https://tandfonline.com/doi/pdf/10.1080/14686996.2019.1599694

New development of atomic layer deposition: processes, methods and applications.

As one of the transition metal oxides, niobium pentoxide (Nb2O5) offers a broad variety of properties that make it a potentially useful and highly applicable material in many different areas. In comparison to many other transition metal oxides, Nb2O5 has received relatively little attention, which presents a significant opportunity for future investigations aimed at fundamentally understanding this material and finding new and interesting applications for it. In this article, a general overview of Nb2O5 is presented which focuses on its fundamental properties, synthesis methods and recent applications, along with a discussion on future research directions relevant to this material.

Thin films and nanostructures of niobium pentoxide : fundamental properties, synthesis methods and applications

This paper describes the synthesis, structure, and tribological behavior of nanocomposite tungsten disulphide (WS2) solid lubricant films grown by atomic layer deposition. A new catalytic route, incorporating a diethyl zinc catalyst, was established to promote the adsorption and growth of WS2. The films were grown down to 8 nm in thickness by sequential exposures of WF6 and H2S gases in a viscous flow reactor on Si, SiO2, stainless steel, and polycrystalline Si and electroplated Ni microelectromechanical systems structures. Films were studied by cross-sectional transmission electron microscopy (XTEM) with Automated eXpert Spectral Image Analysis (AXSIA) software for X-ray spectral images and X-ray diffraction to determine the coating conformality and crystallinity. The coatings exhibited a hexagonal layered structure with predominant preferentially orientated (0 0 2) basal planes. Regardless of orientation to the substrate surface, these basal planes when sheared imparted low friction with a steady-state friction coefficient as low as 0.008 to 50,000 cycles in a dry nitrogen environment. The formation of smooth transfer films during wear provided low interfacial shear stresses during sliding thus achieving low friction and wear. The XTEM combined with AXSIA of the wear tracks identified this mechanism and the effects of vapor phase reaction by-product etching on insulating and native polycrystalline Si and Ni surfaces.

Growth, structure, and tribological behavior of atomic layer deposited tungten disulphide solid lubricant coatings with applications to MEMS.

We investigate Atomic Layer Deposition (ALD) of metal oxide on pristine and functionalized graphene. On pristine graphene, ALD coating can only actively grow on edges and defect sites, where dangling bonds or surface groups react with ALD precursors. This affords a simple method to decorate and probe single defect sites in graphene planes. We used perylene tetracarboxylic acid (PTCA) to functionalize graphene surface and selectively introduced densely packed surface groups on graphene. Uniform ultrathin ALD coating on PTCA graphene was achieved over large area. The functionalization method could be used to integrate ultrathin high-k dielectrics in future graphene electronics.

Atomic Layer Deposition of Metal Oxides on Pristine and Functionalized Graphene

ABSTRACT Fused filament fabrication (FFF) is an additive manufacturing process, which constructs physical items by fused melt material, selectively deposited layer-by-layer through a heated extrusion mechanism. Parameters’ selection and control in FFF are of utmost importance since they significantly affect the surface quality (SQ) and dimensional accuracy (DA) of the FFF printed parts. In the present paper, initially, the FFF process is briefly presented. Next, a cause-and-effect diagram exhibits the process parameters’ categorization with the SQ and DA of the manufactured parts. Then, according to the robust design theory, the process parameters are divided into three classes, i.e., the signal, the control, and the noise. This classification supports the selection of appropriate FFF printers, according to the control parameters, whereas it facilitates the optimization of the SQ and DA of printed parts, concerning the signal parameters. Finally, the impact of each parameter on SQ and DA is presented, supported by an extensive literature review. Overall, the process parameters’ optimization is critical for the SQ and DA. Therefore, they should be adjusted to achieve higher quality and less post-processing work.

Key parameters controlling surface quality and dimensional accuracy: a critical review of FFF process

https://journals.sagepub.com/doi/pdf/10.1177/0734242X21991642

Application of artificial neural networks for predicting the physical composition of municipal solid waste: An assessment of the impact of seasonal variation.

Niobium oxides (NbO, NbO2, Nb2O5), being a versatile material has achieved tremendous popularity to be used in a number of applications because of its outstanding electrical, mechanical, chemical, and magnetic properties. NbxOy films possess a direct band gap within the ranges of 3.2–4.0 eV, with these films having utility in different applications which include; optical systems, stainless steel, ceramics, solar cells, electrochromic devices, capacitor dielectrics, catalysts, sensors, and architectural requirements. With the purpose of fulfilling the requirements of a vast variety of the named applications, thin films having comprehensive properties span described by film composition, morphology, structural properties, and thickness are needed. The theory, alongside the research status of the different fabrication techniques of NbxOy thin films are reported in this work. The impact of fabrication procedures on the thin film characteristics which include; film thickness, surface quality, optical properties, interface properties, film growth, and crystal phase is explored with emphases on the distinct deposition process applied, are also described and discussed.

Preparation and Characterization of NbxOy Thin Films: A Review

Numerical simulation and optimization of p-NiO/n-TiO2 solar cell system using SCAPS

The present waste-management system in most developing countries are insufficient to combat the challenge of increasing rate of solid waste generation. Accurate prediction of waste generated through modelling approach will help to overcome the challenge of deficient-planning of sustainable waste-management. In modelling the complexity within a system, a paradigm-shift from classical-model to artificial intelligent model has been necessitated. Previous researches which used Adaptive Neuro-Fuzzy Inference System (ANFIS) for waste generation forecast did not investigate the effect of clustering-techniques and parameters on the performance of the model despite its significance in achieving accurate prediction. This study therefore investigates the impact of the parameters of three clustering-technique namely: Fuzzy c-means (FCM), Grid-Partitioning (GP) and Subtractive-Clustering (SC) on the performance of the ANFIS model in predicting waste generation using South Africa as a case study. Socio-economic and demographic provincial-data for the period 2008-2016 were used as input-variables and provincial waste quantities as output-variable. ANFIS model clustered with GP using triangular input membership-function (tri-MF) and a linear type output membership-function (ANFIS-GP1) is the optimal model with Mean Absolute Percentage Error (MAPE), Mean Absolute Deviation (MAD), Root Mean Square Error (RMSE) and Correlation Co-efficient (R2) values of 12.6727, 0.6940, 1.2372 and 0.9392 respectively. Based on the result in this study, ANFIS-GP with a triangular membership-function is recommended for modelling waste generation. The tool presented in this study can be utilized for the national repository of waste generation data by the South Africa Waste Information Centre (SAWIC) in South Africa and in other developing countries.

Prediction of municipal solid waste generation: an investigation of the effect of clustering techniques and parameters on ANFIS model performance.

Accurate diagnosis of fault and condition monitoring in a wind turbine is critical to the prevention of turbine failure and timely maintenance or repair of any affected component. Hence, intelligent strategies in fault diagnosis and condition monitoring can offer huge advantage in utility scale wind power plant. Digital twin technology has emerged as an ingenious concept which can give wind energy industry an enhanced accessibility, visibility, and availability. This article provides an overview of the application of digital twin technology in the fault diagnosis and condition monitoring of wind turbine mechanical components. The frequently used tools for digital twins and enabling technologies are identified and briefly analysed while the common mode of failure in wind turbine components were highlighted. The benefits and challenges associated with the application of this technology are discussed. In conclusion, the key issues which need to be addressed to unleash the potential of digital twin technology in fault diagnosis and condition monitoring were outlined.

Tien-Chien Jen

Papers

Application of artificial neural networks for predicting the physical composition of municipal solid waste: An assessment of the impact of seasonal variation.

Preparation and Characterization of NbxOy Thin Films: A Review

Numerical simulation and optimization of p-NiO/n-TiO2 solar cell system using SCAPS

Prediction of municipal solid waste generation: an investigation of the effect of clustering techniques and parameters on ANFIS model performance.

Overview of Digital Twin Technology in Wind Turbine Fault Diagnosis and Condition Monitoring