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In this work, graphene oxide (GO) and epoxy-functionalized graphene oxide (GOSi) are chosen as additives and incorporated into epoxy resin (EP) for nanocomposite photo-coating films (GO/EP and GOSi/EP series). Compared to GO/EP, the GOSi/EP nanocomposite demonstrates strong binding and excellent dispersibility, highlighting covalent bonding between GOSi and the epoxy coating. Furthermore, GOSi/EP-based films demonstrated superior thermal stability and adhesion performance on galvanized steel plates. The corrosion performance of the coated galvanized steel is investigated using electrochemical impedance spectroscopy (EIS) and polarization curve analysis (Tafel). The effectiveness of corrosion protection is evaluated based on a combination of photoreactivity, crosslinking density, dispersity, and adhesion properties. Out of all the treated films, the film based on 0.1GOSi/EP exhibited the highest percentage of inhibition (98.89%) and demonstrated superior long-term anticorrosion stability. In addition, the 0.1GOSi/EP based formulation showed remarkable antibacterial activity against S. aureus, resulting in a 92% reduction. This work demonstrates the development of a facile, environmentally friendly functionalized graphene oxide/epoxy photocured film with superior dual functionalities in both anticorrosion and antibacterial properties. These advancements hold promising potential for impactful practical applications.
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STATEMENT OF PROBLEM: The complete arch implant-supported treatment concept with 2 angled implants has been widely used for the prosthetic rehabilitation of edentulous patients. While mechanical analysis plays a pivotal role in minimizing suboptimal outcomes or premature failure, it is notably time-consuming. Consequently, clinical treatment planning relies heavily on dentists' subjective judgment and an optimization process is needed. PURPOSE: The purpose of this study was to develop an optimization process for providing immediate recommendations to support decision-making in configuring complete arch implant-supported prostheses. MATERIAL AND METHODS: This research was carried out in 2 phases. The first consisted of collecting a dataset from a total of 2800 finite element simulations by randomly configuring 10 implant design variables with 4 types of mandibles. The dataset was used to train an artificial neural network to predict the biomechanical performance of a given complete arch implant-supported prosthesis design configuration. In the second phase, the artificial neural network was used as the objective function predictor in a particle swarm optimization process to enable immediate recommendations for the implant placement. The optimization process was evaluated for accuracy, computing performance, and adaptability for unseen mandibles. RESULTS: Within the specified design space, the optimization process was able to find an optimal design based on an imported mandible model in 30 seconds. The optimized designs were found to improve peri-implant stress by 11.08 ±6.43%. When verified through finite element analysis, the prediction error was found to be 10.4 ±8.1%. Furthermore, the prediction of the optimal design was highly accurate when tested on 2 unseen mandibles, yielding an error of less than 1.7%. CONCLUSIONS: The suggested approach can quickly provide an optimal implant configuration for each individual and effectively reduce the average peri-implant stress in the mandible.
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Background/purpose: Nowadays, zirconia-based framework has been used for longspan or full-arch fixed dental prostheses (FDPs). This study aimed to evaluate the effect of pontic distribution on marginal and internal gaps of five-unit anterior zirconiabased DPs. Materials and methods: Right maxillary central incisor and second premolar were selected as terminal abutments and three different edentulous conditions with one nonterminal abutment were simulated. Marginal and internal gaps in each zirconia-based samples(n = 10) were examined by computer-aided replica technique. Five regions, including marginal gaps at mesial or distal finishing line, internal gaps at the mesial or distal axial wall, and occlusal surface, were statistically analyzed (α = .05). Results: Most of marginal gaps and internal gaps at axial wall were clinically acceptable, but larger at occlusal surface. For the three experimental groups, clinically accepted percentage with qualified gaps were less than 30%.There were statistical differences at axial wall over pontic side and marginal gaps over non-pontic side between groups (P<0.05). For sum of gaps of all abutments in each group, statistical differences were found at marginal and axial wall (P < 0.05). As for those on terminal and non-terminal abutments, statistical differences were found on second premolar (P < 0.05). Conclusion: Except for occlusal surface, the overall marginal gaps and internal gaps at axial wall of five-unit anterior zirconia-based FDPs with different pontic distribution were clinically acceptable. However, the percentage with qualified gaps were low (<30%). Greater gaps were noted when adjacent pontic existed. Different pontic size and distribution with curvature had an influence on the gaps.