3D Topography Research Articles

Multi-tasking geometric phase element array based self-referenced vortex interferometer for three-dimensional topography.

Interferometry is a basic physical method to record and reconstruct the three-dimensional (3D) topography of a complex object. However, mainstream interferometers using two beams can be unstable in a volatile environment. Here, we present a self-referenced optical vortex interferometer employing multi-tasking geometric phase elements. Compared with conventional devices, the multitasking elements can enable vortex filters while deflecting the interference beams to achieve high mode purity in broadband. We use the proposed system to reconstruct the 3D topography of a sample while determining its surface elevations and depressions accurately and conveniently in one static interference pattern.

A new optical photon transport model for application to high aspect ratio scintillation pillars

A new Monte Carlo model of optical photon transport has been developed for application to scintillation pillars with side surfaces modeled using their measured 3D topography. The model addresses deficiencies of existing models specifically pertinent to high aspect ratio scintillator geometries. Inaccuracies with these models’ description of the reflectance of scintillation photons at media boundaries are exacerbated by the high number of surface interactions in such geometries. These models rely either on (a) user-specified parameters that are challenging to set, or (b) pre-computed look-up tables that assume geometrically unconstrained photon incidence on uniform surface finishes, an assumption that is invalid in high aspect ratio geometries. Alternatively, the new model reconstructs the side surfaces of a pillar from 3D topographic measurements and uses first-principles physics of reflection and transmission to transport photons over the surfaces’ microscopic features and throughout the entire pillar volume. It takes advantage of the recent availability of open-source software capable of complex surface modeling and ray-tracing, as well as high performance computing. The model was validated against measurements of the number of photoelectrons (PEs) generated in two silicon photomultipliers (SiPMs) located at the ends of 5 mm × 5 mm × 200 mm EJ-204 scintillation pillars with different surface finishes. It was also validated against the relative amplitudes and arrival time difference of the SiPMs’ signals. The model accurately predicts the measurements as function of the scintillation position along the pillars’ length with 2% mean-absolute-percentage error (MAPE) in the number of PEs, and 16% in the relative amplitudes. The root-mean-squared error (RMSE) in the arrival time difference is 0.114 ns. The model also predicts the experimentally observed higher scintillation light collection in pillars with smoother side surfaces. A proof-of-concept code of the model is available as open source.

Glass Frit Jetting for Advanced Wafer-Level Hermetic Packaging.

Glass frit bonding is a widely used technology to cap and seal micro-electromechanical systems on the wafer level using a low melting point glass. Screen printing is the main method to apply glass frit paste on wafers. Screen printing of glass frit paste is usually performed on less sensitive, less critical wafers, normally the capping wafer, because screen printing is a rough process involving the mechanical contact of the screen printing mesh and the wafer. However, for some applications in which contactless patterning of glass frit materials on the device wafers are preferred (e.g., 3D topographies, micro-lens and optics integration) jet dispensing could be a promising approach. Consequently, in this study, wafer-level jetting of glass frit materials on silicon wafers was proposed and investigated. The jetting parameters such as jetting distance, power and temperature were optimized for a glass frit paste. Additionally, the effect of jetted pitch size on the bond-line thickness was assessed. The wafers with jetted glass frit pastes were conclusively bonded in low vacuum and characterized. As a single-step (non-contact) additive approach, the jet printing of glass frit was revealed to be a straightforward, cost-effective and flexible approach with several implications for hermetic packaging.

Design of a Venation-like Patterned Surface with Hybrid Wettability for Highly Efficient Fog Harvesting.

Inspired by Namib Desert beetle and leaf venation, a wettability-integrated system consisting of wettability-hybrid coatings and venation-like patterns was designed and successfully fabricated via a simple, low-cost, and eco-friendly route. The as-prepared surface can construct a 3D topography with a water layer and efficiently drain through the venation-like patterns. The combination of multiple mechanisms enhances the fog harvesting ability significantly. Meanwhile, the synergistic mechanisms of fog harvesting enhancement by a wettability-integrated surface were further studied and discussed.

Tribological Properties and 3D Topographic Parameters of Hard Turned and Ground Surfaces.

Precision machining of automotive industrial parts is a highlighted topic in mechanical engineering due to the increased need for efficient and high-quality machining processes. This study is aimed to contribute to the field of surface topography evaluation by analyzing tribology-related topography parameters parallelly and finding connections between them. Hard machining experiments were carried out for the widely applied case-hardened material 16MnCr5 and the 3D topography of the machined surfaces was measured and analyzed. Based on a comprehensive design of experiments cubic response functions were determined for the analyzed parameters and the coefficients of determination were calculated. It was found that the cubic response function is reliable for predicting the topography parameter values and there are strong relationships between counterpart parameters under certain circumstances The findings could help clarify the roles of the analyzed parameters in some tribological properties within the analyzed cutting circumstances.

Undeformed chip width non-uniformity modeling and surface roughness prediction in wafer self-rotational grinding process

Silicon wafers are commonly thinned employing an ultra-precision grinding machine based on a workpiece self-rotational principle. The diamond grains, stochastically located on the grinding wheel surface, remove the workpiece material and generate a difference in the size and shape of undeformed chips. However, an in-depth understanding of the grain-workpiece interaction randomness in wafer thinning process and its link with surface roughness has not been revealed yet. In this paper, a new index, i.e., undeformed chip width, is first proposed to analyze and describe the stochastic characteristics in material removal process as well as predict the surface roughness of ground wafer. The grinding wheel morphology is constructed by the random operation for grain size and position. Then, a 2D topography generation model is established to calculate the undeformed chip width. The non-uniform distribution characteristics of undeformed chip width under different grinding conditions are further analyzed. Finally, the relation between undeformed chip width and surface roughness of ground wafer is presented. The correctness of developed models is verified using a series of grinding experiments.

Application of Moire Profilometry in Three-Dimensional Profile Reconstruction of Key Parts in Railway.

Moire profilometry (MP) is one of the three-dimensional (3D) topography measurement methods of structured light, which has the advantages of single frame reconstruction, high speed, no contact and high precision, and is suitable for dynamic measurement scenes. In this article, the digital MP is applied to the wheel tread measurement, the virtual grating is generated by computer to project to the object surface, the moire fringe pattern of the object is obtained by filtering, and finally the continuous phase pattern is obtained by phase unwrapping. The 3D shape reconstruction of the wheel tread is realized, and a new method of wheel tread detection is provided. At the same time, in this paper, the results of using different filters are compared, and the significance of the frequency domain filtering to MP is proved. It is necessary to choose a suitable filtering method according to different environmental conditions. At present, digital MP can be used in industrial static detection, and it can be extended to the dynamic detection of rolling wheels in the future, so as to improve the detection efficiency and realize the automatic detection of trains.

MolNet‐3D: Deep Learning of Molecular Representations and Properties from 3D Topography

AbstractA new paradigm combining quantum‐mechanical calculations with machine learning (ML) to rationally design compounds with specific properties from extremely large chemical space is emerging and developing at a rapid pace. In this context, appropriately describing molecules and efficiently extracting patterns from electronic‐structure calculations are the core challenges for the success of the quantum‐mechanics‐based ML approaches. Here, MolNet‐3D is introduced, a strong deep learning architecture capable of mapping from a flexible and universal 3D topography descriptor to quantum‐mechanical observables of molecules of arbitrary shape. The model can learn an invariant representation without the need for the transformation of atom coordinates into interatomic distances, thus preserving the intrinsic 3D topography information of molecules. The capabilities of MolNet‐3D are shown by accurately predicting the various density functional theory calculated properties for molecules, including energetic, electronic, and thermodynamic properties. Compared with the previously proposed ML methods in the MoleculeNet benchmarks, our model generally offers the best performance in those quantum‐mechanical tasks, elucidating the importance of intrinsic topography information in molecular representation learning. This work may provide new insight into the construction of molecular ML models from 3D topography recognition perspectives.

A Constrained Assembly Strategy for High-Strength Natural Nanoclay Film.

Developing high-performance materials from existing natural materials is highly desired because of their environmental friendliness and low cost; two-dimensional nanoclay exfoliated from layered silicate minerals is a good building block to construct multilayered macroscopic assemblies for achieving high mechanical and functional properties. Nevertheless, the efforts have been frustrated by insufficient inter-nanosheet stress transfer and nanosheet misalignment caused by capillary force during solution-based spontaneous assembly, degrading the mechanical strength of clay-based materials. Herein, a constrained assembly strategy that is implemented by in-plane stretching a robust water-containing nanoclay network with hydrogen and ionic bonding is developed to adjust the 2D topography of nanosheets within multilayered nanoclay film. In-plane stretching overcomes capillary force during water removal and thus restrains nanosheet conformation transition from nearly flat to wrinkled, leading to a highly aligned multilayered nanostructure with synergistic hydrogen and ionic bonding. It is proved that inter-nanosheet hydrogen and ionic bonding and nanosheet conformation extension generate profound mechanical reinforcement. The tensile strength and modulus of natural nanoclay film reach up to 429.0 MPa and 43.8 GPa and surpass the counterparts fabricated by normal spontaneous assembly. Additionally, improved heat insulation function and good nonflammability are shown for the natural nanoclay film and extend its potential for realistic uses.

Convolutional mesh autoencoders for the 3-dimensional identification of FGFR-related craniosynostosis

Clinical diagnosis of craniofacial anomalies requires expert knowledge. Recent studies have shown that artificial intelligence (AI) based facial analysis can match the diagnostic capabilities of expert clinicians in syndrome identification. In general, these systems use 2D images and analyse texture and colour. They are powerful tools for photographic analysis but are not suitable for use with medical imaging modalities such as ultrasound, MRI or CT, and are unable to take shape information into consideration when making a diagnostic prediction. 3D morphable models (3DMMs), and their recently proposed successors, mesh autoencoders, analyse surface topography rather than texture enabling analysis from photography and all common medical imaging modalities and present an alternative to image-based analysis. We present a craniofacial analysis framework for syndrome identification using Convolutional Mesh Autoencoders (CMAs). The models were trained using 3D photographs of the general population (LSFM and LYHM), computed tomography data (CT) scans from healthy infants and patients with 3 genetically distinct craniofacial syndromes (Muenke, Crouzon, Apert). Machine diagnosis outperformed expert clinical diagnosis with an accuracy of 99.98%, sensitivity of 99.95% and specificity of 100%. The diagnostic precision of this technique supports its potential inclusion in clinical decision support systems. Its reliance on 3D topography characterisation make it suitable for AI assisted diagnosis in medical imaging as well as photographic analysis in the clinical setting.

Experimental and numerical studies of turbulent flows over two-dimensional and three-dimensional rough surfaces under an adverse pressure gradient

The effects of surface roughness and other surface topographical feature on turbulent boundary layer (TBL) development have been widely explored, especially for flow cases with a constant streamwise pressure gradient distribution. In the case where the TBL is exposed to the action of an adverse pressure gradient (APG), flow separation is expected to occur and the classical mechanisms responsible for energy transport between the inner and outer part of the TBL are invalid. The combined effect of roughness and APG on the TBL is not easy to predict, especially due to the lack of databases containing relevant research data. The main aims of the present study were to conduct experimental investigations and to perform large eddy simulations to determine the effects of different surface topographies (two-dimensional (2D) and three-dimensional (3D)) on turbulent flow development over a smooth wall under a strong APG downstream of the corrugation. The investigation was performed with a fixed value of the Reynolds number Reθ = 4900. In particular, the differences in the production and dynamics of near-wall vortical structures under different corrugation geometries were studied. It was found that the higher amplitude of 2D wavy surface the greater production of turbulence and the earlier separation of the TBL. The response of the TBL differed according to the 3D topography, where it was characterized by a greater streamwise velocity deficit, lower growth of all components of the velocity fluctuations, and a smaller increase in the normal velocity gradient relative to the 2D case with comparable amplitude. The results also demonstrated that the 3D case generated smaller and less energetic structures on the flat plate downstream of the corrugation compared with the 2D case.

Evaluation of optical properties of fluorescent nanofiber using image-processing technique

PurposeThe purpose of this study is evaluate the optical properties of polyacrylonitrile (PAN) nanofibers containing fluorescent agents such as fluorescent dye and carbon quantum dots (CQDs) by using image-processing technique of Fluorescence microscope image.Design/methodology/approachThe fluorescence microscope image of the pure PAN, PAN/CQDs and PAN/fluorescent dye nanofibers composite was analyzed using several image-processing techniques such as color histogram, lookup table (LUT), Fourier transform, RGB profile and surface plot analysis.FindingsThe fluorescence microscope image indicates that the fluorescence emission of nanocomposites depends on the type of fluorescent agent. The fluorescence intensity of nanofiber containing CQDs is more than nanofiber containing fluorescent dye. Various image-processing methods provide similar results for optical property of nanocomposites. Analyzing the LUT, the blue value of CQDs/PAN nanocomposite image was significantly higher than other nanocomposites. This was confirmed by other methods such as Fourier transform, color histogram and 3D topography of the electrospun nanofibers. According to analysis of colorimetric parameters, higher negative value of b* indicates bluer color for CQDs/PAN nanofibers than other nanocomposites. The obtained results indicate that the image-processing technique can be used to evaluate the optical property of fluorescent nanocomposite.Originality/valueThis study evaluates the optical properties of fluorescent nanocomposites by using image-processing techniques such as Fourier transform, color histogram, RGB profiles, LUT, surface plot and histogram analysis.

In-situ 3D reconstruction of worn surface topography via optimized photometric stereo

Since worn surfaces contain rich information of the wear mechanisms, in-situ measurements of surface topography can characterize ongoing wear degradation in machines. With the help of photometric stereo vision, three-dimensional (3D) topography of worn surfaces is obtained with a monocular microscope. However, the accuracy of the reconstructed surfaces remains low due to the non-Lambertian reflections of worn surfaces and noise in the image acquisition equipment. To address this issue, an optimized photometric stereo approach is proposed for the improvement of worn surface reconstruction. To accommodate the non-Lambertian reflections, a multi-branch network is constructed to estimate normal vectors from both the photometric images and the incident illumination directions. The estimated normal vectors are adopted to reconstruct worn surface topography by embedding prior knowledge. With this design, the overall distortion caused by image noise is effectively suppressed. The proposed method is verified by comparing with the Laser Scanning Confocal Microscopy (LSCM). As the main result, over 88% similarity on the worn surface roughness can be obtained.

A review of the dual-wavelength technique for phase imaging and 3D topography

Optically transmissive and reflective objects may have varying surface profiles, which translate to arbitrary phase profiles for light either transmitted through or reflected from the object. For high-throughput applications, resolving arbitrary phases and absolute heights is a key problem. To extend the ability of measuring absolute phase jumps in existing 3D imaging techniques, the dual-wavelength concept, proposed in late 1800s, has been developed in the last few decades. By adopting an extra wavelength in measurements, a synthetic wavelength, usually larger than each of the single wavelengths, can be simulated to extract large phases or height variations from micron-level to tens of centimeters scale. We review a brief history of the developments in the dual-wavelength technique and present the methodology of this technique for using the phase difference and/or the phase sum. Various applications of the dual-wavelength technique are discussed, including height feature extraction from micron scale to centimeter scale in holography and interferometry, single-shot dual-wavelength digital holography for high-speed imaging, nanometer height resolution with fringe subdivision method, and applications in other novel phase imaging techniques and optical modalities. The noise sources for dual-wavelength techniques for phase imaging and 3D topography are discussed, and potential ways to reduce or remove the noise are mentioned.

Modelling of 3D topographic parameters of machined surfaces using Artificial Neural Network regression approach

Surface Topography is very important to understand many manufacturing and industrial processes. Traditionally 2D surface characterization has been carried out in research laboratories and industries to understand the surface topography of material. However later, sophisticated instruments were developed to measure 3D surface topography parameters. Compared to 2D surface topography of material, 3D surface topography holds more detailed information. It provides insight into the 3D nature of material surface rather than its 2D cross section. Measurement of 2D parameters require less effort and investment than 3D surface parameters. A need thus exists to explore ways to identify 3D surface topography parameters from the 2D parameters which can be obtained more easily. The main objective of this paper is to estimate 3D surface topography parameters of a machined material from 2D parameters using Machine Learning techniques. The current paper focuses on the collection of data of 2D and 3D surface topography parameters for various machining processes. For the inspection of surface parameters, sophisticated 3D surface profilometer was used. The Artificial Neural Network Regression based Machine Learning model is thus proposed, implemented and rigorously tested for various machined surfaces for different operating parameters.

High resolution imaging of viruses: Scanning probe microscopy and related techniques.

Scanning probe microscopy is a group of measurements that provides 3D visualization of viruses in different environmental conditions including liquids and air. Besides 3D topography it is possible to measure the properties like mechanical rigidity and stability, adhesion, tendency to crystallization, surface charge, etc. Choosing the right substrate and scanning parameters makes it much easier to obtain reliable data. Rational interpretation of experimental results should take into account possible artifacts, proper filtering and data presentation using specially designed software packages. Animal and human virus characterization is in the focus of many intensive studies because of their potential harm to higher organisms. The article focuses on high-resolution visualization of plant viruses. Tobacco mosaic virus, potato viruses X and B and others are not dangerous for the human being and are widely used in different applications such as vaccine preparation, construction of building units in nanotechnology and material science applications, nanoparticle production and delivery, and even metrology. The methods of virus's deposition, visualization, and consequent image processing and interpretation are described in details. Specific examples of viruses imaging are illustrated using the FemtoScan Online software, which has typical and all the necessary built-in functions for constructing three-dimensional images, their processing and analysis. Despite visible progress in visualizing the viruses using probe microscopy, many unresolved problems still remain. At present time the probe microscopy data on viruses is not systemized. There is no descriptive atlas of the images and morphology as revealed by this type of high resolution microscopy. It is worth emphasizing that new virus investigation methods will appear due to the progress of science.

3D Immunofluorescent Image Colocalization Quantification in Mouse Epiblast Stem Cells.

This chapter details 3D morphological topography of colony architecture optimization and nuclear protein localization by co-immunofluorescent confocal microscopy analysis. Colocalization assessment of nuclear and cytoplasmic cell regions is detailed to demonstrate nuclear and cytoplasmic localization in mEpiSCs by confocal microscopy and orthogonal colocalization assessment. Protein colocalization within mESCs, mEpiLCs, and mEpiSCs can be efficiently completed using these optimized protocols.

Cryptographic Strain‐Dependent Light Pattern Generators (Adv. Mater. Technol. 1/2022)

Cryptographic Magic Windows In article number 2101129, Francesco Pisani, Andrea Camposeo, and colleagues introduce stretchable and 3D printed cryptographic magic windows capable of generating complex patterns, including micro-QR-codes, by refraction of light in the visible range. The information carried by a light pattern, that is encrypted in the 3D topography of the magic windows, is unveiled by projection of the light pattern on a screen.

Sliding wear behaviour of Ni-5 %Al coating deposited by detonation spray on IN718

Ni-5 %Al metallic coating was deposited on Nickel-based superalloy (IN718) specimens using the detonation spray coating (DSC) method. Detonation spraying yielded coating with extreme chemical bond strength, hardness, and less porosity. The microstructure, microhardness, and room temperature pin-on-disc sliding wear behavior of the Ni-5 %Al coating and the as-received IN718 superalloy were evaluated. Sliding wear tests were done at room temperature (25 °C), under different loading conditions (6 N and 10 N), using an alumina (Al2O3) ball-on-disk tribometer and friction coefficients were measured. The study of worn surfaces conducted by SEM indicated that both Ni-5 %Al coating and the substrate suffered significant abrasive wear with occasional adhesion and spalling of the coating. The 3D topography of the wear track was examined by a 3D non-contact profilometer, which enabled the quantification of the wear. The friction coefficient values of the tests and the wear in terms of mass loss were in good correlation.

Surface Quality in Dry Machining of CFRP Composite/Ti6Al4V Stack Laminate

The present work deals with the effect of drilling parameters on the surface quality of CFRP composite/Ti6Al4V stacks. The assembly of the carbon fiber composite and metallic materials is often carried out by means of the adhesive and autoclave joining. To analyze the effect of the composite/metallic interface on the surface quality, several drilling experiments have been performed for different drilling conditions; spindle speed, feed rate and drilling sequence are particularly investigated. Surface integrity, delamination process and cutting forces were considered as the main output responses to analyze the machining quality. SEM images and 3D topography of the machined surfaces were carried to assess the surface quality of specimens. Thus, this study aims to provide in-depth understanding of drilling and the effect of assembly method on the machinability of CFRP/Ti stacks.