Non-platinum group
metal (non-PGM) electrocatalysts for the oxygen
reduction reaction (ORR) are generally composed of iron, nitrogen,
and carbon synthesized through high-temperature pyrolysis. Among the
various types of precursors, metal–organic frameworks (MOFs),
zeolitic imidazolate framework (ZIF)-8 in particular, have often been
used in the synthesis. The pyrolysis of ZIF-8 precursor relies on
the use of Zn as a sacrificial metal (SM), and the optimal processing
temperatures often exceed 1000 °C to generate active non-PGM
catalysts. The high pyrolysis temperature tends to result in heterogeneous
active moieties ranging from Fe single atoms to nanoparticles. In
this study, we present the synthesis of non-PGM catalysts using Cd
as the sacrificial metal instead of Zn. By using Cd, we were able
to generate active non-PGM electrocatalysts from the MOF precursors
at a low pyrolysis temperature of 750 °C, which helps preserve
the single atomic iron active sites.
Novel and developing artificial intelligence (AI) systems can be integrated into healthcare settings in numerous ways. For example, in the case of automated image classification and natural language processing, AI systems are beginning to demonstrate near expert level performance in detecting abnormalities such as seizure activity. This paper, however, focuses on AI integration into clinical trials. During the clinical trial recruitment process, considerable labor and time is spent sifting through electronic health record and interviewing patients. With the advancement of deep learning techniques such as natural language processing, intricate electronic health record data can be efficiently processed. This provides utility to workflows such as recruitment for clinical trials. Studies are starting to show promise in shortening the time to recruitment and reducing workload for those involved in clinical trial design. Additionally, numerous guidelines are being constructed to encourage integration of AI into the healthcare setting with meaningful impact. The goal would be to improve the clinical trial process by reducing bias in patient composition, improving retention of participants, and lowering costs and labor.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.