A Molecular-Rotor Device for Nonvolatile High-Density Memory Applications

A novel memory device based on an electrically driven molecular rotor was fabricated and demonstrated to have bistable switching effects. The device showed an on/off ratio of approximately 10^4, a read window of about 2.5 V, and retention performance of greater than 10^4 s. The analysis of the device I–V characteristics suggests the source of the observed switching effects to be the redox-induced ligand rotation around the copper metal center, which is consistent with the observed temperature dependence of the switching behavior. This organic monolayer device holds a potential for nonvolatile high-density memory applications due to its scalability and reduced cost

Room temperature negative differential resistance of a monolayer molecular rotor device

An electrically driven molecular rotor device comprised of a monolayer of redox-active ligated copper compounds sandwiched between a gold electrode and a highly doped P+Si substrate was fabricated. Current-voltage spectroscopy revealed a temperature-dependent negative differential resistance (NDR) associated with the device. Time-dependent density functional theory suggests the source of the observed NDR to be redox-induced ligand rotation around the copper metal center, an explanation consistent with the proposed energy diagram of the device. An observed temperature dependence of the NDR behavior further supports this hypothesis

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

The german AD Registry Treatgermany: Results from an interim data analysis on baseline charesteristics, comorbidities and treatment history

Heratizadeh A, Haufe E, Stoelzl D, et al. The german AD Registry Treatgermany: Results from an interim data analysis on baseline charesteristics, comorbidities and treatment history. In: ABSTRACTS from 11 th George Rajka International Symposium on Atopic Dermatitis April 19–20, 2021 Seoul, Korea. Acta Dermato-Venereologica. Vol 101. Uppsala: Society for Publication of Acta Dermato-Venereologica ; 2021: 24-25