Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Protocols”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 595 records · Page 33

Pragmatic protocols for working cleanly when measuring ice nucleating particles

We report that measuring ice nucleating particles (INPs) is critical for understanding, and modeling, cloud formation, reflectivity, and precipitation patterns. However, because INPs are very rare in the atmosphere, but abundant—sometimes alarmingly so—in the dust that covers all work surfaces, contamination during processing of collected aerosol samples can be a significant hindrance to obtaining accurate measures of INPs. In preparing this technical note, we questioned the cleanliness of every collection and processing step involved in making immersion freezing measurements of INPs re-suspended from filter samples. The aim was to identify, and then minimize, all potential sources of significant contamination, including containers and tools used to store filters and prepare liquid suspensions, gloves, work surfaces, and the polymerase chain reaction (PCR) trays commonly used for sample analysis. While plasticware released few INPs, most gloves readily shed them, but this can be mitigated by using washed cleanroom vinyl or polyethylene gloves. Work surfaces, even those that had been cleaned, were prodigious reservoirs of contaminating INPs, but simply covering them with aluminum foil will provide an INP-free surface. By applying these practices, we developed a method to reduce the background level of INPs on Nuclepore™ polycarbonate filters in our tests to 0 at -25 °C and < 20 at -27 °C, making them suitable for use in all sampling environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Protocol to detect dilution cycles in chemostat experiments and estimate growth rate slopes with linear modeling with R software chemostat_regression

Chemostat growth chambers measure optical density over time and require manual calculation of growth rates. Here, we present chemostat_regression, R software that enables users to automatically identify chemostat cycles and estimate growth rate using a linear regression approach. We describe steps for creating requisite software environment(s), formatting input data, executing the software via command line/RStudio/R-Shiny, interpreting results, assessing the validity of results, and modifying input parameters.

59 BASIC BIOLOGICAL SCIENCES↗