Atomically Thin Al2O3 Films for Tunnel Junctions

Metal-insulator-metal tunnel junctions are common throughout the microelectronics industry. The industry standard AlOx tunnel barrier, formed through oxygen diffusion into an Al wetting layer, is plagued by internal defects and pinholes which prevent the realization of atomically thin barriers demanded for enhanced quantum coherence. In this work, we employ in situ scanning tunneling spectroscopy along with molecular-dynamics simulations to understand and control the growth of atomically thin Al2O3 tunnel barriers using atomic-layer deposition. We find that a carefully tuned initial H2O pulse hydroxylated the Al surface and enabled the creation of an atomically thin Al2O3 tunnel barrier with a high-quality M−I interface and a significantly enhanced barrier height compared to thermal AlOx. These properties, corroborated by fabricated Josephson junctions, show that atomic-layer deposition Al2O3 is a dense, leak-free tunnel barrier with a low defect density which can be a key component for the next generation of metal-insulator-metal tunnel junctions

Atomically Thin Al2 O3 Films for Tunnel Junctions

Metal-insulator-metal tunnel junctions are common throughout the microelectronics industry. The industry standard AlOx tunnel barrier, formed through oxygen diffusion into an Al wetting layer, is plagued by internal defects and pinholes which prevent the realization of atomically thin barriers demanded for enhanced quantum coherence. In this work, we employ in situ scanning tunneling spectroscopy along with molecular-dynamics simulations to understand and control the growth of atomically thin Al2O3 tunnel barriers using atomic-layer deposition. We find that a carefully tuned initial H2O pulse hydroxylated the Al surface and enabled the creation of an atomically thin Al2O3 tunnel barrier with a high-quality M-I interface and a significantly enhanced barrier height compared to thermal AlOx. These properties, corroborated by fabricated Josephson junctions, show that atomic-layer deposition Al2O3 is a dense, leak-free tunnel barrier with a low defect density which can be a key component for the next generation of metal-insulator-metal tunnel junctions

Controllable Fabrication of Heterogeneous p-TiO₂ QDs@g-C₃N₄ p-n Junction for Efficient Photocatalysis

Photocatalytic technology has been considered to be an ideal approach to solve the energy and environmental crises, and TiO2 is regarded as the most promising photocatalyst. Compared with bare TiO2, TiO2 based p-n heterojunction exhibits a much better performance in charge separation, light absorption and photocatalytic activity. Herein, we developed an efficient method to prepare p-type TiO2 quantum dots (QDs) and decorated graphitic carbonitrile (g-C3N4) nanocomposites, while the composition and structure of the TiO2@g-C3N4 were analyzed by X-ray diffraction, Fourier transform infrared spectroscopy ,thermogravimetric analysis, transmission electron microscopy, X-ray photoelectron spectroscopy and UV-visible diffuse reflectance spectroscopy characterizations. The characterization results reveal the surface decorated TiO2 quantum dots is decomposed by titanium glycerolate, which exhibits p-type conductivity. The presence of p-n heterojunction over interface is confirmed, and photoluminescence results indicate a better performance in transfer and separation of photo-generated charge carriers than pure semiconductors and type-II heterojunction. Moreover, the synergy of p-n heterojunction over interface, strong interface interaction, and quantum-size effect significantly contributes to the promoted performance of TiO2 QDs@g-C3N4 composites. As a result, the as-fabricated TiO2 QDs@g-C3N4 composite with a p/n mass ratio of 0.15 exhibits improved photo-reactivity of 4.3-fold and 5.4-fold compared to pure g-C3N4 in degradation of organic pollutant under full solar spectrum and visible light irradiation, respectively

Outcomes of COVID-19 in Patients With Cancer: Report From the National COVID Cohort Collaborative (N3C)

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.PURPOSE Variation in risk of adverse clinical outcomes in patients with cancer and COVID-19 has been reported from relatively small cohorts. The NCATS’ National COVID Cohort Collaborative (N3C) is a centralized data resource representing the largest multicenter cohort of COVID-19 cases and controls nationwide. We aimed to construct and characterize the cancer cohort within N3C and identify risk factors for all-cause mortality from COVID-19. METHODS We used 4,382,085 patients from 50 US medical centers to construct a cohort of patients with cancer. We restricted analyses to adults ≥ 18 years old with a COVID-19–positive or COVID-19–negative diagnosis between January 1, 2020, and March 25, 2021. We followed N3C selection of an index encounter per patient for analyses. All analyses were performed in the N3C Data Enclave Palantir platform. RESULTS A total of 398,579 adult patients with cancer were identified from the N3C cohort; 63,413 (15.9%) were COVID-19–positive. Most common represented cancers were skin (13.8%), breast (13.7%), prostate (10.6%), hematologic (10.5%), and GI cancers (10%). COVID-19 positivity was significantly associated with increased risk of all-cause mortality (hazard ratio, 1.20; 95% CI, 1.15 to 1.24). Among COVID-19–positive patients, age ≥ 65 years, male gender, Southern or Western US residence, an adjusted Charlson Comorbidity Index score ≥ 4, hematologic malignancy, multitumor sites, and recent cytotoxic therapy were associated with increased risk of all-cause mortality. Patients who received recent immunotherapies or targeted therapies did not have higher risk of overall mortality. CONCLUSION Using N3C, we assembled the largest nationally representative cohort of patients with cancer and COVID-19 to date. We identified demographic and clinical factors associated with increased all-cause mortality in patients with cancer. Full characterization of the cohort will provide further insights into the effects of COVID-19 on cancer outcomes and the ability to continue specific cancer treatments

Sample average treatment effect on the treated (SATT) analysis using counterfactual explanation identifies BMT and SARS-CoV-2 vaccination as protective risk factors associated with COVID-19 severity and survival in patients with multiple myeloma

Abstract Patients with multiple myeloma (MM), an age-dependent neoplasm of antibody-producing plasma cells, have compromised immune systems and might be at increased risk for severe COVID-19 outcomes. This study characterizes risk factors associated with clinical indicators of COVID-19 severity and all-cause mortality in myeloma patients utilizing NCATS’ National COVID Cohort Collaborative (N3C) database. The N3C consortium is a large, centralized data resource representing the largest multi-center cohort of COVID-19 cases and controls nationwide (>16 million total patients, and >6 million confirmed COVID-19+ cases to date). Our cohort included myeloma patients (both inpatients and outpatients) within the N3C consortium who have been diagnosed with COVID-19 based on positive PCR or antigen tests or ICD-10-CM diagnosis code. The outcomes of interest include all-cause mortality (including discharge to hospice) during the index encounter and clinical indicators of severity (i.e., hospitalization/emergency department/ED visit, use of mechanical ventilation, or extracorporeal membrane oxygenation (ECMO)). Finally, causal inference analysis was performed using the Coarsened Exact Matching (CEM) and Propensity Score Matching (PSM) methods. As of 05/16/2022, the N3C consortium included 1,061,748 cancer patients, out of which 26,064 were MM patients (8,588 were COVID-19 positive). The mean age at COVID-19 diagnosis was 65.89 years, 46.8% were females, and 20.2% were of black race. 4.47% of patients died within 30 days of COVID-19 hospitalization. Overall, the survival probability was 90.7% across the course of the study. Multivariate logistic regression analysis showed histories of pulmonary and renal disease, dexamethasone, proteasome inhibitor/PI, immunomodulatory/IMiD therapies, and severe Charlson Comorbidity Index/CCI were significantly associated with higher risks of severe COVID-19 outcomes. Protective associations were observed with blood-or-marrow transplant/BMT and COVID-19 vaccination. Further, multivariate Cox proportional hazard analysis showed that high and moderate CCI levels, International Staging System (ISS) moderate or severe stage, and PI therapy were associated with worse survival, while BMT and COVID-19 vaccination were associated with lower risk of death. Finally, matched sample average treatment effect on the treated (SATT) confirmed the causal effect of BMT and vaccination status as top protective factors associated with COVID-19 risk among US patients suffering from multiple myeloma. To the best of our knowledge, this is the largest nationwide study on myeloma patients with COVID-19