Achieving a High Thermally Conductive One Micron AlN Deposition by High Power Impulse Magnetron Sputtering plus Kick.

High-power impulse magnetron sputtering (HiPIMS) plus kick is a physical vapor deposition method that employs bipolar microsecond-scale voltage pulsing to precisely control the ion energy during sputter deposition. HiPIMS plus kick for AlN deposition is difficult since nitride deposition is challenged by low surface diffusion and high susceptibility to ion damage. In this current study, a systematic examination of the process parameters of HiPIMS plus kick was conducted. Under optimized main negative pulsing conditions, this study documented that a 25 V positive kick biasing for AlN deposition is ideal for optimizing a high quality film, as shown by X-ray diffraction and transmission electron microscopy as well as optimal thermal conductivity while increasing high speed deposition (25 nm/min) and obtaining ultrasmooth surfaces (rms roughness = 0.5 nm). HiPIMS plus kick was employed to deposit a single-texture 1 µm AlN film with a 7.4° rocking curve, indicating well oriented grains, which correlated with high thermal conductivity (121 W/m·K). The data are consistent with the optimal kick voltage enabling enhanced surface diffusion due to ion-substrate collisions without damaging the AlN grains.

Low-k SiOx/AlOx Nanolaminate Dielectric on Dielectric Achieved by Hybrid Pulsed Chemical Vapor Deposition.

Selective and smooth low-k SiOx/AlOx nanolaminate dielectric on dielectric (DOD) was achieved by a hybrid water-free pulsed CVD process consisting of 50 pulses of ATSB (tris(2-butoxy)aluminum) at 330 °C and a 60 s TBS (tris(tert-butoxy)silanol) exposure at 200 °C. Aniline selective passivation was demonstrated on W surfaces in preference to Si3N4 and SiO2 at 300 °C. At 200 °C, TBS pulsed CVD exhibited no growth on W or SiO2, but its growth was catalyzed by AlOx. Using a two-temperature pulsed CVD process, ∼2.7 nm selective SiOx/AlOx nanolaminate was deposited on Si3N4 in preference to aniline passivated W. Nanoselectivity was confirmed and demonstrated on nanoscale W/SiO2 patterned samples by TEM analysis. For a 1:1 Si:Al ratio, a dielectric constant (k) value of 3.3 was measured. For a 2:1 Si:Al ratio, a dielectric constant (k) value of 2.5 was measured. The k value well below that of Al2O3 and SiO2 is consistent with the formation of a low-density, low-k SiO2/Al2O3 nanolaminate in a purely thermal process. This is the first report of a further thermal CVD process for deposition of a low-k dielectric and the first report for a selective low-k process on the nanoscale.

Predicting of axillary lymph node metastasis in invasive breast cancer using multiparametric MRI dataset based on CNN model.

Purpose: To develop a multiparametric MRI model for predicting axillary lymph node metastasis in invasive breast cancer. Methods: Clinical data and T2WI, DWI, and DCE-MRI images of 252 patients with invasive breast cancer were retrospectively analyzed and divided into the axillary lymph node metastasis (ALNM) group and non-ALNM group using biopsy results as a reference standard. The regions of interest (ROI) in T2WI, DWI, and DCE-MRI images were segmented using MATLAB software, and the ROI was unified into 224 × 224 sizes, followed by image normalization as input to T2WI, DWI, and DCE-MRI models, all of which were based on ResNet 50 networks. The idea of a weighted voting method in ensemble learning was employed, and then T2WI, DWI, and DCE-MRI models were used as the base models to construct a multiparametric MRI model. The entire dataset was randomly divided into training sets and testing sets (the training set 202 cases, including 78 ALNM, 124 non-ALNM; the testing set 50 cases, including 20 ALNM, 30 non-ALNM). Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of models were calculated. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the diagnostic performance of each model for axillary lymph node metastasis, and the DeLong test was performed, P< 0.05 statistically significant. Results: For the assessment of axillary lymph node status in invasive breast cancer on the test set, multiparametric MRI models yielded an AUC of 0.913 (95% CI, 0.799-0.974); T2WI-based model yielded an AUC of 0.908 (95% CI, 0.792-0.971); DWI-based model achieved an AUC of 0.702 (95% CI, 0.556-0.823); and the AUC of the DCE-MRI-based model was 0.572 (95% CI, 0.424-0.711). The improvement in the diagnostic performance of the multiparametric MRI model compared with the DWI and DCE-MRI-based models were significant (P< 0.01 for both). However, the increase was not meaningful compared with the T2WI-based model (P = 0.917). Conclusion: Multiparametric MRI image analysis based on an ensemble CNN model with deep learning is of practical application and extension for preoperative prediction of axillary lymph node metastasis in invasive breast cancer.

Prevalence, correlates and recognition of depression in Chinese inpatients with cancer.

OBJECTIVE: To determine the prevalence, correlates and recognition rates of depressive disorders (DDs) in Chinese inpatients with cancer. METHODS: Four hundred and sixty cancer inpatients were recruited from the oncology ward of a university hospital in Beijing, China. Patients were interviewed with a Chinese version of the Mini International Neuropsychiatric Interview 5.0 by eight trained psychiatrists. Case records of inpatients with DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) DDs were reviewed to determine whether treating oncologists made a diagnosis of depression, prescribed antidepressant medications and/or recommended psychiatric consultation/referral. RESULTS: The 1-month prevalence rates (95% confidence intervals) of DDs and major depressive disorder (MDD) were 25.9% (21.9%-29.9%) and 12.6% (9.6%-15.6%), respectively. In our multiple logistic regression analysis, being unmarried [odds ratio (OR)=1.41], cancer stage of metastasis (OR=2.35), time since cancer diagnosis ≤20 months (OR=2.05), frequent pain (OR=1.99~6.83) and being scored between two and four on the Eastern Cooperative Oncology Group Scale (OR=2.25~4.97) were independently associated with depression. Only 6.9% of patients with MDD were recognized by treating oncologists. CONCLUSIONS: DDs are very common among Chinese inpatients with cancer. The high prevalence rate and low recognition rate of depression in cancer patients indicate a pressing need for routine screening, evaluation and treatment of depression in this patient population.