•Comprehensive review of state-of-the-art cement technology and materials.•Comprehensive review of cementitious materials/composites-based AM technology.•Discussing the foremost applications of ...cementitious materials-based AM technology.•Addressing practical challenges of cementitious materials-based AM technology.•Discussing the future directions of cementitious materials-based AM technology.
From medical to aerospace applications, construction on the Earth to construction on the other planets, additive manufacturing (AM) technology, which is commonly known as 3D printing, has revolutionized manufacturing and construction industries. In other word, other Renaissance era has been started by the born of AM technology. Since the early stage, AM technology developed the initial concepts such as workforce, production time, and costs to an advanced level. With further progression and introduction of multifunctional materials to 3D printing technology, a new chapter of attempts towards mechanization in many more industries, eliminating excessive components needed for fabricated devices, and post-fabrication processes has been launched, which undoubtedly are able to push limitations forwards automation in building and construction industry. Despite of passing almost three decades since the genesis of AM technology, its application in construction industry has not reached to its real potential due to the various numbers of reasons including inappropriate available 3D printing techniques for large-scale construction, limitations in the materials, economic issue due to the expensive equipment, etc. Appearance of new 3D printing methods suitable for structural printing such as contour crafting and binder jetting, have provided new paths towards automated building and construction industry. However, in respect of material science, numerous challenges must be addressed including developing smart cementitious composites suitable for 3D structural printing, reinforcement of cementitious composites during printing process, and 3D printing of fibre-reinforced cementitious composites. Achieving to high-performance printed cementitious composites are another challenge ahead. Highly likely, construction of real habitats on the other planets such as the Mars and Moon, would not be a dream if we could cope with present hurdles in 3D structural printing and develop innovative generation of 3D printers, such as robotic 3D printers. Hence, due to the important role of cement-based materials in the future of automated construction industry, this paper makes an attempt to represent a critical review of materials and methods for AM of cementitious composites, and will address challenges and future possibilities of this beneficial field of science.
State of the art three-dimensional atomic force microscopes (3D-AFM) cannot measure three spatial dimensions separately from each other. A 3D-AFM-head with true 3D-probing capabilities is presented ...in this paper. It detects the so-called 3D-Nanoprobes CD-tip displacement with a differential interferometer and an optical lever. The 3D-Nanoprobe was specifically developed for tactile 3D-probing and is applied for critical dimension (CD) measurements. A calibrated 3D-Nanoprobe shows a selectivity ratio of 50:1 on average for each of the spatial directions
,
, and
. Typical stiffness values are kx = 1.722 ± 0.083 N/m, ky = 1.511 ± 0.034 N/m, and kz = 1.64 ± 0.16 N/m resulting in a quasi-isotropic ratio of the stiffness of 1.1:0.9:1.0 in
:
:
, respectively. The probing repeatability of the developed true 3D-AFM shows a standard deviation of 0.18 nm, 0.31 nm, and 0.83 nm for
,
, and
, respectively. Two CD-line samples type IVPS100-PTB, which were perpendicularly mounted to each other, were used to test the performance of the developed true 3D-AFM: repeatability, long-term stability, pitch, and line edge roughness and linewidth roughness (LER/LWR), showing promising results.
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•3D printing technology for production of low-cost 3D graphene electrodes.•Electrochemical oxidation/reduction pre-treatments for improvement of the electron transfer kinetics.•3D ...printed electrode for electrocatalytic detection of dopamine.
3D printing has been reported as a remarkable technology for development of electrochemical devices, due to no design constraints, waste minimization and, most importantly, fast prototyping. The use of 3D printed electrodes for electroanalytical applications is still a challenge and demand efforts. In this work, we have developed low-cost and reproducible 3D-printed graphene electrodes for electrocatalytic detection of dopamine. Electrocatalytic features were enhanced after electrochemical pre-treatment. The oxidation and reduction at different potential ranges, in 0.1 mol L−1 phosphate buffer solution (pH = 7.4), are used to modulate the structural and morphological characteristics of the electrodes. Since, the electrochemical properties of the electrodes, including electron transfer kinetic and the electrocatalytic activity, are strongly influenced by electronic properties and the presence of functional groups. Raman spectroscopy, SEM and AFM microscopes and electrochemical techniques were used to characterize the 3D electrodes before and after the electrochemical pre-treatments. Finally, the performances of the 3D-printed graphene electrodes were evaluated towards dopamine sensing. The best performance was achieved by oxidation at + 1.8 V vs. SCE for 900 s and reduction from 0.0 V to -1.8 V vs. SCE at 50 mV s−1. The proposed sensor presented linear response from 2.0 μmol L−1 to 10.0 μmol L−1, with detection limit of 0.24 μmol L−1.
Depth sensing is crucial for 3D reconstruction and scene understanding. Active depth sensors provide dense metric measurements, but often suffer from limitations such as restricted operating ranges, ...low spatial resolution, sensor interference, and high power consumption. In this paper, we propose a deep learning (DL) method to estimate per-pixel depth and its uncertainty continuously from a monocular video stream, with the goal of effectively turning an RGB camera into an RGB-D camera. Unlike prior DL-based methods, we estimate a depth probability distribution for each pixel rather than a single depth value, leading to an estimate of a 3D depth probability volume for each input frame. These depth probability volumes are accumulated over time under a Bayesian filtering framework as more incoming frames are processed sequentially, which effectively reduces depth uncertainty and improves accuracy, robustness, and temporal stability. Compared to prior work, the proposed approach achieves more accurate and stable results, and generalizes better to new datasets. Experimental results also show the output of our approach can be directly fed into classical RGB-D based 3D scanning methods for 3D scene reconstruction.
TopNet: Structural Point Cloud Decoder Tchapmi, Lyne P.; Kosaraju, Vineet; Rezatofighi, Hamid ...
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),
2019-June
Conference Proceeding
3D point cloud generation is of great use for 3D scene modeling and understanding. Real-world 3D object point clouds can be properly described by a collection of low-level and high-level structures ...such as surfaces, geometric primitives, semantic parts,etc. In fact, there exist many different representations of a 3D object point cloud as a set of point groups. Existing frameworks for point cloud genera-ion either do not consider structure in their proposed solutions, or assume and enforce a specific structure/topology,e.g. a collection of manifolds or surfaces, for the generated point cloud of a 3D object. In this work, we pro-pose a novel decoder that generates a structured point cloud without assuming any specific structure or topology on the underlying point set. Our decoder is softly constrained to generate a point cloud following a hierarchical rooted tree structure. We show that given enough capacity and allowing for redundancies, the proposed decoder is very flexible and able to learn any arbitrary grouping of points including any topology on the point set. We evaluate our decoder on the task of point cloud generation for 3D point cloud shape completion. Combined with encoders from existing frameworks, we show that our proposed decoder significantly outperforms state-of-the-art 3D point cloud completion methods on the Shapenet dataset.
3D cell-printing technique has been under spotlight as an appealing biofabrication platform due to its ability to precisely pattern living cells in pre-defined spatial locations. In skin tissue ...engineering, a major remaining challenge is to seek for a suitable source of bioink capable of supporting and stimulating printed cells for tissue development. However, current bioinks for skin printing rely on homogeneous biomaterials, which has several shortcomings such as insufficient mechanical properties and recapitulation of microenvironment. In this study, we investigated the capability of skin-derived extracellular matrix (S-dECM) bioink for 3D cell printing-based skin tissue engineering. S-dECM was for the first time formulated as a printable material and retained the major ECM compositions of skin as well as favorable growth factors and cytokines. This bioink was used to print a full thickness 3D human skin model. The matured 3D cell-printed skin tissue using S-dECM bioink was stabilized with minimal shrinkage, whereas the collagen-based skin tissue was significantly contracted during in vitro tissue culture. This physical stabilization and the tissue-specific microenvironment from our bioink improved epidermal organization, dermal ECM secretion, and barrier function. We further used this bioink to print 3D pre-vascularized skin patch able to promote in vivo wound healing. In vivo results revealed that endothelial progenitor cells (EPCs)-laden 3D-printed skin patch together with adipose-derived stem cells (ASCs) accelerates wound closure, re-epithelization, and neovascularization as well as blood flow. We envision that the results of this paper can provide an insightful step towards the next generation source for bioink manufacturing.
Three-dimensional printed electrodes seem to overcome many structural and operational limitations compared to ones fabricated with conventional methods. Compared to other 3D printing techniques, ...direct ink writing (DIW), as a sub-category of extrusion-based 3D printing techniques, allows for easier fabrication, the utilization of various materials, and high flexibility in electrode architectures with low costs. Despite the conveniences in fabrication procedures that are facilitated by DIW, what qualifies an ink as 3D printable has become challenging to discern. Probing rheological ink properties such as viscoelastic moduli and yield stress appears to be a promising approach to determine 3D printability. Yet, issues arise regarding standardization protocols. It is essential for the ink filament to be extruded easily and continuously to maintain dimensional accuracy, even after post-processing methods related to electrode fabrication. Additives frequently present in the inks need to be removed, and this procedure affects the electrical and electrochemical properties of the 3D-printed electrodes. In this context, the aim of the current review was to analyze various energy devices, highlighting the type of inks synthesized and their measured rheological properties. This review fills a gap in the existing literature. Thus, according to the inks that have been formulated, we identified two categories of DIW electrode architectures that have been manufactured: supported and free-standing architectures.
•Explained the basic principles of structured light technologies.•Surveyed the major high-speed 3D shape measurement techniques based on structured light methods.•Demonstrated comparing experimental ...and representative data for some popular methods.
High-speed 3D shape measurement (or imaging) has seen tremendous growths over the past decades, especially the past few years due to the improved speed of computing devices and reduced costs of hardware components. 3D shape measurement technologies have started penetrating more into our daily lives than ever before with the recent release of iPhone X that has an built-in 3D sensor for Face ID, along with prior commercial success of inexpensive commercial sensors (e.g., Microsoft Kinect). This paper overviews the primary state-of-the-art 3D shape measurement techniques based on structured light methods, especially those that could achieve high measurement speed and accuracy. The fundamental principles behind those technologies will be elucidated, experimental results will be presented to demonstrate capabilities and/or limitations for those popular techniques, and finally present our perspectives on those remaining challenges to be conquered to make advanced 3D shape measurement techniques ubiquitous.
Network-on-chips (NoCs) have been widely employed in the design of multiprocessor system-on-chips (MPSoCs) as a scalable communication solution. NoCs enable communications between on-chip ...Intellectual Property (IP) cores to perform a task seamlessly collaborating among them. Mapping and Scheduling methodologies are key elements in assigning application tasks, allocating the tasks to the IPs, and organizing communication among them to achieve some specified objectives. The goal of this paper is to present detailed state-of-the-art research in the field of mapping and scheduling of applications on 3D NoC, classify the works based on several parameters, and provide some potential research directions.
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