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Stereolithography (SLA) additive manufacturing (AM) technique has enabled the production of inconspicuous and aesthetically pleasing orthodontics that are also hygienic. However, the staircase effect poses a challenge to the application of invisible orthodontics in the dental industry. The purpose of this study is to implement chemical postprocessing technique by using isopropyl alcohol as a solvent to overcome this challenge.

Fifteen experiments were conducted using a D-optimal design to investigate the effect of different concentrations and postprocessing times on the surface roughness, material removal rate (MRR), hardness and cost of SLA dental parts required for creating a clear customized aligner, and a container was constructed for chemical treatment of these parts made from photocurable resin.

The study revealed that the chemical postprocessing technique can significantly improve the surface roughness of dental SLA parts, but improper selection of concentration and time can lead to poor surface roughness. The optimal surface roughness was achieved with a concentration of 90 and a time of 37.5. Moreover, the dental part with the lowest concentration and time (60% and 15 min, respectively) had the lowest MRR and the highest hardness. The part with the highest concentration and time required the greatest budget allocation. Finally, the results of the multiobjective optimization analysis aligned with the experimental data.

This paper sheds light on a previously underestimated aspect, which is the pivotal role of chemical postprocessing in mitigating the adverse impact of stair case effect. This nuanced perspective contributes to the broader discourse on AM methodologies, establishing a novel pathway for advancing the capabilities of SLA in dental application.

Material extrusion-based additive manufacturing is a prominent manufacturing technique to fabricate complex geometrical three-dimensional (3D) parts. Despite the indisputable advantages of material extrusion-based technique, the poor surface and subsurface integrity hinder the industrial application of this technology. The purpose of this study is introducing the hot air jet treatment (HAJ) technique for surface treatment of additive manufactured parts.

In the presented research, novel theoretical formulation and finite element models are developed to study and model the polishing mechanism of printed parts surface through the HAJ technique. The model correlates reflow material volume, layer width and layer height. The reflow material volume is a function of treatment temperature, treatment velocity and HAJ velocity. The values of reflow material volume are obtained through the finite element modeling model due to the complexity of the interactions between thermal and mechanical phenomena. The theoretical model presumptions are validated through experiments, and the results show that the treatment parameters have a significant impact on the surface characteristics, hardness and dimensional variations of the treated surface.

The results demonstrate that the average value of error between the calculated theoretical results and experimental results is 14.3%. Meanwhile, the 3D plots of Ra and Rq revealed that the maximum values of Ra and Rq reduction percentages at 255°C, 270°C, 285°C and 300°C treatment temperatures are (35.9%, 33.9%), (77.6%,76.4%), (94%, 93.8%) and (85.1%, 84%), respectively. The scanning electron microscope results illustrate three different treatment zones and the treatment-induced and manufacturing-induced entrapped air relief phenomenon. The measured results of hardness variation percentages and dimensional deviation percentages at different regimes are (8.33%, 0.19%), (10.55%, 0.31%) and (−0.27%, 0.34%), respectively.

While some studies have investigated the effect of the HAJ process on the structural integrity of manufactured items, there is a dearth of research on the underlying treatment mechanism, the integrity of the treated surface and the subsurface characteristics of the treated surface.

The research aims to investigate the impact of thermo-mechanical aging on SBR under cyclic-loading. By conducting experimental analyses and developing a 3D finite element analysis (FEA) model, it seeks to understand chemical and physical changes during aging processes. This research provides insights into nonlinear mechanical behavior, stress softening and microstructural alterations in SBR compounds, improving material performance and guiding future strategies.

This study combines experimental analyses, including cyclic tensile loading, attenuated total reflection (ATR), spectroscopy and energy-dispersive X-ray spectroscopy (EDS) line scans, to investigate the effects of thermo-mechanical aging (TMA) on carbon-black (CB) reinforced styrene-butadiene rubber (SBR). It employs a 3D FEA model using the Abaqus/Implicit code to comprehend the nonlinear behavior and stress softening response, offering a holistic understanding of aging processes and mechanical behavior under cyclic-loading.

This study reveals significant insights into SBR behavior during thermo-mechanical aging. Findings include surface roughness variations, chemical alterations and microstructural changes. Notably, a partial recovery of stiffness was observed as a function of CB volume fraction. The developed 3D FEA model accurately depicts nonlinear behavior, stress softening and strain fields around CB particles in unstressed states, predicting hysteresis and energy dissipation in aged SBRs.

This research offers novel insights by comprehensively investigating the impact of thermo-mechanical aging on CB-reinforced-SBR. The fusion of experimental techniques with FEA simulations reveals time-dependent mechanical behavior and microstructural changes in SBR materials. The model serves as a valuable tool for predicting material responses under various conditions, advancing the design and engineering of SBR-based products across industries.

The surface characteristics of thermally and chemically modified wood, such as surface roughness, surface free energy (SFE) and wettability, are important properties that influence further manufacturing processes such as gluing and coating. The aim of this paper was to determine the influence of the surface roughness of thermally and chemically modified teak wood on their SFE, wettability and bonding quality for water-based acrylic and solvent-based alkyd varnishes. In addition, durability against subterranean termites in the field of these modified teak woods was also investigated to give a valuable information for their further application.

The woods tested in this study were fast-growing teak woods that were prepared in untreated and treated with furfuryl alcohol (FA), glycerol maleic anhydride (GMA) and thermal. SFE values were calculated using the Rabel method. The wettability values were measured based on the contact angle between varnish liquids and wood surfaces using the sessile drop method, and the Shi and Gardner model model was used to evaluate the wettability of the varnishes on the wood surface. The bonding quality of the varnishes was measured using a cross-cut test based on ASTM 3359-17 standard. In addition, durability against subterranean termites in the field of these modified teak woods was also investigated according to ASTM D 1758-06.

The results showed that furfurylated and GMA-thermal 220°C improved the durability of teak wood against termites. The furfurylated teak wood had the roughest surface with an arithmetic average roughness (Ra) value of 15.65 µm before aging and 27.11 µm after aging. The GMA-thermal 220°C treated teak wood was the smoothest surface with Ra value of 6.44 µm before aging and 13.75 µm after aging. Untreated teak wood had the highest SFE value of 46.90 and 57.37 mJ/m² before and after aging, respectively. The K values of untreated and treated teak wood increased owing to the aging treatment. The K values for the water-based acrylic varnish were lower than that of the solvent-based alkyd varnish. The untreated teak wood with the highest SFE produced the highest bonding quality (grades 4–5) for both acrylic and alkyd varnishes. The solvent-based alkyd varnish was more wettable and generated better bonding quality than the water-based acrylic varnish.

The originality of this research work is that it provides evaluation values of the durability and SFE. The SFE value can be used to quantitatively determine the wettability of paint liquids on the surface of wood and its varnish bonding quality.

The purpose of this study is to investigate the structural, surface roughness and corrosion properties of the zirconium oxide thin films deposited onto SS304 substrates using the direct current (DC) magnetron sputtering technique.

DC sputtering at different powers – 80, 100 and 120 W – was used to deposit ZrO₂ thin films onto different substrates (Si/SS304) without annealing of the substrate. Atomic force microscope (AFM), energy-dispersive X-ray spectroscopy (EDS), Tafel extrapolation and contact angle techniques were applied to investigate the surface roughness, chemical compositions, corrosion behavior and hydrophobicity of these films.

Results showed that the thickness of the deposited film increased with power increase, while the corrosion current decreased with power increase. AFM images indicated that the surface roughness decreased with an increase in DC power. EDS analysis showed that the thin film has a stoichiometric ZrO₂ (Zr:O 1:2) composition with basic uniformity. Water contact angle measurements indicated that the hydrophobicity of the synthesized films decreased with an increase in surface roughness.

DC magnetron sputtering technique is infrequently used to deposition thin films. The obtained thin films showed good hydrophobic and anticorrosion properties. Finally, results are compared with other deposition techniques.

Surface roughness has a serious impact on the fatigue strength, wear resistance and life of mechanical products. Realizing the evolution of surface quality through theoretical modeling takes a lot of effort. To predict the surface roughness of milling processing, this paper aims to construct a neural network based on deep learning and data augmentation.

This study proposes a method consisting of three steps. Firstly, the machine tool multisource data acquisition platform is established, which combines sensor monitoring with machine tool communication to collect processing signals. Secondly, the feature parameters are extracted to reduce the interference and improve the model generalization ability. Thirdly, for different expectations, the parameters of the deep belief network (DBN) model are optimized by the tent-SSA algorithm to achieve more accurate roughness classification and regression prediction.

The adaptive synthetic sampling (ADASYN) algorithm can improve the classification prediction accuracy of DBN from 80.67% to 94.23%. After the DBN parameters were optimized by Tent-SSA, the roughness prediction accuracy was significantly improved. For the classification model, the prediction accuracy is improved by 5.77% based on ADASYN optimization. For regression models, different objective functions can be set according to production requirements, such as root-mean-square error (RMSE) or MaxAE, and the error is reduced by more than 40% compared to the original model.

A roughness prediction model based on multiple monitoring signals is proposed, which reduces the dependence on the acquisition of environmental variables and enhances the model's applicability. Furthermore, with the ADASYN algorithm, the Tent-SSA intelligent optimization algorithm is introduced to optimize the hyperparameters of the DBN model and improve the optimization performance.

This study aims to fabricate the acrylic-based polymeric composite coating with a hydrophobic surface associated with natural oil polyol (NOP) and polydimethylsiloxane with the incorporation of 3 Wt.% SiO₂ nanoparticle (SiO₂np) against the corrosive NaCl media.

The structural properties of the formulated polymeric composite coatings were investigated by using Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, water contact angle (WCA) and cross-hatch (X-Hatch) tests. The WCA measurement was used to study the surface wettability of the formulated polymeric composite coatings. The corrosion protection performance of the nanocomposite coated on the mild steel substrate was studied by immersing the samples in 3.5 Wt.% NaCl solution for 30 days using electrochemical impedance spectroscopy.

The enhanced polymeric composite coating system performed with an excellent increase in the WCA up to 111.1° which is good hydrophobic nature and very high coating resistance in the range of 10¹⁰ Ω attributed to the superiority of SiO₂np.

The incorporation of SiO₂np into the polymeric coating could enhance the surface roughness and hydrophobic properties that could increase corrosion protection. This approach is a novel attempt of using NOP along with the addition of SiO₂np.

This paper aims to investigate the influence of “BroncoCut-X” (copper core-ZnCu50 coating) electrode on the machining of Ti-3Al-2.5V in view of its extensive use in aerospace and medical applications. The machining parameters are selected as Spark-off Time (ST_off), Spark-on Time (ST_on), Wire-speed (S_w), Wire-Tension (WT) and Servo-Voltage (S_v) to explore the machining outcomes. The response characteristics are measured in terms of material removal rate (MRR), average kerf width (KW) and average-surface roughness (SA).

Taguchi’s approach is used to design the experiment. The “AC Progress V2 high precision CNC-WEDM” is used to conduct the experiments with ϕ 0.25 mm diameter wire electrode. The machining performance characteristics are examined using main effect plots and analysis of variance. The grey-relation analysis and fuzzy interference system techniques have been developed to combine (called grey-fuzzy reasoning grade) the experimental response while Rao-Algorithm is used to calculate the optimal performance.

The hybrid optimization result is obtained as ST_off = 50µs, ST_on = 105µs, S_w = 7 m/min, WT = 12N and S_v=20V. Additionally, the result is compared with the firefly algorithm and improved gray-wolf optimizer to check the efficacy of the intended approach. The confirmatory test has been further conducted to verify optimization results and recorded 8.14% overall machinability enhancement. Moreover, the scanning electron microscopy analysis further demonstrated effectiveness in the WEDMed surface with a maximum 4.32 µm recast layer.

The adopted methodology helped to attain the highest machinability level. To the best of the authors’ knowledge, this work is the first investigation within the considered parametric range and adopted optimization technique for Ti-3Al-2.5V using the wire-electro discharge machining.

Regular monitoring of bacteria, especially Escherichia coli, in wastewater is crucial to ensure the maintenance of public health. Amperometric detection proves to be a fast, sensitive and economically viable solution for E. coli enumeration. This paper reported a prototype amperometric sensor based on PANI-ZnO-NiO nanocomposite thin films prepared by sol–gel method and irradiated with gamma ray. The purpose of this study is to investigate the sensor performance of PANI-ZnO-NiO nanocomposite thin films to detect E. coli in water.

The films were varied with different compositions of ZnO and NiO by using the formula PANI-(ZnO)_1-x-(NiO)_x, with x = 0.2, 0.4, 0.6 and 0.8. PANI-ZnO-NiO nanocomposite thin films were characterized by using X-ray diffraction (XRD) and atomic force microscopy (AFM) to study the crystallinity and surface morphology of the films. The sensor performance was conducted using the current–voltage (I-V) measurement by testing the films in clean water and E. coli solution.

XRD diffractograms show the peaks of ZnO (1 0 0) and NiO (1 0 2). AFM analysis shows the surface roughness, and the grain size of PANI-ZnO-NiO thin films decreases when the concentration ratios of NiO increased. I-V curves show the difference in current flow, where the current in E. coli solution is higher than the clean water.

PANI-(ZnO)_1-x-(NiO)_x nanocomposite thin film with the highest concentration of ZnO performed the highest sensitivity among the other concentrations, which can be used to indicate the presence of E. coli bacteria in water.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.