Characterization Methods Research Articles

Amphiphilic self-assembling peptides: formulation and elucidation of functional nanostructures for imaging and smart drug delivery.

The rational design of self-assembled peptide-based nanostructures for theranostics applications requires in-depth physicochemical characterization of the peptide nanostructures, to understand the mechanism and the interactions involved in the self-assembly, allowing a better control of the objects' physicochemical and functional properties for theranostic applications. In this work, several complementary characterization methods, such as dynamic light scattering, transmission electron microscopy, circular dichroism, Taylor dispersion analysis, and capillary electrophoresis, were used to study and optimize the self-assembly of pH-sensitive short synthetic amphiphilic peptides containing an RGD motif for active targeting of tumor cells and smart drug delivery. The combined methods evidenced the spontaneous formation of nanorods (L = 50nm, d = 10nm) at pH 11, stabilized by β-sheets. To complement with imaging properties for diagnosis, a new strategy was developed by designing an optimized peptide sequence to allow for efficient functionalization with a contrast agent, while preserving the self-assembling properties. Co-assemblies of the peptide and its derivatives, after peptide modification with a gadolinium complex, exhibited similar nanorod structures and required properties for drug delivery and imaging applications in vivo.

Single ion effect on material and electrical properties of deposited and annealed Al2O3 film on 4H-SiC by atomic layer deposition

Abstract It is preferable for the use of highly radiation tolerant SiC devices in space applications due to the strong covalent bond of SiC material. In particular, the MOS devices using SiO2 as a gate dielectric still exhibits a high density of interface states, which enables huge difficulties in accounting for the formation of latent gate damage generated along the heavy ion incidence path. High-k materials represented by Al2O3 gate dielectric offer the most promise to replace the current SiO2 gate dielectric. Al2O3 is a promising high-k material for application in radiation-resistant gate dielectrics on 4H-SiC. The effects of heavy ion irradiation via linear energy transfer (LET) of 99.8 MeV·cm²/mg Bi ions on the surface morphology and interfacial properties of Al2O3 gate dielectric on 4H-SiC were investigated and demonstrated by various characterization methods. It is found that the uniformity of refractive index of 1100 °C annealed Al2O3 films is less affected by radiation compared to as deposited films. Also, the roughness of Rq for the annealed films is varied from 0.28 nm to 0.34 nm before and after irradiation, which shows less degree of increment as compared to as deposited films with increase from 0.24 nm to 0.54 nm. The bombarded pores can be hardly observed in annealed Al2O3. Additionally, the formation of oxygen vacancies or interstitial oxygen contributes to a decrease of Al-O and Al-O-Si bonds after irradiation. Fortunately, the crystallized Al2O3 induced by annealing exhibits a more robust and stable bonding between Al and O and shows less damaged elemental components. These film characterization and underlying mechanisms behind heavy ion irradiation is of meaningful use for development of SiC metal-oxide-semiconductor field effect transistor (MOSFET) irradiation hardening process.

Bubble Detection in Multiphase Flows Through Computer Vision and Deep Learning for Applied Modeling

An innovative method for bubble detection and characterization in multiphase flows using advanced computer vision and neural network algorithms is introduced. Building on the research group’s previous findings, this study combines high-speed video capture with advanced deep learning techniques to enhance bubble detection accuracy and dynamic analysis. In order to further develop a robust framework for detecting and analyzing bubble properties in multiphase flows, enabling accurate estimation of essential mass transfer parameters, a YOLOv9-based neural network was implemented for bubble segmentation and trajectory analysis, achieving high accuracy. Key contributions include the development of an averaged mass transfer model integrating experimental data, neural network outputs, and scaling algorithms, as well as validation of the proposed methodology through experimental studies, including high-speed video imaging and comparisons with mass transfer coefficients obtained via the sulfite method. By precisely characterizing critical parameters, the algorithm enables accurate gas transfer rate calculations, ensuring optimal conditions in various industrial applications. The neural network-based algorithm serves as a non-invasive platform for detailed characterization of bubble media, demonstrating high accuracy in experimental validation and significantly outperforming traditional techniques. This approach provides a robust tool for real-time monitoring and modeling of bubble flows, laying the foundation for novel, non-invasive methods to measure multiphase media properties.

Apparent specific surface area as an indicator of the degree of cellulose microfibrillation

AbstractTracking mechanical microfibrillation in nanocellulose production is time-consuming due to a lack of quick characterization methods. This study investigates optical monitoring of the mechanical microfibrillation process by determining the dimensions of microfibrillated cellulose (MFC) particles on micron scale. Bleached hardwood pulp was microfibrillated using three sets of grinding discs in a six-stage pilot process, analyzing MFC characteristics as a function of specific energy consumption via image analysis. A laboratory-scale ultrafine grinder was also used for comparison. The degree of microfibrillation was assessed over a broad energy range using the equivalent diameter derived from the MFC length and width through image processing. The microfibrillation process adhered to Rittinger’s law, i.e., changes in the apparent specific surface area (SSA) were linearly proportional to the applied grinding energy. SSA, being inversely proportional to equivalent diameter, predicted MFC quality in terms of nanofilm strength properties. The optical fiber image analyzer proved suitable for online monitoring and control of microfibrillation processes. Despite resolution limits in detecting sub-micron particles, their proportion interrelates to the size of optically visible particles, covering industrial needs for mechanical microfibrillation.

Spectroscopic Signatures of Ultra-Thin Amorphous Carbon with the Tuned Disorder Directly Grown on a Dielectric Substrate.

The reduced structural complexity of atomically thin amorphous carbons makes it suitable for semiconductor technology. Inherent challenges arise from transfer processes subsequent to growth on metallic substrates, posing significant challenges to the accurate characterization of amorphous materials, thereby compromising the reliability of spectroscopic analysis. Here this work presents a novel approach: direct growth of ultra-thin amorphous carbon with tuned disorder on a dielectric substrate (SiO2/Si) using photochemical reaction and thermal annealing process with a solid precursor. This work characterizes the amorphous carbon films' disorder using spectroscopic techniques, such as X-ray photoelectron spectroscopy, Electron energy loss spectroscopy, and Raman spectroscopy, which offer greater convenience compared to microscopy-based studies. This method, rooted in comprehensive spectroscopic characterization, elucidates characteristic signatures inherent to the amorphous carbon films. These findings reveal that Raman spectroscopy is particularly effective in identifying the amorphous phase of atomically-thin carbon. Additionally, I-V characterization and high-frequency dielectric measurements showcase the potential application of directly grown amorphous carbon films in the semiconductor industry, where nanometer-level thin conductors and dielectrics are commonly utilized. This transfer-free characterization method provides a useful tool to find the correlation between atomic structure and electrical/optical properties, giving valuable insights into comprehensive crystallographic fundamental research.

Advancing Micro Plastic Analysis: A Comprehensive Review of Detection and Characterization Techniques

This review paper critically evaluates the current state of micro plastic detection and characterization methods, highlighting the significant environmental and health risks posed by microplastics. Microplastics, categorized into primary and secondary types, are ubiquitous in various ecosystems, raising concerns about their impacts on aquatic life and human health. The paper discusses the diverse characteristics of microplastics and the challenges associated with their detection in complex environmental matrices. An overview of existing detection methods, including visual identification, spectroscopic techniques, and emerging technologies such as automated imaging and machine learning, is provided. Additionally, the review addresses the environmental fate and transport of microplastics, their interactions with biota, and the socio-economic implications of pollution. Emphasizing the need for standardized methodologies and innovative solutions, the paper calls for enhanced public awareness and policy initiatives to mitigate the pervasive threat of microplastics, thereby contributing to global environmental sustainability efforts.

Lithium Storage Mechanisms and Electrochemical Behavior of a Molybdenum Disulfide Nanoparticle Anode

This study investigates the electrochemical behavior of molybdenum disulfide (MoS2) as an anode in Li‐ion batteries, focusing on the extra capacity phenomenon. Employing advanced characterization methods such as in situ and ex situ X‐ray diffraction, Raman spectroscopy, X‐ray photoelectron spectroscopy, and transmission electron microscopy, the research unravels the complex structural and chemical evolution of MoS2 throughout its cycling. A key discovery is the identification of a unique Li intercalation mechanism in MoS2, leading to the formation of reversible LixMoS2 phases that contribute to the extra capacity of the MoS2 electrode. Density function theory calculations suggest the potential for overlithiation in MoS2, predicting Li5MoS2 as the most energetically favorable phase within the lithiation–delithiation process. Additionally, the formation of a Li‐rich phase on the surface of Li4MoS2 is considered energetically advantageous. After the first discharge, the battery system engages in two main reactions. One involves operation as a Li‐sulfur battery within the carbonate electrolyte, and the other is the reversible intercalation and deintercalation of Li in LixMoS2. The latter reaction contributes to the extra capacity of the battery. The incorporation of reduced graphene oxide as a conductive additive in MoS2 electrodes notably improves their rate capability and cycling stability.

Development of an Indoor Line Scanning System for Photovoltaic Modules Performance Characterization

Uganda’s interest in using solar energy for various applications began 20 years ago. However, there have been numerous reports by the public over the poor performance of the photovoltaic (PV) modules during their operations. This study determined the performance of selected PV modules openly sold in the Ugandan markets. The low-cost indoor line scanning system developed using locally available materials was used to assess the performance of each of the solar cells in the PV module by determining their photogenerated currents. In addition, the electrical characteristics of the PV modules were determined using the outdoor characterization method, which assumed the actual operation of the PV modules under direct sunlight. From the indoor line scans, the percentage of performing solar cells in the three PV modules of single-crystalline silicon (c-Si), multi-crystalline silicon (mc-Si), and amorphous silicon (a-Si) technologies were determined as 79%, 61%, and 95% respectively. The outdoor characterization results revealed that the c-Si, mc-Si, and a-Si PV modules had measured maximum power outputs of 18.5 W, 19.0 W, and 18.9 W, respectively and these were lower than the rated power values of 20 W. The line scan results had a direct relationship with the measured power output of the PV module, which implied that solar cells mismatch, affected the performance of the PV modules by lowering their performance. This developed testing system is affordable for developing countries with limited testing systems and would in the long run contribute to significant increase in the deployment of PV technology in Uganda since only performing PV modules would be allowed into the open market.

Inline Measurement of Light Beam Induced Current (LBIC) Under High-Injection and Reverse Bias Conditions

Quality control in solar cell production relies on characterization methods that are fast enough to yield information on the properties of each solar cell in less than about one second. Imaging techniques such as electroluminescence (EL) are well established methods revealing spatially resolved quality mappings. Scanning techniques such as light beam induced current (LBIC) are common laboratory methods yielding complementary information but do not meet the speed requirements. In our work, we analyse an inline implementation of the LBIC method which is extended with respect to its measurement parameters, i.e., both the laser power and a solar cell bias-voltage are varied. As these extended conditions differ from conventional LBIC-applications at zero bias and low injection, we compare our inline-LBIC images with EL images and conventional LBIC images by means of an image contrast analysis. We find that our method resembles more the EL imaging as variations in the local series resistance are prominently detected. Thus, the proposed LBIC approach with extended measurement parameter range can yield both local short circuit information and local series resistance information. With our setup, measurement speeds around 700 ms are achieved.

Investigation of Coal Structure and Its Differential Pore–Fracture Response Mechanisms in the Changning Block

The deep coal seams in the southern Sichuan region contain abundant coalbed methane resources. Determining the characteristics and distribution patterns of coal structures in this study area, and analyzing their impact on pore and fracture structures within coal reservoirs, holds substantial theoretical and practical significance for advancing coal structure characterization methods and the efficient development of deep coalbed methane resources. This paper quantitatively characterizes coal structures through coal core observations utilizing the Geological Strength Index (GSI) and integrates logging responses from different coal structures to develop a quantitative coal structure characterization model based on logging curves. This model predicts the spatial distribution of coal structures, while nitrogen adsorption data are used to analyze the development of pores and fractures in different coal structures, providing a quantitative theoretical basis for accurately characterizing deep coal seam features. Results indicate that density, gamma, acoustic, and caliper logging are particularly sensitive to coal structure variations and that performing multiple linear regression on logging data significantly enhances the accuracy of coal structure identification. According to the model proposed in this paper, primary-fragmented structures dominate the main coal seams in the study area, followed by fragmented structures. Micropores and small pores predominantly contribute to the volume and specific surface area of the coal samples, with both pore volume and specific surface area increasing alongside the degree of coal fragmentation. Additionally, the fragmentation of coal structures generates more micropores, enhancing pore volume and suggesting that tectonic coal has a greater adsorption capacity. This study combines theoretical analysis with experimental findings to construct a coal structure characterization model for deep coal seams, refining the limitations of logging techniques in accurately representing deep coal structures. This research provides theoretical and practical value for coal seam drilling, fracturing, and reservoir evaluation in the southern Sichuan region.

Recent Advances in Transdermal Drug Delivery Systems

Transdermal drug delivery systems (TDDS), particularly transdermal patches, represent a significant advancement in pharmaceutical technology, offering non-invasive drug administration through the skin. These systems provide controlled release mechanisms and improved therapeutic outcomes. The evolution of TDDS has effectively addressed various limitations of conventional drug delivery methods, by escaping first-pass metabolism and maintaining steady plasma drug concentrations. Technological innovations have introduced sophisticated materials and formulation strategies, including advanced polymer matrices, smart delivery systems, and novel permeation enhancers. The integration of nanotechnology has expanded the scope of transdermal delivery, enabling the administration of previously unsuitable drug molecules. Current knowledge of skin structure and its barrier function has led to improved transdermal patch designs incorporating microemulsions, nanocarriers, and smart polymers. Advanced technologies such as microneedles, iontophoresis, and sonophoresis have significantly improved drug permeation capabilities. Marketed formulations demonstrate successful implementation of these technologies, while ongoing research continues to optimize characterization methods and delivery mechanisms. The development of more effective and patient-friendly transdermal systems has resulted in improved therapeutic outcomes and enhanced patient compliance, marking a significant advancement in drug delivery technology. Recent innovations suggest a promising future for transdermal delivery systems in addressing complex therapeutic challenges and meeting diverse patient needs.

Tumor-infiltrating lymphocytes in melanoma: from prognostic assessment to therapeutic applications

Malignant melanoma, the most aggressive form of skin cancer, is characterized by unpredictable growth patterns, and its mortality rate has remained alarmingly high over recent decades, despite various treatment approaches. One promising strategy for improving outcomes in melanoma patients lies in the early use of biomarkers to predict prognosis. Biomarkers offer a way to gauge patient outlook early in the disease course, facilitating timely, targeted intervention. In recent years, considerable attention has been given to the immune response’s role in melanoma, given the tumor’s high immunogenicity and potential responsiveness to immunologic treatments. Researchers are focusing on identifying predictive biomarkers by examining both cancer cell biology and immune interactions within the tumor microenvironment (TME). This approach has shed light on tumor-infiltrating lymphocytes (TILs), a type of immune cell found within the tumor. TILs have emerged as a promising area of study for their potential to serve as both a prognostic indicator and therapeutic target in melanoma. The presence of TILs in melanoma tissue can often signal a positive immune response to the cancer, with numerous studies suggesting that TILs may improve patient prognosis. This review delves into the prognostic value of TILs in melanoma, assessing how these immune cells influence patient outcomes. It explores the mechanisms through which TILs interact with melanoma cells and the potential clinical applications of leveraging TILs in treatment strategies. While TILs present a hopeful avenue for prognostication and treatment, there are still challenges. These include understanding the full extent of TIL dynamics within the TME and overcoming limitations in TIL-based therapies. Advancements in TIL characterization methods are also critical to refining TIL-based approaches. By addressing these hurdles, TIL-focused research may pave the way for improved diagnostic and therapeutic options, ultimately offering better outcomes for melanoma patients.

Significance of ZnO nano photocatalysts in the clean hospital environment: Effective bacterial disinfection and antibiotic waste (ciprofloxacin) disposal

Hospital waste containing antibiotics is toxic to the ecosystem. Ciprofloxacin is one of the essential, widely used antibiotics and is often detected in water bodies and soil. It is vital to treat these medical wastes, which urge new research towards waste management practices in hospital environments themselves. Ultimately minimizes its impact in the ecosystem and prevents the spread of antibiotic resistance. The present study highlights the decomposition of ciprofloxacin using nano-catalytic ZnO materials by reactive oxygen species (ROS) process. The most effective process to treat the residual antibiotics by the photocatalytic degradation mechanism is explored in this paper. The traditional co-precipitation method was used to prepare zinc oxide nanomaterials. The characterization methods, X-Ray diffraction analysis (XRD), Fourier Transform infrared spectroscopy (FTIR), Ulraviolet-Visible spectroscopy (UV-Vis), Scanning Electron microscopy (SEM) and X-Ray photoelectron spectroscopy (XPS) have done to improve the photocatalytic activity of ZnO materials. The mitigation of ciprofloxacin catalyzed by ZnO nano-photocatalyst was described by pseudo-first-order kinetics and chemical oxygen demand (COD) analysis. In addition, ZnO materials help to prevent bacterial species, S. aureus and E. coli, growth in the environment. This work provides some new insights towards ciprofloxacin degradation in efficient ways.

Evolutionary trends and photothermal catalytic reduction performance of carbon dioxide by MOF-derived MnOx

Metal oxide catalysts derived from MOFs can inherit the excellent performance from their parent MOFs, possess abundant surface defects and high stability, and have attracted widespread interest in multiphase catalysis. In this study, we used Mn-MOF as a precursor and systematically investigated the evolution of MnOx catalysts by setting different calcination temperatures and times. XRD, SEM, TEM, Fourier transform infrared spectroscopy (FTIR), N2 adsorption–desorption analysis, XPS, H2-TPR, CO2-TPD, electrochemical characterization, and other methods were used to investigate the structural characteristics, microstructure, surface properties, and photoelectric properties of the catalysts. The catalytic performance of the catalysts was also investigated through photocatalytic carbon dioxide hydrogenation reduction tests. Research has shown that calcination temperature and time have a significant impact on the phase structure and surface properties of MnOx, and the physicochemical properties of derived MnOx can be controlled by controlling calcination temperature and time. Among them, MnOx-500 has a wider light absorption range, better electron transfer performance, richer oxygen vacancies, and excellent separation performance of photo generated charge carriers, resulting in higher photocatalytic CO2 hydrogenation and reduction performance. Its CO yield and selectivity reached 7420 μmol/g/h and above 99 %, respectively. This study provides valuable references for the preparation, optimization, and utilization in CO2 photothermal catalytic conversion of MnOx catalysts derived from MOFs.

Structural Evolution of an Optimized Highly Interconnected Hierarchical Porous Mg Scaffold under Dynamic Flow Challenges.

The development of Mg and its alloys as bone screws has garnered significant attention due to their exceptional biocompatibility and unique biodegradability. Notably, the controlled release of Mg2+ ions during degradation can positively influence bone fracture healing. The advantages of Mg raise appeal for application in bone tissue engineering. However, porous Mg scaffolds, while offering high surface areas, face challenges in maintaining slow degradation rates and preserving interconnectivity, which are crucial features for tissue ingrowth. To address these issues, this study introduces a highly interconnected hierarchical porous Mg scaffold and investigates its degradation behavior within a bioreactor, simulating body fluid flow rates to mimic the in vivo degradation performance at different implantation sites. The focus lies on elucidating the evolution of the porous structure, particularly the impact of degradation behavior on scaffold interconnectivity. Our findings reveal that the initial high interconnectivity of the scaffold is significantly influenced by the flow rate. The dynamic fluid flow modulates the transport of degradation byproducts and the deposition patterns. At lower flow rates, Mg2+ ions accumulate within pores, leading to the formation of substantial deposits that directly reduce porosity. Specifically, after 42 days, porosities decreased to 68.80 ± 2.31, 58.52 ± 2.53, and 41.25 ± 2.82% at flow rates of 2.0, 1.0, and 0.5 mL/min, respectively. This porosity reduction and pore space occlusion by deposits sequentially hinder the interconnectivity. The magnitude of decreased porosity could be used to evaluate the ability of the microarchitecture to maintain scaffold interconnectivity. Meanwhile, the long-term degradation deposition behavior of the highly interconnected hierarchical porous Mg scaffold potentially revealed the structural integrity loss from the original design to its in vivo degraded structure at different body fluid flow rates. The present work might bring valuable insight into the design of pore strut and interconnectivity characterization methods for the progress of a high-performance tissue engineering scaffold.

Characterization of compressive fracture strain based on bilinear strain paths

This study proposes the compressive fracture characterization method using bilinear strain paths: pre-tension and compression. Compressive ductile fracture exhibits extremely large strain, which has been regarded as being difficult to be measured. Large deformation under compressive loading makes the shape of a specimen barreled and changes the stress triaxiality rapidly. Due to these complicated and large strains, compressive fracture strain can be considered to be within the so-called cut-off region where no fracture occurs. In order to enable compression tests to be easier, an approach that can lower the range of fracture strain is needed. Uniaxial tensile deformation is a strain path that induces the growth of voids inside ductile materials and leads to ductility reduction. Ductile materials subjected to pre-tensile loading before compressive loading can show the premature compressive fracture. A ductile fracture model capable of predicting the cut-off region is selected for ductile fracture loci of the bilinear paths and implemented into the numerical simulation with different pre-tensile strain levels. The verification of the proposed characterization method is performed by comparing experimental data and simulation results for fractured specimen shapes and load-displacement curves.

Advanced oxidative degradation of norfloxacin based on peroxomonosulfate activated by the Co/Fe@ eggshell

The CoFe@Eggshell composites were fabricated to degrade the norfloxacin (NOR) with the peroxymonosulfate (PMS) activation. Various characterization methods were used to analyze the property of the composite, which showed that the material has excellent stability and practical applications. The results indicated that the CoFe@Eggshell/PMS system achieved a removal efficiency of 93.9% for NOR under optimal conditions. After five regeneration cycles, the degradation efficiency for NOR reached over 91.9%, demonstrating the excellent stability of the catalyst. The combination of Co, Fe and eggshell enhanced the electron transfer ability and promoted the redox cycles of Co2+/Co3+ and Fe2+/Fe3+. The porous structure of eggshells provided abundant active sites on the catalyst surface that facilitated the effective degradation of NOR. The research provides a research direction for the application of eggshell waste in the field of advanced oxidation.

Coupling effects of loading rate and temperature on mode I dynamic fracture characteristics of ductile cast iron

Engineering structures made of ductile cast iron (DCI) have a potential risk of failure due to extreme service environments such as high velocity impacts and sub-zero temperatures. Therefore, it is of great importance to investigate the dynamic fracture behavior of DCI under the coupling effect of rate and temperature. In this paper, two sets of impact velocities (5 m/s and 13.5 m/s), and four sets of temperatures (20 °C, −40 °C, −60 °C, and −80 °C) were specially designed to investigate the coupling effect on the mode I dynamic fracture toughness (DFT). The results show that DFT is positively correlated with impact velocity at 20 °C, −40 °C and −60 °C. However, at −80 °C, the rate effect is reversed. Moreover, DFT decreases with decreasing temperature regardless of impact velocity. With microscopic analysis, the phenomenon of ductile–brittle transition (DBT) was observed in the failure of the material, and it’s verified by dynamic tensile tests. The ductile–brittle transition temperature (DBTT) of DCI is determined as −39.7 °C by comparing the DFT with the strain energy density (SED) characterization method.

Decoration of CeO2 nanoparticles on Cu/Co bimetallic oxide and their catalytic performance

We have developed a series of Co-Cu bimetallic oxide nanocatalysts using an environmentally friendly water phase synthesis method, demonstrating significant potential in catalyzing the CO oxidation reaction. The 0.3Co3O4/0.7CuO nano-hybrid, with a feed ratio of 3:7 for Cobalt(II) chloride hexahydrate to Copper(II) chloride dihydrate, exhibited a CO catalytic oxidation T90 approximately 70 °C lower than that of a single transition metal oxide material. Building on this, we enhanced the catalysts by incorporating CeO2 nanoparticles to produce Co3O4/CuO/CeO2 oxide nanocatalysts. By varying the amount of CeO2 nanoparticles added to the 0.3Co3O4/0.7CuO catalyst, we achieved further improvement in the CO oxidation performance. Specifically, the T90 of the CO catalytic oxidation reaction for the 0.3Co3O4/0.7CuO/0.7CeO2 material was approximately 30 °C lower than that of 0.3Co3O40.7CuO. Various characterization methods, such as XRD, EDX, and in situ FT-IR, were employed to investigate the impact of different components on the CO oxidation process and the potential reaction mechanism. The results indicated that the introduction of CeO2 successfully enhanced the activity and stability of the catalysts.

Molecular characterization of selected endophytic fungi isolate IDGG 3 leaf galing galing (cayratia trifolia L.) with the polymerase chain reaction method

Background: Endophytic fungi live in plant tissues and are usually not harmful to their host plants. One of the host plants for endophytic fungi is bush grape leaves (Cayratia trifolia L.). Objective: The research aimed to determine the molecular characteristics of the endophytic fungi isolates selected IDGG 3 of bush grape leaves. Methods: The test used the polymerase chain reaction method to determine the species-level characteristics using internal transcribed spacers (ITS) 1 and 4. The DNA band was successfully amplified with 500 base pairs with 3000 markers. Results: The fungi isolates selected IDGG 3 of bush grape leaves in molecular identification based on the Basic Local Alignment Search Tool (BLAST) analysis on Genebank NCBI that the IDGG 3 samples of bush grape leaves had a similarity level of 99%, namely Fusarium incarnatum JL5-2, Fusarium incarnatum JL3-4- 1, Fusarium incarnatum CBB-2, Fusarium incarnatum JL3-3, Fusarium incarnatum CBA-3, Fusarium incarnatum CBB-1, Fusarium incarnatum CBA-2, Fusarium chlamydospore, Fusarium cf. Incarnatum, and Fusarium sp. Conclusion: The results of the molecular characteristics of the selected endophytic fungi isolate IDGG 3 galing-galing leaves (Cayratia trifoliata L.) have the closest degree of kinship with the species Fusarium incarnatum JL3-4-1. The importance of the PCR method in the molecular characterization of endophytic fungi, as well as opening opportunities for further exploration of the biotechnological potential of endophytic fungi from Cayratia trifolia L.