis orientation. The c-axis orientation results were verified with scanning electron microscopy electron backscattered diffraction (SEM-EBSD) data. For quartz (uniaxial) in a granite mylonite the test yielded excellent correspondence of c-axis azimuth and good agreement for inclination. For orthorhombic orthopyroxene in a deformed garnet harzburgite, POAM produced acceptable results for slow axis azimuth. In addition, the method identified slight anisotropy in garnet that would not be appreciated by traditional microscopy.

We propose that our method is ideally suited for two commonly performed tasks in mineralogy. First, for mineral grain classification of entire thin sections scans on blended images to provide automated modal abundance estimates and grain size distribution. Second, for prospective fields of view of interest, POAM can rapidly generate slow axis crystal orientation maps from multiangle image stacks on conventionally prepared thin sections for targeting detailed SEM-EBSD studies.

Super sulphated cement (SSC) is a very promising substitute for traditional construction materials (i.e. Portland cement), due to its enhanced durability and particularly low environmental impact. This paper explores the microstructure and certain properties of SSC, focusing on the particular complexities of its microstructure and the difficulties of microanalysis of its hydrates. To do so, SSC paste samples were first cast to identify hydration products using X-ray diffraction, then observed at early age using confocal laser scanning microscopy (CLSM) and at early and late age using scanning electron microscopy. In addition, concrete cores impregnated with fluorescein in order to highlight porosity, cracking and aggregates debonding were observed under UV light using optical microscopy (OM), showing a complete absence of cracking and aggregate debonding. Both microscopy techniques (CLSM and UV light OM) have been applied to this type of binder for the first time. The results show that SSC microstructure is characterised by a sophisticated intergrowth of various phases, including ettringite and amorphous calcium-(alumina)-silicate hydrate gels. Finally, Monte–Carlo simulation of electron-matter has been provided for a better understanding of EDS analysis.

Nowadays, the use of super-resolution microscopy (SRM) is increasing globally due to its potential application in several fields of life sciences. However, a detailed and comprehensive guide is necessary for understanding a single-frame image's resolution limit. This study was performed to provide information about the structural organisation of isolated cellulose fibres from garlic and agave wastes through fluorophore-based techniques and image analysis algorithms. Confocal microscopy provided overall information on the cellulose fibres’ microstructure, while techniques such as total internal reflection fluorescence microscopy facilitated the study of the plant fibres’ surface structures at a sub-micrometric scale. Furthermore, SIM and single-molecule localisation microscopy (SMLM) using the PALM reconstruction wizard can resolve the network of cellulose fibres at the nanometric level. In contrast, the mean shift super-resolution (MSSR) algorithm successfully determined nanometric structures from confocal microscopy images. Atomic force microscopy was used as a microscopy technique for measuring the size of the fibres. Similar fibre sizes to those evaluated with SIM and SMLM were found using the MSSR algorithm and AFM. However, the MSSR algorithm must be cautiously applied because the selection of thresholding parameters still depends on human visual perception. Therefore, this contribution provides a comparative study of SRM techniques and MSSR algorithm using cellulose fibres as reference material to evaluate the performance of a mathematical algorithm for image processing of bioimages at a nanometric scale. In addition, this work could act as a simple guide for improving the lateral resolution of single-frame fluorescence bioimages when SRM facilities are unavailable.

Long-term placement of facial implants requires avoiding the formation of fibrous tissue capsules around the artificial material by creating osteoconductive properties of the surface. Most promising approach is the deposition coatings made of materials very similar to bone mineral components, that is, calcium phosphates such as hydroxyapatite (HAp). As part of the research work, an innovative, cost-effective atmospheric pressure plasma deposition (APPD) system was used as a low-temperature coating technology for generating the HAp coatings deposition. Full microstructural characterisation of the coatings using SEM and TEM techniques was carried out in the work. It has been shown that the fully crystalline HAp powder undergoes a transformation during the coatings deposition and the material had a quasi-sintered structure after deposition. The crystalline phase content increased at the coating/substrate interface, while the surface of the HAp was amorphous. This is a very beneficial phenomenon due to the process of bioresorption. The amorphous phase undergoes much faster biodegradation than the crystalline one. In order to increase the bioactivity of the HAp, Zn particles were introduced on the surface of the coating. The TEM microstructural analysis in conjunction with the qualitative analysis of the EDS chemical composition showed that the binding of the Zn particles within the HAp matrix had diffusive character, which is very favourable from the point of view of the quality of the adhesion and the bioactivity of the coating. In the case of such a complex structure and due to its very porous nature, micromechanical analysis was carried out in situ in SEM, that is, by microhardness measurements of both the HAp matrix and the Zn particle. It was shown that the average value of HAp microhardness was 4.395 GPa ± 0.08, while the average value of Zn microhardness was 1.142 GPa ± 0.02

C₄AF is considered the least reactive main clinker phase, but its reactivity may be affected by adding supplementary cementitious materials (SCMs). Pure C₄AF was synthesised in a laboratory furnace, and the role of silica fume without gypsum on its early hydration properties was monitored. Burning was carried out in four stages to achieve 99% purity of C₄AF. Heat flow development was monitored by isothermal calorimetry over 7 days of hydration at 20°C and 40°C. The role of silica fume on hydrogarnet phase katoite (Ca₃Al₂(SiO₄)_{3 – x}(OH)_4x x = 1.5–3) formation during early hydration was studied. Rapid dissolution of C₄AF, formation of metastable C-(A,F)-H and its conversion to C₃(A, F)H₆ was evidenced by isothermal calorimetry as a large exotherm. Changes in microstructure during early hydration were documented by SE micrographs, EDS point analyses, X-ray mapping and line scans by SEM-EDS. The phase composition was characterised by DTA-TGA and QXRD after 7 days of hydration. The katoite diffraction pattern is similar for the reference sample and sample with silica fume, but substitution in its structure can be revealed by X-ray microanalyses. The composition of katoite is variable due to the various extent of substitution of 4OH⁻ by SiO₄⁴⁻ due to silica fume.

To accurately simulate the hydration process of cementitious materials, understanding the growth rate of C-S-H layers around clinker grains is crucial. Nonetheless, the thickness of the hydrate layer shows substantial variation around individual grains, depending on their surrounding. Consequently, it is not feasible to measure hydrate layers manually in a reliable and reproducible manner. To address this challenge, a software has been developed to statistically determine the C-S-H thickness, requiring minimal manual interventions for thresholding and for setting limits like particle size or circularity.

This study presents a tool, which automatically identifies suitable clinker grains and and perform statistical measurements of their hydrate layer up to a specimen age of 28 days. The findings reveal a significant increase in the C-S-H layer, starting from 0.45 $��\mu �m�$ after 1 day and reaching 3.04 $��\mu �m�$ after 28 days. However, for older specimens, the measurement of the C-S-H layer was not feasible due to limited pore space and clinker grains.

The fracture behaviour of concrete is studied in various micro- and macro-damage models. This is important for estimating serviceability and stability of concrete structures. However, a detailed understanding of the material behaviour under load is often not available. In order to better interpret the fracture behaviour and pattern, images of lightweight concrete were taken using a high-resolution computed tomography (μ-CT) scanner. The samples were loaded between the taken images and the load was kept constant during the measurement. This study describes the method used and how the data set was analysed to investigate displacements and cracks. It has been shown that displacements and damage to the concrete structure can be detected prior to failure, allowing conclusions to be drawn about the structural behaviour. In principle, the μ-CT measurement can be used to examine different kinds of concrete as well as other systems with inorganic binders and to compare the fracture behaviour of different systems.

The accelerating pace of technological advancements necessitates specialised expertise and cutting-edge instruments to maintain competitive research in life sciences. Core facilities – collaborative laboratories equipped with state-of-the-art tools and staffed by expert personnel – are vital resources that support diverse scientific endeavours. However, their adoption in lower-income communities has been comparatively stagnant due to both financial and cultural challenges. This paper explores the perils of not supporting core facilities on national research enterprises, underscoring the need for balanced investments in discovery science and crucial infrastructure support. We explore the implications from the perspectives of funders, university leaders and lab heads. We advocate for a paradigm shift to recognise these facilities as essential components of national research efforts. Core facilities are positioned not as optional but as strategic investments that can catalyse breakthroughs, particularly in environments with limited resources.

Atomic electric fields in a thin GaN sample are measured with the centre-of-mass approach in 4D-scanning transmission electron microscopy (4D-STEM) using a 12-segmented STEM detector in a Spectra 300 microscope. The electric fields, charge density and potential are compared to simulations and an experimental measurement using a pixelated 4D-STEM detector. The segmented detector benefits from a high recording speed, which enables measurements at low radiation doses. However, there is measurement uncertainty due to the limited number of segments analysed in this study.