RESUMO
3,4-Bis(3-nitrofurazan-4-yl)furoxan (DNTF) is a novel energetic material with an excellent performance and has attracted considerable attention. Motivated by recent theories and experiments, we had carried out experimental and theoretical studies on the high-pressure responses of vibrational characteristics, in conjunction with structural and electronic characteristics. It is found that all observed infrared spectra peaks seem to shift towards higher frequencies. And the peaks attributed to N-Oc (coordinated oxygen atom) stretching vibrations become broader due to the decrease of lattice constants and the free region of DNTF crystals with the increase of pressure, where the a-direction is more sensitive to pressure. In addition, the non-covalent interaction between adjacent DNTF molecules in the same layer changes from the van der Waals interaction to the steric effect with the increase of pressure, and that between layers also changes from the van der Waals interaction to the π-π stacking interaction. More importantly, these results highlight that the increase of pressure may lead to the stability decrease and impact the sensitivity increase of DNTF. This study can deepen the understanding of the energetic material DNTF under high pressure and is of great significance for blasting and detonation applications of DNTF.
RESUMO
BACKGROUND: Accurate preoperative planning is an important step for accurate reconstruction in total hip arthroplasty (THA). Presently, preoperative planning is completed using either a two-dimensional (2D) template or three-dimensional (3D) mimics software. With the development of artificial intelligence (AI) technology, AI HIP, a planning software based on AI technology, can quickly and automatically identify acetabular and femur morphology, and automatically match the optimal prosthesis size. However, the accuracy and feasibility of its clinical application still needs to be further verified. The purposes of this study were to investigate the accuracy and time efficiency of AI HIP in preoperative planning for primary THA, compared with 3D mimics software and 2D digital template, and further analyze the factors that influence the accuracy of AI HIP. METHODS: A prospective study was conducted on 53 consecutive patients (59 hips) undergoing primary THA with cementless prostheses in our department. All preoperative planning was completed using AI HIP as well as 3D mimics and 2D digital template. The predicted component size and the actual implantation results were compared to determine the accuracy. The templating time was compared to determine the efficiency. Furthermore, the potential factors influencing the accuracy of AI HIP were analyzed including sex, body mass index (BMI), and hip dysplasia. RESULTS: The accuracy of predicting the size of acetabular cup and femoral stem was 74.58% and 71.19%, respectively, for AI HIP; 71.19% (P = 0.743) and 76.27% (P = 0.468), respectively, for 3D mimics; and 40.68% (P < 0.001) and 49.15% (P = 0.021), respectively, for 2D digital templating. The templating time using AI HIP was 3.91 ± 0.64 min, which was equivalent to 2D digital templates (2.96 ± 0.48 min, P < 0.001), but shorter than 3D mimics (32.07 ± 2.41 min, P < 0.001). Acetabular dysplasia (P = 0.021), rather than sex and BMI, was an influential factor in the accuracy of AI HIP templating. Compared to patients with developmental dysplasia of the hip (DDH), the accuracy of acetabular cup in the non-DDH group was better (P = 0.021), but the difference in the accuracy of the femoral stem between the two groups was statistically insignificant (P = 0.062). CONCLUSION: AI HIP showed excellent reliability for component size in THA. Acetabular dysplasia may affect the accuracy of AI HIP templating.
