Tool For Characterization Research Articles

Effective affective EEG-based indicators in emotion-evoking VR environments: an evidence from machine learning

AbstractThis study investigates the use of electroencephalography (EEG) to characterize emotions and provides insights into the consistency between self-reported and machine learning outcomes. Thirty participants engaged in five virtual reality environments designed to elicit specific emotions, while their brain activity was recorded. The participants self-assessed their ground truth emotional state in terms of Arousal and Valence through a Self-Assessment Manikin. Gradient Boosted Decision Tree was adopted as a classification algorithm to test the EEG feasibility in the characterization of emotional states. Distinctive patterns of neural activation corresponding to different levels of Valence and Arousal emerged, and a noteworthy correspondence between the outcomes of the self-assessments and the classifier suggested that EEG-based affective indicators can be successfully applied in emotional characterization, shedding light on the possibility of using them as ground truth measurements. These findings provide compelling evidence for the validity of EEG as a tool for emotion characterization and its contribution to a better understanding of emotional activation.

Analysis of lipid composition of cell-bound membrane vesicles (CBMVs) derived from endothelial cells

Cell-bound membrane vesicles (CBMVs), a novel type of membrane vesicles, have been identified through a series of characterization tools. However, the lipid composition of CBMVs has not yet been characterized. This study focuses on the differences in lipid composition between CBMVs and cell membranes. In order to determine the lipid composition of CBMVs and cell membranes of Human umbilical vein endothelial cells (HUVECs) and find out differential metabolites, this study was carried out by isolating CBMVs lipids and characterizing them using high-performance liquid chromatography tandem secondary mass spectrometry (LC-MS/MS). The results showed the presence of 213 up-regulated and 726 down-regulated lipids in CBMVs compared to cell membranes which produced CBMVs. There are lipids expressed in CBMVs and not in cell membranes: DGDG 18:0_8:0, DGDG O-8:0_16:1, DGDG O-26:7_26:7, DGDG O-16:3_26:7, TG 15:4_21:5_22:5; 4O, PC 49:11, PG 19:5_38:10, PI 60:14, PI 44:9, PI 25:2, PI 43:5, PI 50:10, PS 55:10. DGDG (digalactosyl diglyceride), MGDG (monogalactosyl diglyceride) belongs to galactosyl diglyceride, promotes fat catabolism, which also has antioxidant and anti-inflammatory effects, and unsaturated diacylglycerols are a class of antioxidant compounds, which enables CBMVs to have a therapeutic potential.

Automated diagnosis of atherosclerosis using multi-layer ensemble models and bio-inspired optimization in intravascular ultrasound imaging.

Atherosclerosis causes heart disease by forming plaques in arterial walls. IVUS imaging provides a high-resolution cross-sectional view of coronary arteries and plaque morphology. Healthcare professionals diagnose and quantify atherosclerosis physically or using VH-IVUS software. Since manual or VH-IVUS software-based diagnosis is time-consuming, automated plaque characterization tools are essential for accurate atherosclerosis detection and classification. Recently, deep learning (DL) and computer vision (CV) approaches are promising tools for automatically classifying plaques on IVUS images. With this motivation, this manuscript proposes an automated atherosclerotic plaque classification method using a hybrid Ant Lion Optimizer with Deep Learning (AAPC-HALODL) technique on IVUS images. The AAPC-HALODL technique uses the faster regional convolutional neural network (Faster RCNN)-based segmentation approach to identify diseased regions in the IVUS images. Next, the ShuffleNet-v2 model generates a useful set of feature vectors from the segmented IVUS images, and its hyperparameters can be optimally selected by using the HALO technique. Finally, an average ensemble classification process comprising a stacked autoencoder (SAE) and deep extreme learning machine (DELM) model can be utilized. The MICCAI Challenge 2011 dataset was used for AAPC-HALODL simulation analysis. A detailed comparative study showed that the AAPC-HALODL approach outperformed other DL models with a maximum accuracy of 98.33%, precision of 97.87%, sensitivity of 98.33%, and F score of 98.10%.

Coordinate-based simulation of pair distance distribution functions for small and large molecular assemblies: implementation and applications.

X-ray scattering has become a major tool in the structural characterization of nanoscale materials. Thanks to the widely available experimental and computational atomic models, coordinate-based X-ray scattering simulation has played a crucial role in data interpretation in the past two decades. However, simulation of real-space pair distance distribution functions (PDDFs) from small- and wide-angle X-ray scattering, SAXS/WAXS, has been relatively less exploited. This study presents a comparison of PDDF simulation methods, which are applied to molecular structures that range in size from β-cyclo-dextrin [1 kDa molecular weight (MW), 66 non-hydrogen atoms] to the satellite tobacco mosaic virus capsid (1.1 MDa MW, 81 960 non-hydrogen atoms). The results demonstrate the power of interpretation of experimental SAXS/WAXS from the real-space view, particularly by providing a more intuitive method for understanding of partial structure contributions. Furthermore, the computational efficiency of PDDF simulation algorithms makes them attractive as approaches for the analysis of large nanoscale materials and biological assemblies. The simulation methods demonstrated in this article have been implemented in stand-alone software, SolX 3.0, which is available to download from https://12idb.xray.aps.anl.gov/solx.html.

Block Copolymer-Directed Single-Diamond Hybrid Structures Derived from X-ray Nanotomography.

Block copolymers are recognized as a valuable platform for creating nanostructured materials. Morphologies formed by block copolymer self-assembly can be transferred into a wide range of inorganic materials, enabling applications including energy storage and metamaterials. However, imaging of the underlying, often complex, nanostructures in large volumes has remained a challenge, limiting progress in materials development. Taking advantage of recent advances in X-ray nanotomography, we noninvasively imaged exceptionally large volumes of nanostructured hybrid materials at high resolution, revealing a single-diamond morphology in a triblock terpolymer-gold composite network. This morphology, which is ubiquitous in nature, has so far remained elusive in block copolymer-derived materials, despite its potential to create materials with large photonic bandgaps. The discovery was made possible by the precise analysis of distortions in a large volume of the self-assembled diamond network, which are difficult to unambiguously assess using traditional characterization tools. We anticipate that high-resolution X-ray nanotomography, which allows imaging of much larger sample volumes than electron-based tomography, will become a powerful tool for the quantitative analysis of complex nanostructures and that structures such as the triblock terpolymer-directed single diamond will enable the generation of advanced multicomponent composites with hitherto unknown property profiles.

Interface-Centric Strategies in Kesterite Solar Cells: Addressing Challenges, solutions, and Future Directions for Efficient Solar-Harvesting Technologies.

As reserves of non-renewable energy sources decline, the search for sustainable alternatives becomes increasingly critical. Next-generation energy materials play a key role in this quest by enabling the manipulation of properties for effective energy solutions and understanding interfaces to enhance energy yield. Studying these interfaces is essential for managing charge transport in optoelectronic devices, yet it presents significant challenges. This review emphasizes the critical role of interfaces in kesterite solar cells (KSCs), focusing on interfacial architecture, carrier losses, and non-radiative recombination. This review highlights the importance of addressing interface issues and utilizing advanced characterization tools to reveal interface properties. Current interface problems are addressed, recent advancements in interface engineering are summarized, and perspectives on future challenges and prospects are offered. The goal is to illuminate the nature of interfaces and tackle interface losses, which are crucial for improving device design and performance. Despite their pivotal role in device operation, comprehensive reviews on interfaces are lacking, underscoring the relevance of the work for researchers in material interfaces and device engineering. It is hoped that this article will spark interest and inspire further research into interface studies and the mitigation of interface losses.

A Comprehensive Review on Studying and Developing Guidelines to Standardize the Inspection of Properties and Production Methods for Mycelium-Bound Composites in Bio-Based Building Material Applications.

Mycelium-bound composites (MBCs) represent a promising advancement in bio-based building materials, offering sustainable alternatives for engineering and construction applications. This review provides a comprehensive overview of the current research landscape, production methodologies, and standardization ideas related to MBCs. A basic search on Scopus revealed over 250 publications on MBCs between 2020 and 2024, with more than 30% focusing on engineering and materials science. Key studies have investigated the physical and mechanical properties of MBCs, optimizing parameters such as substrate type, fungal species, incubation time, and post-processing to enhance material performance. Standardizing the inspection of MBC properties is crucial for ensuring quality and reliability. Various testing standards, including those from the American Society for Testing and Materials (ASTM), the International Organization for Standardization (ISO), the Japanese Industrial Standard (JIS), European Standards (EN), Deutsches Institut für Normung (DIN), and the Thai Industrial Standards Institute (TIS), are utilized to evaluate density, water absorption, compression strength, tensile strength, insulation, and other critical properties. This review highlights the distinction between lab-scale and apply-scale testing methodologies, emphasizing the need for comprehensive evaluation protocols. Additionally, the production process of MBCs involves critical steps like substrate preparation, fungal species selection, and mycelium growth, necessitating the implementation of good manufacturing practices (GMPs) to ensure consistency and quality. The internal and external structures of MBCs significantly influence their performance, necessitating standardized inspection methods using advanced techniques such as scanning electron microscopy (SEM), X-ray computed tomography (CT) scanning, and surface profilometry. By establishing robust inspection protocols and production standards, the industry can enhance the reliability and adoption of MBCs, contributing to innovations in materials science and promoting environmental sustainability. This review underscores the importance of interdisciplinary collaboration, advanced characterization tools, and regulatory frameworks to address challenges and advance the field of MBCs.

Multi-objective, multi-constraint high-throughput design, synthesis, and characterization of tungsten-containing refractory multi-principal element alloys

Refractory multi-principal element alloys (RMPEAs) have gained interest recently due to their superior properties at elevated temperatures, including outstanding yield and ultimate strengths, high thermal conductivity, and resistance to creep. RMPEAs can be designed to exhibit a wide range of properties by tailoring their composition. However, the vast chemical design space makes brute-force experimental screening inefficient and costly. In this work, we follow a closed-loop, iterative computational/experimental screening approach that combines computational alloy design methodologies with high-throughput synthesis and characterization tools to explore the vast RMPEAs space and design new RMPEAs that satisfy multiple objectives and constraints. In particular, we targeted compositions with yield strengths higher than 50 MPa at 2000 °C, W content of more than 30 at.% for high-temperature strength and operability up to 2000 °C, narrow solidification range for additive manufacturability, competitive ductility metrics, among other property constraints. We evaluated the mechanical properties and microstructure of 58 alloys designed in 5 batches, in both as-cast and homogenized conditions, synthesized using vacuum arc melting, utilizing scanning electron microscopy, X-ray diffraction, Vickers microhardness, nanoindentation, and high-temperature compression testing. Based on the microhardness screening experiments in each batch, the best-performing alloys were selected for scale-up. High-temperature compression at 1800 °C was performed in these alloys, demonstrating that the designed alloys exhibit up to five times higher yield strength than a pure tungsten benchmark. We conclude that W-containing RMPEAs designed in this study merit further consideration for next-generation structural materials for ultra-high temperature applications.

Exploring mechanical behavior at interfaces of laser powder bed fusion (LPBF) deposits on wrought Inconel 718: an indentation-based approach

PurposeThis study used an indentation-based mechanical testing framework for the mechanical characterization of laser powder bed fusion (LPBF) processed Inconel 718 on a wrought Inconel 718 substrate. The purpose of the paper is to investigate the effectiveness of the indentation-based approach for localized mechanical evaluation.Design/methodology/approachThe LPBF-processed wrought substrate was sectioned into three sections for microstructural and mechanical characterization. A 3D heat source model was used for the thermal analysis of the interface region. The developed interface region is probed using the Knoop hardness indenter in different orientations to determine the textural anisotropy and mechanical behavior of the region.FindingsLPBF process develops a melted interface zone (MIZ) at the deposition-substrate interface. The MIZ exhibited a coarse grain structure region along with a larger primary dendritic arm spacing (PDAS), signifying a slower cooling rate. FE modeling of the LPBF process reveals heat accumulation in the substrate along with intrinsic heat treatment (IHT) induced due to layer-wise processing. The obtained yield locus shows strong anisotropy in the deposition region, whereas reduced anisotropy with a nearly uniform ellipse locus for the MIZ regions. This reduced anisotropy is attributable to IHT and heat accumulation in the substrate.Originality/valueAn alternative localized mechanical characterization tool has been investigated in this work. The approach proved sensitive to thermal variations during LPBF processing in an isolated region which extends its suitability to variable geometry parts. Moreover, the approach could serve as a screening tool for parts made from dissimilar metals.

A Study on the Effects of Depth-Dependent Power Loss on Speckle Statistics Estimation

Characterization of the interference patterns observed in B-mode images (i.e., speckle statistics) is a valuable tool in tissue characterization. However, changes in echo amplitudes unrelated to speckle, including power loss due to attenuation and diffraction, can bias these metrics, undermining their utility. Tissue with high attenuation such as the uterine cervix are especially affected. The purpose of this study was to demonstrate and quantify the effects of attenuation and diffraction on speckle statistics and to propose methods of compensation. Analysis was performed on simulated diffuse scattering phantoms of varying attenuation with simulated transducers at 9 and 5 MHz center frequency. Application in the in vivo macaque cervix using a clinical scanner is also presented. Nakagami and homodyned K distribution parameters were calculated in parameter estimation regions (PERs) of varying size within simulations and experiments. Changes in speckle statistics parameters with respect to PER size and depth were compared with and without two different compensation schemes. It has been shown that compensation for attenuation and diffraction is necessary to produce speckle statistics estimates that do not depend on medium attenuation or PER size. Reducing the dependence on these factors connects speckle statistics estimates more closely with the microstructure of the probed medium.

Low-dose electron microscopy imaging for beam-sensitive metal-organic frameworks.

Metal-organic frameworks (MOFs) have garnered significant attention in recent years owing to their exceptional properties. Understanding the intricate relationship between the structure of a material and its properties is crucial for guiding the synthesis and application of these materials. (Scanning) Transmission electron microscopy (S)TEM imaging stands out as a powerful tool for structural characterization at the nanoscale, capable of detailing both periodic and aperiodic local structures. However, the high electron-beam sensitivity of MOFs presents substantial challenges in their structural characterization using (S)TEM. This paper summarizes the latest advancements in low-dose high-resolution (S)TEM imaging technology and its application in MOF material characterization. It covers aspects such as framework structure, defects, and surface and interface analysis, along with the distribution of guest molecules within MOFs. This review also discusses emerging technologies like electron ptychography and outlines several prospective research directions in this field.

Characterizing strong-field tunneling ionization with a phase-dependent THz polarization spectrum

The terahertz radiation emitted by asymmetrically ionized wavepackets in two-color strong-field tunneling ionization is essential for detecting the system's associated electron dynamics and structural properties. We propose to characterize and control tunneling ionization using a phase-dependent terahertz polarization (PTP) spectrum, analyzed through a combination of the classical trajectory Monte Carlo method, an analytical model based on the virial theorem, and the rigorous solution of the time-dependent Schrödinger equation as a benchmark. Our results demonstrate that the PTP spectrum offers a high-precision measure of the Coulomb effect through the relative phase of the two-color laser. Comparisons of PTP results calculated using different methods suggest how the electron can be manipulated by controlling the relative phase and laser intensity. In particular, the PTP spectrum can be used to calibrate the relative phase and provides a convenient and robust reconstruction of the time-averaging of tunneling positions with high precision using the analytical model. These insights reveal that the PTP spectrum as a whole can be a new and useful tool for the all-optical characterization of ultrafast atomic and molecular ionization.

A Novel Composite Material UiO-66-Br@MBC for Mercury Removal from Flue Gas: Preparation and Mechanism.

To reduce the mercury content in flue gas from coal-fired power plants and to obtain high-performance, low-cost mercury adsorbents, a novel composite material was prepared by structural design through the in situ growth method. Functionalization treatments such as the modification of functional groups and multilayer loading of polymetallic were conducted. These materials include the MOF material UiO-66 and modified biochar doped with Fe/Ce polymetallic, both of which contain unsaturated metal centrals and oxygen-containing functional groups. On the basis of obtaining the effects of adsorption temperature and composite ratio on the Hg0 removal characteristics, coupling and synergistic mechanisms between the various types of active centers included were investigated by using a variety of characterization and analysis tools. The active adsorption sites and oxidation sites were identified during this process, and the constitutive relationship between the physicochemical properties and the performance of Hg0 removal was established. The temperature-programmed desorption technique, Grand Canonical Monte Carlo simulation, and adsorption kinetic model were employed to reveal the mechanism of Hg0 removal. The results showed that the UiO-66-Br@MBC composite adsorbent possessed an excellent Hg0 removal performance at adsorption temperatures ranging from 50 to 250 °C, and targeted construction of adsorption and oxidation sites while maintaining thermal stability. The Hg0 removal by the composites is the result of both adsorption and oxidation. The micropores and small pore mesopores in the samples provide physical adsorption sites. The modified biochar acts as a carrier to facilitate the full exposure of the central metal zirconium ions, the formation of more active sites, and the process of electron transfer. The doping modification of the Br element can enhance the overall redox ability of the sample, and the introduced Fe and Ce polymetallic ions can work in concert to promote the oxidation process of Hg0. The excellent regulation of the ratio between adsorption and oxidation sites on the surface of the composite material finally led to a significant boost in the samples' capacity to remove Hg0.

Temperature-dependent charge transport measurements unveil morphological insights in non-fullerene organic solar cells

The morphological analysis of bulk heterojunction (BHJ) active layer stands as a critical imperative for advancing the performance of future organic solar cells. Conventional characterization tools employed for morphological investigation often require substantial resources, both in cost and physical space, thereby imposing restraints on research endeavors in this domain. Here, we extend the application of charge carrier transport characterization beyond conventional mobility assessments, utilizing it as a table-top method for preliminary morphological screening in organic thin films. The investigation focuses on several high-performance BHJ systems that utilize typical “Y” non-fullerene acceptors. It involves in-depth transport studies, including temperature- and field-dependent transport characterizations. The resulting transport data are analyzed in detail using the Gaussian disorder model to extract key transport parameters, specifically the high-temperature limited mobility (μ∞) and positional disorder (∑). Integrating these transport parameters with morphological insights obtained through various characterization tools—including x-ray scattering, sensitive spectroscopy, and quantum chemistry simulation—provides a deep understanding of the intricate interplay between charge transport properties and morphological characteristics. The results reveal explicit relationships, associating μ∞ with the degree of molecular stacking in BHJs and ∑ with the structural disorder in molecule skeleton. Our findings point to the promising potential of utilizing a simple transport characterization technique for the early stage evaluation of thin film packing and geometric properties of organic materials.

The sensitivity of powder characterization tool measurements to particle properties

Calibration of Discrete Element Method (DEM) simulations is challenging and non-standardised. A common approach involves deducing particle properties from bulk measurements obtained through powder characterisation instruments. However, choosing the best bulk measurements for calibrating DEM simulations depends on the specific material and system. This paper presents a detailed sensitivity analysis of four commonly used bulk measurements to aid in selecting the best measurements for DEM calibration: Beverloo C fitting term (flowing density), angle of repose, dynamic angle of repose, and cohesive index. Rolling friction and cohesion significantly impact these measurements, with systems showing higher sensitivity to frictional properties in faster flow conditions, while the coefficient of restitution has low sensitivity. The cubic term of a polynomial fit to the free surface of a rotating drum was investigated for measuring the coefficient of restitution. This method demonstrated better sensitivity, particularly at lower rotational speeds.

Elemental analyses of feldspathic to basaltic soils and rocks on the moon using laser-induced breakdown spectroscopy

In-situ analysis of major elements using laser-induced breakdown spectroscopy (LIBS) is essential for future lunar landing missions, yet its performance under lunar conditions remains not fully understood. This uncertainty arises from the absence of an atmosphere and the diverse range of surface materials, which vary in chemical composition from anorthosites to basalts, and in physical properties from fine regolith to boulders. To address these challenges, we developed and cross-validated a multivariate LIBS calibration model by measuring 169 compressed fine powders of geologic samples under vacuum. These samples fully encompass the bulk composition range of lunar meteorites. We investigated the applicability of the model to a wider range of samples by measuring lunar meteorites, terrestrial anorthites, and lunar simulants in various physical forms, including rock chips and soils with different grain sizes and bulk densities. For powder samples, the quantification accuracy, assessed using root mean squared error (RMSE), resulted in 2.5 wt% SiO2, 0.25 wt% TiO2, 1.2 wt% Al2O3, 1.3 wt% MgO, 1.2 wt% CaO, 0.33 wt% Na2O, 0.47 wt% K2O (0.060 wt% K2O in the <1 wt% range), and 1.5 wt% T-Fe2O3. For rock chip samples, the RMSEs were 3.1 wt% SiO2, 0.32 wt% TiO2, 2.2 wt% Al2O3, 2.5 wt% MgO, 2.0 wt% CaO, 0.33 wt% Na2O, 0.089 wt% K2O, and 2.1 wt% T-Fe2O3. Despite significant differences in physical conditions between powders and rocks, their RMSEs remained consistent within a factor of two. Changes in grain size or bulk density of soils had relatively minor effects on the RMSE. These RMSEs confirm that the quantification accuracy of LIBS is sufficient to distinguish the subgroups within the lunar anorthosite suite (e.g., anorthosites vs. norites) and basalts (e.g., high-Ti vs. low-Ti) across a range of soil types, from coarse to fine and from loose to compact, as well as rocks. Furthermore, our analysis shows that LIBS can differentiate between “purest” and “pure” anorthosites (98 and 95 vol% plagioclase, respectively) based on the 3σ detection limits of Mg and Fe lines. These capabilities of LIBS align well with the goals of future lunar exploration, such as locating ilmenite-rich soils for resource extraction, detecting purest anorthosites to understand early lunar evolution, and identifying noritic impact melts to refine lunar chronology. Overall, our results demonstrate that LIBS serves as a versatile tool for rapid geochemical characterization on the Moon.

A new inversion method for imaging near-wellbore radial slowness based on array acoustic logging data

Abstract The slowness of near-wellbore formation is critical to geophysical exploration as it can be used to evaluate rock brittleness, wellbore stability, fracturing effect, and invasion depth. Conventional methods for investigating radial slowness profiles of both compression wave and shear wave near-wellbore are time-consuming and depend on the extracted arrival time of the first wave. Additionally, these methods cannot simultaneously conduct the profile inversion of the compression and shear waves. We develop a new inversion method for imaging near-wellbore radial slowness to overcome these limitations. It can adaptively extract slowness and its corresponding radial thickness from array acoustic logging data. The new method adaptively extracts slowness sequences with different radial depths by combining receivers with different source distances. The thickness corresponding to the slowness sequences can be obtained by combining the slow sequence with the ray theory, and finally, the radial slowness profile can be obtained. an example of synthesis using the FDTD method is presented. The results show that the algorithm is stable and reliable. Overall, this study highlights the value of radial slowness imaging as a powerful tool for wellbore analysis and reservoir characterisation.

Experimental review and accuracy of etchants used for phase analysis of SAF2507 Super Duplex Stainless Steel

The mechanical and corrosion properties of duplex stainless steels (DSS) depend on the distribution of ferrite and austenite as well as the presence of secondary phases. It is therefore necessary to accurately determine both the distribution of the phases and their morphology. The aim of this research is to define a standard method for the determination of the volume fraction of the phases present in a SAF2507 SDSS by analysing images acquired by light microscope. To do this, the material is heat-treated at 850 °C for 5 min, 15 min, 30 min, 1h, 5h to stimulate the formation of the σ-phase. The metallographic etchant capable of maximising phase contrast is then identified. Micrographic analyses are performed using different reagents at different holding times and temperatures, in order to find the best combination. A standard procedure is then defined for the image analysis. The data obtained were are processed to calculate the phase distribution. The results are compared with the quantitative analysis performed using X-ray diffraction as reference.The research evidence that Kalling's reagent is best etchant for fully solubilised materials, as it accurately estimates ferrite and austenite content. On the other hand, Marble's reagent should be preferred for the detection of σ-phase. For comprehensive analysis of all phases, Murakami's reagent is recommended.The approach defined in this paper not only improves the understanding of the microstructure of DSS, but also provides an important tool for industrial quality control and material characterisation.

Fragmentation characterization in the circular restricted three body problem for cislunar space domain awareness

With heightened international interest in spacecraft activities in the vicinity of the Moon, cislunar space debris is likely to follow. Even one fragmentation event can have catastrophic and far-reaching consequences, which drives the need for appropriate debris characterization tools. How a single fragmentation plays out is highly dependent on any given initial condition in the near-chaotic cislunar region. This paper offers a means of structuring the cislunar region in terms of dynamical flow, which enables global characterization of fragmentation events without propagation of every possible case. This work investigates patterns in fragment behaviour as a function of energy, Δv, and orbit location, and explores emergent dynamic structures in the vicinity of the Earth-Moon L2 Lagrange point. Subsequent findings are applied to analysis of a realistic breakup event for a 500 kg satellite on an L2 Lyapunov orbit with a Jacobi constant of 3.0165, modeled using an in–house modified version of the NASA Standard Breakup Model.

Study on the global and nano-scale characterization of heat-induced changes in ordinary Portland cement paste

Cement-based composite materials can be damaged by distributed micro-cracking and degradation of hydration products when exposed to sustained high temperatures. In this study, a nano-scale characterization tool (dynamic nanoindentation) and global mechanical methods (vibration resonance frequency and damping) are employed to better understand the degradation of ordinary Portland cement paste subjected to high temperature exposures. A connection between the methods is demonstrated.