SRM 2969 Electronic files containing certified values and their uncertainties, and the data used to assign those values

Electronic files containing certified values and their uncertainties, and the data used to assign those values.

The dataset can be used to develop and test algorithms for communication and sensing in the 60GHz band. The dataset consists of synthetically generated indoor mm-wave channels between a MIMO transmitter and a MIMO receivers. Multiple targets are moving in the room. Number of targets, velocity of each target and trajectory are randomized across the dataset. The dataset contains also noisy received IEEE 802.11ay channel estimation fields. The dataset is suitable for development and testing of machine/deep learning algorithms.

This database gives hydrogen-deuterium exchange mass spectrometry (HDX-MS) data from measurements of three purified IgG1 glycoform samples, predominantly G0F, G2F, and SAF, in isolation and in complexation with the high-affinity receptor, Fc(gamma)RIa (CD64). The IgG1 antibody used in this study, aIL8hFc, is a murine-human chimeric IgG1, which inhibits IL-8 binding to human neutrophils.

The NIST DART-MS Forensics Database is an evaluated collection of in-source collisionally-induced dissociation (is-CID) mass spectra of compounds of interest to the forensics community (e.g. seized drugs, cutting agents, etc.). The is-CID mass spectra were collected using Direct Analysis in Real-Time (DART) Mass Spectrometry (MS), either by NIST scientists or by contributing agencies noted per compound. The database is provided as a general-purpose structure data file (.SDF).

Code and demonstration data for the paper, "On-the-fly closed-loop materials discovery via Bayesian active learning," Kusne, A.G., Yu, H., Wu, C. et al. Nat Commun 11, 5966 (2020). https://doi.org/10.1038/s41467-020 19597-w Code: Closed-loop autonomous materials exploration and optimization. This code is used to control an autonomous materials exploration and optimization platform. It guides subsequent experiments to learn about a material's phase map and target functional properties in a unified framework.