3D Surface Research Articles

Observation of dynamic nanoscale thermal expansion in mirrors and graphene-aided heat dissipation by an advanced chromatic confocal microscopy

In this Letter, dynamic nano-thermal expansion images of reflective mirrors from high-intensity incident laser beams were observed in situ. The inspections are based on rapid 3D surface morphology changes on the reflective surfaces, captured by a Chromatic Confocal Microscope with Nanoscale Sensitivity (CCMNS). Nano-expansions of two types of coatings were studied: the E02 dielectric coating (coating 1) and the graphene-on-E02 complex film (coating 2), both applied to the same fused silica substrate. The superior thermal dissipation properties of coating 2, including enhanced heat dissipation, suppressed wavefront distortion, and its unique negative expansion coefficient, were observed. In addition to studying the effects of graphene coating, the CCMNS demonstrates an accurate and efficient approach for evaluating reflective mirrors. Moreover, the proposed methodology possesses enormous potential across various fields, ranging from estimating photonic elements dealing with high-intensity beams to physical thermal conductivity measurements.

Large Area Freestanding Au Nanoporous Ultrathin Films Transfer Printed on Bendable Substrates and 3D Surfaces for Flexible Electronics

Large Area Freestanding Au Nanoporous Ultrathin Films Transfer Printed on Bendable Substrates and 3D Surfaces for Flexible Electronics

Impact of surface topography and hydrophobicity in varied precursor concentrations of tenorite (CuO) films: a study of film properties and photocatalytic efficiency

Semiconductor films are crucial in photocatalysis applications, yet their controlled production remains challenging. Previous studies have mainly focused on deposition processes, heating rates, and doping of semiconductor oxides. In this paper, we introduce a novel method for fabricating tenorite (CuO) semiconductor films with varying precursor concentrations (0.01, 0.02, 0.04, 0.06, and 0.1 g/ml) using a dip-coating technique. We explore the impact of contact angles, 3D surface topography, and film thickness on photoactivation properties, areas with limited previous research focus. The results demonstrate that higher-concentration tenorite films (0.1 g/ml) exhibit rougher surfaces (77.3 nm), increased hydrophobicity (65.61°), improved light-harvesting ability, enhanced charge separation, and higher active oxygen output. The crystal sizes were within the range of 7.3–44.1 nm. Wettability tests show a 21.47% improvement in the 0.1 g/ml film surface under indirect sunlight compared to darkness. Transmittance rates in the 600 nm range were from 0.02 to 90.94%. The direct optical band gaps were 1.21–2.74 eV, while the indirect band gaps remained unaffected (0.9–1.11 eV). Surface morphology analysis reveals an increased presence of grains with higher concentrations. Regarding photocatalysis's impact on film morphology and copper content, SEM images reveal minimal changes in film structure, while copper content remains stable with slight variations. This suggests strong adhesion of tenorite to the film after photocatalysis. Tenorite thin films display exceptional photocatalytic efficiency, making them suitable for practical applications.

Optimization and Detergent Compatibility of Protease Produced from Aspergillus oryzae by Utilizing Agro Wastes.

The biotechnological process called solid-state fermentation (SSF) was applied for hyper production of protease by using a fungal strain called Aspergillus oryzae. From screening of 9 different local substrates (peanut shell, wheat bran, guava leaves, sugar cane bagasse, rice polish, wheat straw, corn straw, reed grass, and rice straw), peanut shells serve as the best substrates for protease production under optimized cultured conditions. The varying physiochemical parameters such as pH (2-9.5), temperature (30-52 °C), incubation time (1-10 days), inoculum size (1-8 mL), moisture level (20-125%), and substrate concentration (1-7 g) were optimized by response surface methodology (RSM). The highest activity of protease was recorded to be 1101.778 U/mL at 660 nm using peanut shell was optimum at pH 8, temperature 52 °C, incubation time 8 days, inoculum size 2 mL, moisture level 20%, and substrate concentration 2 g. The crude form of enzymes produced were further purified through ammonium sulfate precipitation, dialysis, and gel filtration chromatography. Then, purified enzymes were characterized at different pH, temperature, and incubation time. For characterization of purified protease, pH, temperature, and incubation time were 8, 52 °C, and 8 days for peanut shell and was done by one factor at a time method. Hence, isolated enzymes were alkaline in nature, i.e., alkaline proteases. Then, protease produced from peanut shells was applied to locally available detergents to increase their catalytic activity for strain removal. At last, the final results were interpreted in the form of 3D surface and contour plots using Microsoft Excel 2013 and Minitab 17 software. In conclusion, the utilization of A. oryzae and peanut shell as the substrate in the biotechnological process of SSF demonstrated successful hyper production of alkaline protease. The optimized conditions resulted in high enzyme activity and showcased the potential application of the isolated enzymes in improving the catalytic activity of locally available detergents.

Numerical Characterization of Prestall Disturbances in a Compressor Stage

Abstract Compared to the subject of rotating stall, less attention has been given to prestall flow disturbances in turbomachinery. This is mostly due to the fact that these phenomena, often referred to as Rotating Instabilities, do not necessarily or distinctly occur in every compressor and usually last for a long period without posing serious threats to stable operation. The present study aims at numerically characterizing prestall disturbances in detail in a compressor stage in which they have been experimentally observed. Full-annulus computational fluid dynamics (CFD) computations employing a hybrid scale-resolving turbulence model are performed and compared against unsteady experimental data. Assessment of specific prestall disturbance metrics, including power spectral density, coherence, and circumferential mode distribution at the rotor clearance, shows that the numerical model is successful in reproducing the unsteady phenomena close to stall inception. Moreover, dynamic mode decomposition is employed to directly link each peak of the unique prestall disturbance spectral signature to spatial structures with a different circumferential order. This procedure is done for both 1D circumferential modes, based on flush-mounted pressure probes, and for 2D surfaces exposing the tip clearance dynamics. The high-resolution numerical model, supplemented with vortex identification criteria and data-driven decompositions, enhances the understanding of prestall disturbances and their associated coherent flow structures.

Distinct Quantum States in Topological Insulator Surfaces of Nanowires and Nanoribbons of Bismuth Selenide (Bi2Se3)

AbstractTopological insulators (TIs) exhibit unconventional quantum phases that can be tuned by external quantum confinements. The geometry of the surface of 3D TIs plays a crucial role. For example, the geometrical crossover from 2D surfaces to a 1D cylinder results in a novel state with a Spin‐Berry Phase (SBP). Surface‐Enhanced Raman Scattering (SERS) with a sub‐micron spatial resolution is utilized to study the quantum‐confinement effects of quasi‐relativistic electrons along the perimeter of the circular bismuth selenide (Bi2Se3) nanowires. The presence of diameter‐dependent SERS in nanowires can be attributed to the self‐interference effect of the electronic wave‐function along the circumferential direction of the TI nanowires. Nanoribbons with rectangular cross‐section do not show this effect. Further gold nanoparticles are applied as plasmonic SERS sensors attached to the distinct topological surface states to manipulate quasi‐relativistic surface states of nanoribbons and nanowires. This technique enables to discriminate between different geometries of TI surface states and also opens a novel pathway to probe the quantum properties of topological surface states.

First-principles prediction on the structural stability, electronic, optical and mechanical properties of TiBC, Ti6Si2B and Ti6Ge2B

The crystal structure stability, mechanical, optical and thermodynamic properties of TiBC, Ti6Si2B and Ti6Ge2B were predicted using the first principles calculations. The analysis of phonon dispersion curves, formation enthalpies, energy bands, and density of states demonstrate that TiBC, Ti6Si2B and Ti6Ge2B exhibit structure stability and metallic properties. The tensile strength of TiBC, Ti6Si2B and Ti6Ge2B were simulated, the results showed that the tensile strength of TiBC was the best. Anisotropy was explored by anisotropy index, 3D surface constructions and 2D projections. The order of anisotropy is TiBC > Ti6Ge2B > Ti6Si2B. The optical properties showed that TiBC, Ti6Si2B and Ti6Ge2B have strong long-wave absorption capacity. Finally, Debye temperature and sound velocity were investigated, the order of Debye temperature is: TiBC > Ti6Si2B > Ti6Ge2B.

A 3D surface wave attenuation method based on dispersion curve analysis and its application

A 3D surface wave attenuation method based on dispersion curve analysis and its application

Registration of Longitudinal Spine CTs for Monitoring Lesion Growth.

Accurate and reliable registration of longitudinal spine images is essential for assessment of disease progression and surgical outcome. Implementing a fully automatic and robust registration is crucial for clinical use, however, it is challenging due to substantial change in shape and appearance due to lesions. In this paper we present a novel method to automatically align longitudinal spine CTs and accurately assess lesion progression. Our method follows a two-step pipeline where vertebrae are first automatically localized, labeled and 3D surfaces are generated using a deep learning model, then longitudinally aligned using a Gaussian mixture model surface registration. We tested our approach on 37 vertebrae, from 5 patients, with baseline CTs and 3, 6, and 12 months follow-ups leading to 111 registrations. Our experiment showed accurate registration with an average Hausdorff distance of 0.65 mm and average Dice score of 0.92.

Analytical investigation of space–time shifted nonlocal stochastic Sasa–Satsuma equation using the enhanced modified extended tanh-expansion method for stochastic solitary waves Solutions

In this paper, discover exact solutions of the space–time shifted nonlocal stochastic Sasa–Satsuma equations using the enhanced modified extended tanh-expansion method. This method is a sophisticated mathematical approach for analytical and approximate solution of a nonlinear partial differential equations. The space–time shifted nonlocal stochastic Sasa–Satsuma equations define the behavior of two complex-valued functions, u and v, in a nonlinear system. These equations are complicated to solve analytically because they contain a number of components that describe space–time shifting, nonlocal interactions, and stochastic problems. To increase reliability and effectiveness of the solutions, this method couples the extended tanh-function method with an enhanced method. In order to demonstrate how white noise affects the solutions to the space–time shifted nonlocal stochastic Sasa–Satsuma equations, we also use Matlab to create 3D surfaces and contour graphs of exact solutions.

The production of electrodes for microsupercapacitors based on MoS2-modified reduced graphene aerogels by 3D printing

Micro-supercapacitors (MSCs) are of interest because of their high power density and excellent cycling performance, offering a broad array of potential applications. However, preparing electrodes for the MSCs with an extremely high areal capacitance and energy density remains a challenge. We constructed MSC electrodes with an ultra-high area capacitance and a high energy density, using reduced graphene oxide aerogel (GA) and MoS2 as the active materials, combined with 3D printing and surface modification. Using 3D printing, we obtained electrodes with a stable macrostructure and a GA-crosslinked micropore structure. We also used a solution method to load the surface of the printed electrode with molybdenum disulfide nanosheets, further improving the electrochemical performance. The surface capacitance of the electrode reached 3.99 F cm−2, the power density was 194 W cm−2, and the energy density was 1 997 mWh cm−2, confirming its excellent electrochemical performance and cycling stability. This work provides a simple and efficient method for preparing MSC electrodes with a high areal capacitance and energy density, making them ideal for portable electronic devices.

Design, synthesis, and applications of nucleic acid-specific benzoxazole-N,N-dialkylphenylamines derivatives for nucleolus imaging in the cells

Considered the brain of the nucleus, alterations in the structure and function of the nucleolus are linked to numerous cellular functions and, consequently, contribute to several diseases. The identification of nucleolar morphology and activity via novel biomarkers presents new avenues for the development of therapeutic approaches for a variety of human diseases, including cancer, neurodegeneration, and aging. Therefore, specific detection of the nucleolus with fluorescence probes is of critical importance for clinical applications. In the present study, a series of benzoxazole-N,N-dialkylphenylamines derivative compounds were designed and synthesized based on the benzothiazole-based fluorescence probe Thioflavin T (ThT). Among the compounds, BX-3 and BX-16, which carry electron-withdrawing substituents in the benzoxazole ring, were observed to have higher fluorescence emission at wavelengths of 470 and 465 nM, respectively. The general morphology and divisions of the cells were examined under inverted and light microscopes, respectively, and the fluorescence potentials of selected compounds were determined using immunofluorescence microscopy. The fluorescence intensity of molecules and 3D interactive surface plot images of cells were analyzed using ImageJ software. Cell imaging analyses showed that BX-6 and BX-13, like ThT, specifically stain the cell nucleolus. Moreover, molecular docking studies showed that the compounds could identify the RNA-rich nucleolus by binding with high affinity to the guanine region in the RNA structure. The results suggest that the compounds may be an initial route in developing specific biosensor compounds for nucleolus imaging.

Three-dimensional imaging of the forearm and hand: A comparison between two 3D imaging systems.

The conventional treatment for distal radius fractures typically involves immobilization of the injured extremity using a conventional forearm cast. These casts do cause all sorts of discomfort during wear and impose life-style restrictions on the wearer. Personalized 3D printed splints, designed using three-dimensional (3D) imaging systems, might overcome these problems. To obtain a patient specific splint, commercially available 3D camera systems are utilized to capture patient extremities, generating 3D models for splint design. This study investigates the feasibility of utilizing a new camera system (SPENTYS) to capture 3D surface scans of the forearm for the design of 3D printed splints. In a prospective observational cohort study involving 17 healthy participants, we conducted repeated 3D imaging using both the new (SPENTYS) and a reference system (3dMD) to assess intersystem accuracy and repeatability. The intersystem accuracy of the SPENTYS system was determined by comparison of the 3D surface scans with the reference system (3dMD). Comparison of consecutive images acquired per device determined the repeatability. Feasibility was measured with system usability score questionnaires distributed among professionals. The mean absolute difference between the two systems was 0.44 mm (SD:0.25). The mean absolute difference of the repeatability of the reference -and the SPENTYS system was respectively 0.40 mm (SD: 0.30) and 0.53 mm (SD: 0.25). Both repeatability and intersystem differences were within the self-reported 1 mm. The workflow was considered easy and effective, emphasizing the potential of this approach within a workflow to obtain patient specific splint.

Comparative study of different machine learning approaches for predicting the compressive strength of palm fuel ash concrete

Nowadays, the challenge of industrialising concrete is to produce economical, ecological and efficient concrete. As a result, cementitious additions are increasingly used in concrete binders with proportions conferring the desired properties, particularly compressive strength. Palm oil fuel ash (POFA) from palm trees is one of these additions and introduced by substitution of cement in concrete. Although laboratory tests applied to concrete samples are expensive and time-consuming, considerable research is directed towards modelling approaches and machine learning (ML) applications. The purpose of this study is to explore different ML techniques, including artificial neural network (ANN), ANN with combined inputs (ANNX), particle swarm optimisation (PSO) and genetic algorithm (GA). These techniques are used to predict the compressive strength of POFA concrete derived from a dataset consisting of 249 samples with regard to 6 input parameters, namely, cement and POFA contents, aggregate ratio, water-to-binder ratio, superplasticiser dosage and curing duration. The performance of these techniques is evaluated using six performance indices: correlation coefficient, Willmott index of agreement, Nash–Sutcliffe efficiency, root mean squared error, mean absolute error and mean squared relative error. The comparison shows that ANN and ANNX have better predictive accuracy than PSO and GA, and ANNX performs relatively better than ANN. Results are presented using a 3D surface response plot which visually depicts the relationship between predicted outcomes and influential parameters. The comparison made between ANNX and other models in the literature demonstrated that the present model is reliable to predict CS of POFA concrete with high precision in a wide range of data.

LDBM-PFR: Local Directional Binary Pattern Mixed Filtering for 2D and 3D Palmprint Fusion Recognition

<p>Single-dimensional palmprint images are susceptible to interference from noise, lighting, and various factors, leading to information loss and subpar recognition performance. To address the problem, a fusion recognition scheme of 2D and 3D palmprints based on Hybrid Filter Local Orientation Binary Pattern (HFLOBP) is proposed. Firstly, the HFLOBP algorithm is employed to extract 2D features and 3D Shape Index (SI) features respectively to improve the recognition effect. Secondly, Principal Component Analysis (PCA) is utilized to improve the recognition efficiency, to reduce the dimension of 2D features and 3D Surface Type (ST) features of palmprint, to improve the recognition efficiency. Finally, the multi-dimensional palmprint features are fused by Double Weight Threshold Algorithm (DWTA), and classified and recognized by Collaborative Representation (CR). Experimental results conducted on the 3D palmprint database of Hong Kong Polytechnic University reveal that, in comparison with alternative classification methods, the average recognition rate reaches 99.98%, with an average recognition time of 0.64 seconds. The proposed method not only demonstrates a commendable recognition effect but also meets the real-time requirements, underscoring its practical application value.</p> <p> </p>

The Effect of Non-Invasive Treatment Techniques on the Color Masking Ability and Surface Roughness of Induced Enamel Lesions (An in vitro Study).

The aim of this in vitro study was to evaluate the effect of the resin infiltration technique and remineralization of induced enamel caries with fluoride solution on the color masking of white spot lesions and surface roughness. A total of 45 sound teeth were used in this study. All the teeth were sectioned along the long axes into two halves, lingual and buccal to get 90 specimens. All specimens were immersed in a demineralized solution for 7 days. The specimens were divided randomly into three equal groups (n = 30) according to the type of treatment; Group 1 (n = 30) was treated with fluoride varnish (Clinpro); Group 2 (n = 30) was treated by resin infiltration (Icon); and Group 3 (n = 30) was used as a control group with no treatment. The color and surface roughness were measured three times at baseline (T1), directly after induction of artificial white spot lesions (WSLs) (T2), and directly after application of the treatment options (T3). The colors were measured using a portable reflective spectrophotometer and the 3D surface roughness was measured using a Light Sectioning Vision System. Data were collected and statistically analyzed using T test and Mann-Whitney U test. Surface roughness was almost equal in the study groups with no statistically significant differences reported. Icon showed slightly higher color scores than that of ClinPro. The Icon produced favorable esthetic results compared to the fluoride therapy while no significant differences were reported regarding the surface roughness.

New Conformable P-Type $(3+1)$-Dimensional Evolution Equation and its Analytical and Numerical Solutions

The paper examines the conformable nonlinear evolution equation in $(3+1)$-dimensions. First, basic definitions and characteristics for the conformable derivative are given. Then, the modified extended tanh-function and $\exp(–\phi(\xi))$-expansion techniques are utilized to determine the exact solutions to this problem. The consequences of some of the acquired data's physical 3D and 2D contour surfaces are used to demonstrate the findings, providing insight into how geometric patterns are physically interpreted. These solutions help illustrate how the studied model and other nonlinear representations in physical sciences might be used in real-world scenarios. It is clear that these methods have the capacity to solve a large number of fractional differential equations with beneficial outcomes.

A Rapid Segmentation Method of Highway Surface Point Cloud Data Based on a Supervoxel and Improved Region Growing Algorithm

Mobile laser scanning (MLS) systems have become an important technology for collecting and measuring road information for highway maintenance and reconstruction services. However, the efficient and accurate extraction of unstructured road surfaces from MLS point cloud data collected on highways is challenging. Specifically, the complex and unstructured characteristics of road surveying point cloud data lead to traditional 3D point cloud segmentation. When traditional 3D point cloud algorithms extract unstructured road surfaces, over-segmentation and under-segmentation often occur, which affects efficiency and accuracy. To solve these problems, this study introduces an enhanced road extraction method that integrates supervoxel and trajectory information into a traditional region growing algorithm. The method involves two main steps: first, a supervoxel data structure is applied to reconstruct the original MLS point cloud data, which diminishes the calculation time of the point cloud feature vector and accelerates the merging speed of a similar region; second, the trajectory information of the vehicle is used to optimize the seed selection strategy of the regio growing algorithm, which improves the accuracy of road surface extraction. Finally, two typical highway section tests (flat road and slope road) were conducted to validate the positioning performance of the proposed algorithm in an MLS point cloud. The results show that, compared with three kinds of traditional road surface segmentation algorithms, our method achieves an average extraction recall and precision of 99.1% and 96.0%, and by calculating the recall and precision, an F1 score of 97.5% can be obtained to evaluate the performance of the proposed method, for both datasets. Additionally, our method exhibits an average road surface extraction time that is 45.0%, 50.3%, and 55.8% faster than those of the other three automated segmentation algorithms.

Derivation of 3D Coseismic Displacement Field from Integrated Azimuth and LOS Displacements for the 2018 Hualien Earthquake

A 3D surface deformation field for an earthquake can aid in understanding fault behaviors and earthquake mechanisms. However, SAR-based 3D surface deformation estimates are often limited by insufficient observations and hampered by various error sources. In this study, we demonstrate the derivation of a 3D coseismic displacement field from different InSAR processing algorithms. The azimuth displacements from Multiple Aperture Interferometry (MAI) and Pixel Offset Tracking (POT) were integrated to ensure reliable displacements at low coherent areas. The 3D displacement field was inverted pixel-by-pixel by Line-of-Sight (LOS) displacement and integrated azimuth displacement. The results showed that MAI and POT could compensate for the weaknesses of each algorithm. Also, pixels with less than three sets of observations showed higher noise levels. Such noisy pixels were removed by a denoising criterion proposed herein. For the vertical direction, the proportion of pixels inverted with two sets of azimuth and one set of LOS displacements was 26.1%. After denoising, the proportion dropped to 2.4% due to the insufficiency of LOS displacements. This shows that the viewing angle influences the overall performance of 3D surface displacement inversion. Implementing various displacement vectors should reduce such limitations.

Enhancing dielectric passivation on monolayer WS2 via a sacrificial graphene oxide seeding layer

The full utilization of two-dimensional transition metal dichalcogenides (2D TMDCs) faces several challenges, among which is realizing uniform material deposition on the 2D surface. Typical strategies to enable material growth lead to a poor interface quality, degrading the 2D TMDC’s properties. In this work, a sacrificial, graphene oxide-based seeding layer is used (1) as passivation layer, protecting the underlying 2D TMDC and (2) as nucleation layer, enabling uniform material growth. Graphene is transferred on monolayer WS2, establishing a high-quality van der Waals interface. After transfer, the polymeric residues on graphene are cleaned via a combination of wet- and dry treatments and functionalized via dry UV/O3 oxidation. The rate of graphene oxidation is shown to be substrate dependent, which is explained by UV light-induced ultrafast charge transfer between the graphene and WS2 monolayer. The carbon-oxygen functionalities serve as nucleation sites in a subsequent HfO2 ALD process, achieving more uniform dielectric growth and faster layer closure compared to direct deposition. The graphene-based nucleation- / passivation approach offers adaptability, allowing for tailored surface chemistry to enable any alternative material growth, while maintaining a prefect van der Waals interface.