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Proton radiography is an essential diagnostic for studying magnetic fields in high energy density physics experiments. Protons are born in a fusion implosion, traverse the plasma, and are detected on CR-39 solid state nuclear track detectors. Here, it is shown that there is an intrinsic non-uniformity in ∼ 15 MeV D3He proton radiography data. The increasing angle between the proton trajectory and the center of the detector results in the proton traveling through more detector stack material. As the protons travel through more material and lose energy, the proton energy spectrum gets wider. Protons at the lower end of the spectrum can therefore be lost. The nominal filtering results in protons being ranged out at large angles, causing the intrinsic non-uniformity. This angular effect is confirmed with both OMEGA experiments and Geant4 simulations. It is found that reducing the filtering between the pieces of CR-39 in the detector stack mitigates this effect. Results from accelerator experiments show that this reduced filtering does not impact the detection efficiency of the CR-39. Accounting for this intrinsic fluence non-uniformity is essential for magnetic field reconstruction techniques using proton radiographs. [ABSTRACT FROM AUTHOR]

Because proton head and neck (HN) treatments are sensitive to anatomical changes, plan adaptation (re-plan) during the treatment course is needed for a significant portion of patients. We aim to predict re-plan at plan review stage for HN proton therapy with a neural network (NN) model trained with patients' dosimetric and clinical features. The model can serve as a valuable tool for planners to assess the probability of needing to revise the current plan. Mean beam dose heterogeneity index (BHI), defined as the ratio of the maximum beam dose to the prescription dose, plan robustness features (clinical target volume (CTV), V100 changes, and V100 > 95% passing rates in 21 robust evaluation scenarios), as well as clinical features (e.g., age, tumor site, and surgery/chemotherapy status) were gathered from 171 patients treated at our proton center in 2020, with a median age of 64 and stages from I-IVc across 13 HN sites. Statistical analyses of dosimetric parameters and clinical features were conducted between re-plan and no-replan groups. A NN was trained and tested using these features. Receiver operating characteristic (ROC) analysis was conducted to evaluate the performance of the prediction model. A sensitivity analysis was done to determine feature importance. Mean BHI in the re-plan group was significantly higher than the no-replan group (p <.01). Tumor site (p <.01), chemotherapy status (p <.01), and surgery status (p <.01) were significantly correlated to re-plan. The model had sensitivities/specificities of 75.0%/77.4%, respectively, and an area under the ROC curve of.855. There are several dosimetric and clinical features that correlate to re-plans, and NNs trained with these features can be used to predict HN re-plans, which can be used to reduce re-plan rate by improving plan quality. [ABSTRACT FROM AUTHOR]

Development of flip-chip-on-glass (FCOG) assembly technology using anisotropic conductive adhesive/film (ACA/ACF) is currently underway to achieve fine pitch interconnections between driver IC and fiat panel display. Conductive adhesives are characterized by fine-pitch capability and more environment compatibility. Anisotropic conductive adhesive/film (ACA/ACF) is composed of an adhesive resin and conductive particles, such as metallic or metal-coated polymer particles. In contrast to a solder type flip chip interconnection, the electric current passing through conductive particles becomes the dominant conduction paths. The interconnection between the particles and the conductive surfaces is constructed by the elastic/plastic deformation of conductive particles with contact pressure, which is maintained by tensile stress in the adhesive. Although loss of electric contact can occur when the adhesive expands or swells in the Z-axis direction, delamination and cracking can occur in the adhesive layer while the tensile stress is excessive. In addition to performing processing simulations as well as reliability modeling, this research investigates the contact force that is developed and relaxed within the interconnection during the process sequence by using nonlinear finite element simulations. Environmental effects, such as high temperature and thermal loading, are also discussed. Moreover, a parametric study is performed for process design. To improve performance and reliability, variables such as ACF materials, proper processing conditions are discussed as well. Furthermore, this study presents a novel method called equivalent spring method, capable of significantly reducing the analysis CPU time and make process modeling and contact analysis of the 3D ACA/ACF process possible.