Recent years have witnessed an explosive surge in dental research related to artificial intelligence (AI). These applications have optimised dental workflows, demonstrating significant clinical importance. Understanding the current landscape and trends of this topic is crucial for both clinicians and researchers to utilise and advance this technology. However, a comprehensive scientometric study regarding this field had yet to be performed. A literature search was conducted in the Web of Science Core Collection database to identify eligible "research articles" and "reviews." Literature screening and exclusion were performed by 2 investigators. Thereafter, VOSviewer was utilised in co-occurrence analysis and CiteSpace in co-citation analysis. R package Bibliometrix was employed to automatically calculate scientific impacts, determining the core authors and journals. Altmetric data were described narratively and supplemented with Spearman correlation analysis. A total of 1558 research publications were included. During the past 5 years, AI-related dental publications drastically increased in number, from 36 to 581. Diagnostics and Scientific Reports published the most articles, whereas Journal of Dental Research received the highest number of citations per article. China, the US, and South Korea emerged as the most prolific countries, whilst Germany received the highest number of citations per article (23.29). Charité Universitätsmedizin Berlin was the institution with the highest number of publications and citations per article (29.16). Altmetric Attention Score was correlated with News Mentions (P < .001), and significant associations were observed amongst Dimension Citations, Mendeley Readers, and Web of Science Citations (P < .001). The publication numbers regarding AI-related dental research have been rising rapidly and may continue their upwards trend. China, the US, South Korea, and Germany had promoted the progress of AI-related dental research. Disease diagnosis, orthodontic applications, and morphology segmentation were current hotspots. Attention mechanism, explainable AI, multimodal data fusion, and AI-generated text assistants necessitate future research and exploration.

Zirconia is a material that mimics human teeth and has been extensively studied and applied. This study investigated the surface modifications of dental zirconia induced by two UV-C wavelengths (222 and 254 nm). A total of 72 zirconia specimens were prepared and divided into groups for irradiation at varying distances (1, 6, 12 cm) and durations (40, 120, 480 and 1440 min), with three specimens retained as untreated controls. Surface changes were assessed by measuring colour difference (ΔE) and water contact angle, and by analyzing surface morphology and elemental composition using SEM and EDX, and XRD was employed to determine the crystalline structure. The results showed that both wavelengths induced clinically perceptible colour changes (ΔE > 2.0), with the most pronounced effect at 6 cm for 222 nm and 1 cm for 254 nm. WCA decreased significantly with irradiation time, showing a linear correlation with log(time), and 222 nm irradiation yielded lower WCA than 254 nm. While SEM revealed no morphological changes, both UV treatments significantly increased the Zr/O ratio compared to the control. XRD tests confirmed that UV-C irradiation does not damage the zirconium oxide crystal structure. It is concluded that both UV-C wavelengths can alter the colour and enhance the wettability of zirconia; these modifications are particularly relevant for dental restorative applications, specifically in the fabrication of anterior tooth crowns, where achieving a natural tooth-like appearance is desired.