Manipulating exchange bias in 2D magnetic heterojunction for high-performance robust memory applications.

The exchange bias (EB) effect plays an undisputed role in the development of highly sensitive, robust, and high-density spintronic devices in magnetic data storage. However, the weak EB field, low blocking temperature, as well as the lack of modulation methods, seriously limit the application of EB in van der Waals (vdW) spintronic devices. Here, we utilized pressure engineering to tune the vdW spacing of the two-dimensional (2D) FePSe3/Fe3GeTe2 heterostructures. The EB field (HEB, from 29.2 mT to 111.2 mT) and blocking temperature (Tb, from 20 K to 110 K) are significantly enhanced, and a highly sensitive and robust spin valve is demonstrated. Interestingly, this enhancement of the EB effect was extended to exposed Fe3GeTe2, due to the single-domain nature of Fe3GeTe2. Our findings provide opportunities for the producing, exploring, and tuning of magnetic vdW heterostructures with strong interlayer coupling, thereby enabling customized 2D spintronic devices in the future.

Risk-Based Monitoring in Clinical Trials: 2021 Update.

Clinical trial quality depends on ensuring participant safety and data integrity, which require careful management throughout the trial lifecycle, from protocol development to final data analysis and submission. Recent developments-including new regulatory requirements, emerging technologies, and trial decentralization-have increased adoption of risk-based monitoring (RBM) and its parent framework, risk-based quality management (RBQM) in clinical trials. The Association of Clinical Research Organizations (ACRO), recognizing the growing importance of these approaches, initiated an ongoing RBM/RBQM landscape survey project in 2019 to track adoption of the eight functional components of RBQM. Here we present results from the third annual survey, which included data from 4889 clinical trials ongoing in 2021. At least one RBQM component was implemented in 88% of trials in the 2021 survey, compared with 77% in 2020 and 53% in 2019. The most frequently implemented components in 2021 were initial and ongoing risk assessments (80 and 78% of trials, respectively). Only 7% of RBQM trials were Phase IV, while the proportions of Phase I-III trials ranged 27-36%. Small trials (< 300 participants) accounted for 60% of those implementing RBQM. The therapeutic areas with the largest number of RBQM trials were oncology (38%), neurology (10%), and infectious diseases (9%). The 2021 survey confirmed a pattern of increasing RBM/RBQM adoption seen in earlier surveys, with risk assessments, which have broad regulatory support, driving RBQM growth; however, one area requiring further development is implementation of centralized monitoring combined with reductions in source data verification (SDV) and source data review (SDR).

Risk-Based Monitoring in Clinical Trials: Increased Adoption Throughout 2020.

With the emergence of new technologies for data collection, the continued impact of the COVID-19 pandemic, and the increasing number of partially or fully decentralized clinical trials (DCTs), the importance of risk-based monitoring (RBM) and the larger risk-based quality management (RBQM) framework in clinical trial management is increasing. RBM and RBQM focus on the detection of events or trends that impact trial quality in terms of participant safety and data integrity. In 2019, the Association of Clinical Research Organizations (ACRO) began a landscape survey of RBM/RBQM implementation in ongoing clinical trials. Initial results of this survey, representing full-year data for 2019, were reported previously. Here, we present full-year landscape data for 2020 drawn from 5,987 clinical trials ongoing at the end of 2020, including 908 new studies started that year. Of these trials, 77% implemented at least one RBM/RBQM component, an increase from 47% for studies ongoing at the end of 2019. We also observed increased implementation for three of the five RBM components included in the survey. Centralized monitoring decreased nominally in 2020 compared with 2019. Although the percentages of 2020 trials incorporating reduced source data verification (SDV) and reduced source data review (SDR) increased from 2019 to 2020, these numbers are still low considering the large percentage of trials implementing at least one RBQM component. In the current clinical trial landscape, as more DCTs are launched and new data collection technologies are implemented, there remains a pressing need for greater use of centralized monitoring coupled with reductions in SDR/SDV and, ultimately, greater adoption of RBM and RBQM.

Employing Hybrid Lennard-Jones and Axilrod-Teller Potentials to Parametrize Force Fields for the Simulation of Materials' Properties.

The development of novel materials has challenges besides their synthesis. Materials such as novel MXenes are difficult to probe experimentally due to their reduced size and low stability under ambient conditions. Quantum mechanics and molecular dynamics simulations have been valuable options for material properties determination. However, computational materials scientists may still have difficulty finding specific force field models for their simulations. Force fields are usually hard to parametrize, and their parameters' determination is computationally expensive. We show the Lennard-Jones (2-body interactions) combined with the Axilrod-Teller (3-body interactions) parametrization process' applicability for metals and new classes of materials (MXenes). Because this parametrization process is simple and computationally inexpensive, it allows users to predict materials' behaviors under close-to-ambient conditions in molecular dynamics, independent of pre-existing potential files. Using the process described in this work, we have made the Ti2C parameters set available for the first time in a peer-reviewed work.