Microscopy Imaging Techniques Research Articles

MICROSCOPIC METHOD TO VERIFY THE EFFICIENCY OF REMOVAL OF ORGANIC POLLUTANTS FROM MICROPLASTIC SURFACES

The purification of microplastic samples is a crucial step in environmental research, aiming to remove contaminants and ensure accurate analysis. This study explores various methods for purifying microplastics, focusing on the removal of organic contaminants, specifically fulvic acids. Comparative analysis using microscopic imaging techniques was conducted to evaluate the effectiveness of these methods. The results highlight the complexities involved in microplastic purification and the challenges associated with different approaches. While some methods showed promising outcomes, such as the sonification method, it was also observed that they could potentially alter the microplastic structure. Additionally, the limitations and potential interferences of other purification methods, such as Fenton's solution, were identified. This study underscores the importance of selecting purification methods that minimize negative impacts on microplastics and ensure reliable analysis. Further research is needed to optimize purification techniques and fully understand their effects on microplastic integrity. This research contributes to the broader goal of developing robust methodologies for microplastic analysis in environmental studies.

Fluorescence microscopy imaging of mitochondrial metabolism in cancer cells.

Mitochondrial metabolism is an important contributor to cancer cell survival and proliferation that coexists with enhanced glycolytic activity. Measuring mitochondrial activity is useful to characterize cancer metabolism patterns, to identify metabolic vulnerabilities and to identify new drug targets. Optical imaging, especially fluorescent microscopy, is one of the most valuable tools for studying mitochondrial bioenergetics because it provides semiquantitative and quantitative readouts as well as spatiotemporal resolution of mitochondrial metabolism. This review aims to acquaint the reader with microscopy imaging techniques currently used to determine mitochondrial membrane potential (ΔΨm), nicotinamide adenine dinucleotide (NADH), ATP and reactive oxygen species (ROS) that are major readouts of mitochondrial metabolism. We describe features, advantages, and limitations of the most used fluorescence imaging modalities: widefield, confocal and multiphoton microscopy, and fluorescent lifetime imaging (FLIM). We also discus relevant aspects of image processing. We briefly describe the role and production of NADH, NADHP, flavins and various ROS including superoxide and hydrogen peroxide and discuss how these parameters can be analyzed by fluorescent microscopy. We also explain the importance, value, and limitations of label-free autofluorescence imaging of NAD(P)H and FAD. Practical hints for the use of fluorescent probes and newly developed sensors for imaging ΔΨm, ATP and ROS are described. Overall, we provide updated information about the use of microscopy to study cancer metabolism that will be of interest to all investigators regardless of their level of expertise in the field.

Use of diformyl‐triazolo Schiff base for Zn2+ sensing and intracellular live cell imaging

A diformylphenol Schiff base of triazole‐amine, 4‐methyl‐2, 6‐bis‐[(1H‐[1,2,4] triazol‐3‐ylimino)‐methyl]‐phenol (PTR) has been synthesised and characterised by spectroscopic data (ESI‐MS, UV‐vis, FT‐IR, NMR spectra). The probe, PTR, emits at 610 nm upon excitation at 380 nm and the emission is strongly intensified on interacting with Zn2+ ion in DMSO‐water (99:1, v/v; HEPES buffer, pH, 7.2) solution even in the presence of 15 other cations (Cu2+, Mn2+, Co2+, Ni2+, Pd2+, Cd2+, Pb2+, Hg2+, Fe3+, Cr3+, Al3+, Na+, K+, Ba2+, Ca2+) and the emission band has been shifted to 530 nm. The limit of detection of Zn2+, 0.30 μM is much lower than WHO recommended value (76 μM). The binding constant (Kd) is 4.2585 × 104 M−1. Selective and sensitive chemosensing behaviour of PTR to Zn2+ has been explained by switching off ESIPT quenching of the keto‐enol tautomerisation of the probe along with the chelation enhancement of fluorescence (CHEF) by binding with Zn2+. The Job's plot and NMR titration have been extended to measure the 1:1 M composition [PTR + Zn2+]. The energy calculation by the DFT computation of keto and enol isomers supports easy tautomerisation and helps ESIPT quenching by proton transfer. Intracellular Zn2+ ions in living cells of HEK293 (PBS: phosphate buffer saline; pH, 7.2) have also been identified by the probe, PTR, using fluorescence microscopic imaging technique.

Robust Local Thickness Estimation of Sub-Micrometer Specimen by 4D-STEM.

A quantitative four-dimensional scanning transmission electron microscopy (4D-STEM) imaging technique (q4STEM) for local thickness estimation across amorphous specimen such as obtained by focused ion beam (FIB)-milling of lamellae for (cryo-)TEM analysis is presented. This study is based on measuring spatially resolved diffraction patterns to obtain the angular distribution of electron scattering, or the ratio of integrated virtual dark and bright field STEM signals, and their quantitative evaluation using Monte Carlo simulations. The method is independent of signal intensity calibrations and only requires knowledge of the detector geometry, which is invariant for a given instrument. This study demonstrates that the method yields robust thickness estimates for sub-micrometer amorphous specimen using both direct detection and light conversion 2D-STEM detectors in a coincident FIB-SEM and a conventional SEM. Due to its facile implementation and minimal dose reauirements, it is anticipated that this method will find applications for in situ thickness monitoring during lamella fabrication of beam-sensitive materials.

Multimodal microscopic imaging with deep learning for highly effective diagnosis of breast cancer

Accurate and rapid diagnosis of breast cancer is particularly important since it becomes the primary malignant tumor threatening women's health. Although pathological diagnosis with H&E staining section is the gold standard in tumor diagnosis, it is hard to meet quick intraoperative inspection because of its complex procedures and hysteresis. This study adopts multimodal microscopic imaging technology (bright-field imaging, auto-fluorescence imaging and orthogonal polarization imaging) combined with deep learning to achieve rapid intelligent diagnosis of breast cancer by getting the rich information of tissue morphology, content and structure of collagen in tissue slices. By using both fusion classification models of multimodal images at pixel level and decision level, the AUC score and accuracy is 0.9366 and 89.01% for the pixel fusion classification, as well as 0.9421 and 87.53% for the decision fusion classification, respectively. The results suggest that the multimodal microscopic imaging technique proposed in this study has unique advantages in accuracy, speed and feasibility in clinic for breast cancer diagnosis, and has strong clinical potential and application prospects when combined with deep learning.

Deep learning-enhanced fluorescence microscopy via confocal physical imaging model.

Confocal microscopy is one of the most widely used tools for high-resolution cellular, tissue imaging and industrial inspection. Micrograph reconstruction based on deep learning has become an effective tool for modern microscopy imaging techniques. While most deep learning methods neglect the imaging process mechanism, which requires a lot of work to solve the multi-scale image pairs aliasing problem. We show that these limitations can be mitigated via an image degradation model based on Richards-Wolf vectorial diffraction integral and confocal imaging theory. The low-resolution images required for network training are generated by model degradation from their high-resolution counterparts, thereby eliminating the need for accurate image alignment. The image degradation model ensures the generalization and fidelity of the confocal images. By combining the residual neural network with a lightweight feature attention module with degradation model of confocal microscopy ensures high fidelity and generalization. Experiments on different measured data report that compared with the two deconvolution algorithms, non-negative least squares algorithm and Richardson-Lucy algorithm, the structural similarity index between the network output image and the real image reaches a high level above 0.82, and the peak signal-to-noise ratio can be improved by more than 0.6 dB. It also shows good applicability in different deep learning networks.

Preferential substitution at cationic sites in 9-4-9 Zintl phase Ca9− yEuyZn4.5+ δ Sb9

Ca9Zn4.5Sb9 Zintl compound is one of the promising thermoelectric materials with excellent performance, which can be further improved by Eu alloying. In this work, a series of Ca9−yEuyZn4.5+δSb9 compounds is investigated by using the advanced Cs-corrected high-angle annular dark field scanning transmission electron microscope (HAADF-STEM) imaging technique at an atomic level. The HAADF-STEM images show that alloying Eu will lead to preferential substitution of Eu atoms at Ca(1) and Ca(5) sites. The further structural analysis and first-principles density functional theory calculation elucidate the origin that the Eu atoms are prone to replace Ca(1) and Ca(5) sites in Ca9−yEuyZn4.5+δSb9. The preferential substitutions may provide a new insight into revealing the structural transformation commonly found in Zintl phase thermoelectric materials.

A data-driven framework for permeability prediction of natural porous rocks via microstructural characterization and pore-scale simulation.

Understanding the microstructure-property relationships of porous media is of great practical significance, based on which macroscopic physical properties can be directly derived from measurable microstructural informatics. However, establishing reliable microstructure-property mappings in an explicit manner is difficult, due to the intricacy, stochasticity, and heterogeneity of porous microstructures. In this paper, a data-driven computationalframework is presented to investigate the inherent microstructure-permeability linkage for natural porous rocks, where multiple techniques are integrated together, including microscopy imaging, stochastic reconstruction, microstructural characterization, pore-scale simulation, feature selection, and data-driven modeling. A large number of 3D digital rocks with a wide porosity range are acquired from microscopy imaging and stochastic reconstruction techniques. A broad variety of morphological descriptors are used to quantitatively characterize pore microstructures from different perspectives, and they compose the raw feature pool for feature selection. High-fidelity lattice Boltzmann simulations are conducted to resolve fluid flow passing through porous media, from which reliable permeability references are obtained. The optimal feature set that best represents permeability is identified through a performance-oriented feature selection process, upon which a cost-effective surrogate model is rapidly fitted to approximate the microstructure-permeability mapping via data-driven modeling. This surrogate model exhibits great advantages over empirical/analytical formulas in terms of prediction accuracy and generalization capacity, which can predict reliable permeability values spanning four orders of magnitude. Besides, feature selection also greatly enhances the interpretability of the data-driven prediction model, from which new insights into the mechanism of how microstructural characteristics determine intrinsic permeability are obtained.

Analysis of burr formation in finish machining of nickel-based superalloy with worn tools using micro-scale in-situ techniques

The formation of burrs is among the most significant factors affecting quality and productivity in machining. Burrs are a negative byproduct of machining processes that are difficult to avoid because of a limited understanding of the complex burr formation mechanisms in relation to cutting conditions, including both process parameters and tool condition. Thus, the objective of this work was to characterize burr formation under finish machining conditions via a high-speed, high-resolution in-situ experimental method. Various parameters pertaining to burr geometry such as height, thickness, and initial negative shear angle were measured both during and after cutting. Results showed that varying the conditions of uncut chip thickness, tool-wear, and cutting speed all have a significant effect on burr formation, although certain burr metrics were found to be insensitive with respect to different process conditions because the difference was statistically insignificant. This study provides new insights into the relationships between the workpiece material's microstructure, machining parameters, and tool condition on both crack formation and propagation/plasticity during burr formation. Using digital image correlation (DIC) and a physics-based process model not previously utilized for burr formation analysis, the displacement and corresponding flow stress were calculated at the exit burr root location. This novel semi-analytical approach revealed that the normalized stress at the exit burr root was approximately equal to the flow stress for a variety of different conditions, indicating the potential for model-based prediction of burr formation mechanics. Finally, this study investigates factors that influence fracture evolution during exit burr formation. It was found that negative exit burrs are a direct result of high strain rate and high uncut chip thickness, which was expected, but also a microstructural size effect and a tool-wear effect, neither of which have been previously reported. By harnessing ultra-high-speed imaging and advanced optical microscopy techniques, this manuscript deals with the fundamentals of burr formation, including new insights into material response at the grain-scale to the loads imposed with both sharp and worn tools.

Atomic Insights into the Cu Species Supported on Zeolite for Direct Oxidation of Methane to Methanol via Low-Damage HAADF-STEM.

Precise determination of the structure-property relationship of zeolite-based metal catalysts is critical for the development toward practical applications. However, the scarcity of real-space imaging of zeolite-based low-atomic-number (LAN) metal materials due to the electron-beam sensitivity of zeolites has led to continuous debates regarding the exact LAN metal configurations. Here, a low-damage high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) imaging technique is employed for direct visualization and determination of LAN metal (Cu) species in ZSM-5 zeolite frameworks. The structures of the Cu species are revealed based on the microscopy evidence and also proved by the complementary spectroscopy results. The correlation between the characteristic Cu size in Cu/ZSM-5 catalysts and their direct oxidation of methane to methanol reaction properties is unveiled. As a result, the mono-Cu species stably anchored by Al pairs inside the zeolite channels are identified as the key structure for higher C1 oxygenates yield and methanol selectivity for direct oxidation of methane. Meanwhile, the local topological flexibility of the rigid zeolite frameworks induced by the Cu agglomeration in the channels is also revealed. This work exemplifies the combination of microscopy imaging and spectroscopy characterization serves as a complete arsenal for revealing structure-property relationships of the supported metal-zeolite catalysts.

Impact of photovoltaic effect on performance enhancement of triboelectric nanogenerator for energy harvesting applications

The photo-induced triboelectric nanogenerator (PTENG) has been explored as new generation energy technology, which is enabled by coupling triboelectric and photo-induced charge carriers. PTENG shows a dual work mechanism that is attributed to the synergetic outcome of the photovoltaic and triboelectric effects. This study aims to provide a new strategy for triboelectric nanogenerator devices to achieve high output performance for various smart electronic device applications. Aluminum and n-type silicon were chosen as two different materials for triboelectric measurements. Different techniques were adopted to obtain triboelectric output parameters through the in-house developed triboelectric setup. AFM and Kelvin probe force microscopy imaging techniques were employed to obtain surface roughness and to measure the change in surface potential under the illumination of red (630 nm) laser light. A significant improvement in surface potential of around 40 mV was observed under laser illumination. Triboelectric characterization has been performed to obtain open circuit voltage (VOC) and short circuit current (ISC) with and without light illumination at different speeds of the motor. VOC and Isc were found to be 0.8 V and 2.2 nA, respectively, at 50 rpm speed without any illumination, which was further enhanced to 1.8 V and 5.5 nA, respectively, under the influence of laser light illumination. An increase in the motor speed to 100 rpm results in higher VOC (2.4 V) and higher ISC (3.4 nA) as compared to 50 rpm at no illuminating condition. However, it enhances to 3.4 V and 6.0 nA in illuminating conditions. This is attributed to the generation of charge carrier due to triboelectrification, which is further enhanced because of the photovoltaic effect wherein the generation of electron-hole pair occurs due to the shining of light on the side of semiconductors. These synergetic effects have tremendous potential in sustainable energy harvesting.

Designing ABC-6 family small pore zeolites by epitaxial growth approach

Aluminosilicate small pore zeolites belonging to ABC-6 family play crucially important roles in the high methanol conversion with the high selectivity of light olefins, gas separation and storage, and selective catalytic reduction of NOx. In this work, we report a general method, called the epitaxial growth approach, for designing ABC-6 family small pore zeolites. It is mainly realized through the epitaxial growth on the nonporous SOD-type zeolite in the presence of inorganic cations (Na+ and K+) combined with a variety of organic structure directing agents (OSDAs). In this case, a series of ABC-6 family small pore zeolites such as ERI-, SWY-, LEV-, AFX-, and PTT-type zeolites have been successfully synthesized within a few hours. More importantly, the advanced focused ion beam (FIB) and the low-dose high-resolution transmission electron microscopy (HRTEM) imaging technique have been utilized for unraveling the zeolite heterojunction at the atomic level during the epitaxial growth process. It turns out (222) crystallographic planes of the SOD-type zeolite substrate provide unique pre-building units, which facilitate the growth of targeted ABC-6 family small pore zeolites along its c-axis. Moreover, the morphologies of ERI-type zeolite can also be tuned through the epitaxial growth approach, achieving a longer lifetime in the methanol conversion.

Spectral Imaging of UV-Blocking Carbon Dot-Based Coatings for Food Packaging Applications

Nowadays, there is an increased demand to develop alternative non-plastic packaging to be used in the food industry. The most popular biodegradable films are cellulose and poly(lactic acid) (PLA); however, there is still the need to increase their UV absorption to protect the packaging content. In this work, we have covered those biodegradable films with thin coatings based on carbon dots (CDs) dispersed in polyvinyl alcohol (PVA) deposited by spin- or spray-coating techniques. We report a strong increase in the UV light-absorbing properties, together with a detailed morphological characterization; moreover, we show the results of a new microscopy and spectral imaging technique applied to the coated samples. The scientific and technological novelty of this approach is the possibility of characterizing large areas of the material surface by the simultaneous detection of PL spectra in all the pixels of a highly spatially-resolved two-dimensional (2D) map of the surface. We report UV-excited PL maps whose detailed information allows us to clearly identify regions with different spectral behaviors and to compare their characteristic signals for different CDs:PVA deposition techniques.

Effect of SiCp on the microstructure and tensile properties of the Mg–3Y magnesium alloy

Magnesium matrix composite is another competitive light metal matrix composite following aluminum matrix composite, with excellent application prospects in the aerospace and automotive fields. In this paper, the Mg - 3Y – xSiCp (x = 0, 1, 3, 5 wt%) composites are fabricated by stir casting with ultrasonic vibration followed by extrusion. The microstructure of the alloys is investigated by means of scanning electron microscopy (SEM) imaging and electron backscatter diffraction (EBSD) techniques. The results reveal that the composites have a finer grain size due to the particle promoted nucleation (PSN) mechanism. When the SiCp content is 3 wt%, the grain size is the smallest (0.76 μm), and the refinement rate is about 16.7%. Moreover, the addition of SiCp can inhibit the transformation from low-angle grain boundaries (LABGs) to high-angle grain boundaries (HABGs), thus hindering the dynamic recrystallization (DRX) of the alloy, which decreases from 55.7% to 15.4%. The reduction in the proportion of recrystallized grains in the composite leads to increasing the maximum intensity of the texture. In addition, the tensile properties and the strengthening mechanism of the alloys are investigated. The results show that the composites have higher ultimate tensile strength (UTS) and yield strength (YS) due to the combination of grain refinement and dislocation strengthening. When the SiCp content is 5 wt%, the UTS (291 MPa) and YS (283 MPa) increase by ∼12.7% and ∼17.1%, respectively, over the matrix alloy. However, the addition of SiCp causes more oxides and holes in the alloys, which leads to a fracture strain (δ) decrease in the composites.

Wavelength-dependent three-dimensional single-molecule superlocalization imaging for yoctomole detection of thyroid-stimulating hormone on a quantum dot nanobiosensor

A wavelength-dependent three-dimensional (3D) superlocalization imaging method on gold nanoislands (GNIs) chip was developed as a supersensitive single-molecule thyroid-stimulating hormone (TSH) nanobiosensor. Scattered and fluorescent signals from gold nanoislands on the substrate and quantum dots (QDs) nanoprobes were simultaneously isolated and acquired within an evanescent field layer generated by total internal reflection (TIR) of incident light using a dual-view device. The 3D TIR fluorescence images of TSH-bound QDs on the GNIs were obtained using z-axis optical sectioning at 10 nm intervals before/after immunoreaction to identify the optimal conditions for detection. The localized centroid position of QD nanoprobes and GNI were distinguished at a subdiffraction limit resolution using 3D Gaussian fitting to the point spread function. The QD TSH nanobiosensor using wavelength-dependent 3D TIR fluorescence-based single-molecule localization microscopy (3D TIRF-SLM) imaging technique showed an excellent detection limit of 90 yoctomoles (∼54 molecules) and a wide linear dynamic range of 1.14 zmol/L − 100 pmol/L for TSH. The detection sensitivity was about 4.4 × 109 times higher than conventional enzyme-linked immunosorbent assay and could successfully quantify TSH in human serum. The wavelength-dependent 3D TIRF-SLM technique may emerge as a reliable platform for ultrahigh-sensitive nanobiosensors at the single-molecule level and early diagnosis with quantification of disease-related ultra-trace biomolecules.

Many Roles of Carbohydrates: A Computational Spotlight on the Coronavirus S Protein Binding.

Glycosylation is one of the post-translational modifications with more than 50% of human proteins being glycosylated. The exact nature and chemical composition of glycans are inaccessible to X-ray or cryo-electron microscopy imaging techniques. Therefore, computational modeling studies and molecular dynamics must be used as a "computational microscope". The spike (S) protein of SARS-CoV-2 is heavily glycosylated, and a few glycans play a more functional role "beyond shielding". In this mini-review, we discuss computational investigations of the roles of specific S-protein and ACE2 glycans in the overall ACE2-S protein binding. We highlight different functions of specific glycans demonstrated in myriad computational models and simulations in the context of the SARS-CoV-2 virus binding to the receptor. We also discuss interactions between glycocalyx and the S protein, which may be utilized to design prophylactic polysaccharide-based therapeutics targeting the S protein. In addition, we underline the recent emergence of coronavirus variants and their impact on the S protein and its glycans.

HCFC-141b hydrate formation with amino acid surfactants: Insights into hydrate formation promotion mechanism

Surfactants are good promoters for hydrate nucleation and growth. The hydrate promoting mechanism study by surfactants is very important for hydrate application technology. Amino acid surfactants (AAS) are environmentally friendly and easily degradable surfactants. Five AAS are used to investigate the influence on hydrate nucleation and growth. HCFC-141b is effectively dispersed in water by AAS. AAS with head group glutamic acid and longer aliphatic acyl chain can effectively promote hydrate formation. Sodium cocoyl glutamate and sodium stearoyl glutamate improve and stabilize hydrate nucleation. The hydrate conversion rate and hydrate cooling storage capacity by adding the optimal mass fraction of sodium cocoyl glutamate or sodium stearoyl glutamate is similar. Hydrate nucleation and growth are studied using microscopic imaging techniques. Hydrate nucleus first appear at the surface of HCFC-141b droplets. Hydrophobic HCFC-141b droplets formed under the help of AAS is the key to improve hydrate nucleation and growth.

In vivo assessment of differences in fungal cell density in cerebral cryptococcomas of mice infected with Cryptococcus neoformans or Cryptococcus gattii

In cerebral cryptococcomas caused by Cryptococcus neoformans or Cryptococcus gattii, the density of fungal cells within lesions can contribute to the overall brain fungal burden. In cultures, cell density is inversely related to the size of the cryptococcal capsule, a dynamic polysaccharide layer surrounding the cell. Methods to investigate cell density or related capsule size within fungal lesions of a living host are currently unavailable, precluding in vivo studies on longitudinal changes. Here, we assessed whether intravital microscopy and quantitative magnetic resonance imaging techniques (diffusion MRI and MR relaxometry) would enable non-invasive investigation of fungal cell density in cerebral cryptococcomas in mice. We compared lesions caused by type strains C. neoformans H99 and C. gattii R265 and evaluated potential relations between observed imaging properties, fungal cell density, total cell and capsule size. The observed inverse correlation between apparent diffusion coefficient and cell density permitted longitudinal investigation of cell density changes. Using these imaging methods, we were able to study the multicellular organization and cell density within brain cryptococcomas in the intact host environment of living mice. Since the MRI techniques are also clinically available, the same approach could be used to assess fungal cell density in brain lesions of patients.

Identification of Supramolecular Structures of Porphyrin Polymer on Single-Walled Carbon Nanotube Surface Using Microscopic Imaging Techniques

Although the supramolecular structure of porphyrin polymers on flat surfaces (i.e., mica and HOPG) has been extensively studied, the self-assembly arrays of porphyrin polymers on the SWNT (as curved nanocarbon surfaces) have yet to be fully identified and/or investigated, especially using microscopic imaging techniques, i.e., scanning tunneling microscopy (STM), atomic force microscopy (AFM), and transmission electron microscopy (TEM). This study reports the identification of the supramolecular structure of poly-[5,15-bis-(3,5-isopentoxyphenyl)-10,20-bis ethynylporphyrinato]-zinc (II) on the SWNT surface using mainly AFM and HR-TEM microscopic imaging techniques. After synthesizing around >900 mer of porphyrin polymer (via Glaser-Hay coupling); the as-prepared porphyrin polymer is then non-covalently adsorbed on SWNT surface. Afterward, the resultant porphyrin/SWNT nanocomposite is then anchored with gold nanoparticles (AuNPs), which are used as a marker, via coordination bonding to produce a porphyrin polymer/AuNPs/SWNT hybrid. The polymer, AuNPs, nanocomposite, and/or nanohybrid are characterized using 1H-NMR, mass spectrometry, UV-visible spectroscopy, AFM, as well as HR-TEM measuring techniques. The self-assembly arrays of porphyrin polymers moieties (marked with AuNPs) prefer to form a coplanar well-ordered, regular, repeated array (rather than wrapping) between neighboring molecules along the polymer chain on the tube surface. This will help with further understanding, designing, and fabricating novel supramolecular architectonics of porphyrin/SWNT-based devices.

Super-Resolution Structured Illumination Microscopy for the Visualization of Interactions between Mitochondria and Lipid Droplets

Visualizing the dynamics of fine structures in cells requires noninvasive, long-duration imaging of the intracellular environment at high spatiotemporal resolution and low background noise. With modularized hardware and polarized laser modulation, we developed a nanoscale super-resolution structured illumination microscope (SR-SIM) imaging technique. Combined with a reliable image reconstruction algorithm and timing synchronization of all devices, the super-resolution (SR) images in hepatocytes reached 134.95 nm spatial resolution and 50 fps temporal resolution. This imaging system was able to maintain the optimal operation state over hundreds of time points due to less exposure and low phototoxicity. In hepatocytes, interactions between mitochondria and lipid droplets (LDs) underpin many crucial physiological processes, ranging from cellular metabolism to signaling. In this study, we pioneered the use of the SIM system for imaging the interaction characteristics between mitochondria and LDs. More than 200 hepatocytes were counted and recorded effectively. We found that LDs in an unstable state were divided under mitochondrial contact and fused without it. Among 200 LDs, more than 69% were surrounded by mitochondria that tended to wrap LDs. The SR-SIM imaging technique was demonstrated to break the limitations of conventional imaging methods in spatial-temporal resolution and imaging duration in the field of the dynamic study between mitochondria and LDs.