SEDCORR is an open-source Python module designed to correct for the systematic energy deficits in atom probe mass spectra of electrically insulating samples. The assumption of the algorithm is that the mass spectrum for a dataset is conserved throughout the dataset and that any changes to the peak positions arise from an unknown slowly-fluctuating accelerating voltage. For computational speed, the unknown accelerating voltage is determined using a template matching FFT-based cross correlation method.

SCATMECH is a library of object-oriented C++ computer codes originally developed for disseminating models for polarized light scattering from surfaces and aerosols and for diffraction from gratings. The pySCATMECH package has been developed as an interface to the SCATMECH library, simplifying use of the codes and allowing for more rapid development of software for these applications.

Python module 'optbayesexpt' uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given an parametric model - analogous to a fitting function - Bayesian inference uses each measurement 'data point' to refine model parameters. Using this information, the software suggests measurement settings that are likely to efficiently reduce uncertainties. A TCP socket interface allows the software to be used from experimental control software written in other programming languages.

The project that produced these data involved the analysis and modeling of atmospheric Asian dust particles and background marine air particles collected in Hawaii, USA at the Mauna Loa Observatory (MLO) of the National Oceanic and Atmospheric Administration. Individual heterogeneous dust particles were analyzed with focused ion-beam scanning electron microscopy and energy-dispersive X-ray spectroscopy.

Data for mass concentration analysis and spectral analysis for the paper titled, "Comparison of primary laser spectroscopy and mass spectrometry methods for measuring mass concentration of gaseous elemental mercury"

SRM 3672 Organic Contaminants in Smokers' Urine (Frozen) - This Standard Reference Material (SRM) is intended for use in evaluating analytical methods for the determination of selected hydroxylated polycyclic aromatic hydrocarbons (hydroxylated PAHs) and phthalate, phenol, and volatile organic compound (VOC) metabolites in urine. All of the constituents for which certified and reference values are provided are naturally present in the urine. This data is public in the Certificate of Analysis for this material.

SRM 3673 Organic Contaminants in Non-Smokers' Urine (Frozen) - This Standard Reference Material (SRM) is intended for use in evaluating analytical methods for the determination of selected hydroxylated polycyclic aromatic hydrocarbons (hydroxylated PAHs) and phthalate, phenol, and volatile organic compound (VOC) metabolites in urine. All of the constituents for which certified and reference values are provided are naturally present in the urine. This data is public in the Certificate of Analysis for this material.

Standard Reference Material 695 Trace Elements in Multi-Nutrient Fertilizer - This Standard Reference Material (SRM) is intended primarily for use in the evaluation of techniques employed in the analysis of multi-nutrient fertilizer materials and materials of a similar matrix. A unit of SRM 695 consists of approximately 70 g of jet-milled fertilizer. This data is public in the Certificate of Analysis for this material.

Standard Reference Material-1721: Southern Oceanic Air. Ambient Nominal Amount of Substance Fraction for Carbon Dioxide, Methane & Nitrous Oxide. This Standard Reference Material (SRM) is a primary gas mixture for which the amount-of-substance fraction, expressed as concentration, may be related to secondary working standards. This SRM is intended for the calibration of instruments used for ambient carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) determinations and for other applications. This data is public in the Certificate of Analysis for this material.

This folder contains image data sets from 14 separate serial sectioning sessions. The entire data folder consists of 1379 8 bit tif images and is 47.3 GB in size. Serial sectioning was performed using FEI Helios 660 NanoLab focused ion beam scanning electron microscope (FIB SEM) and Auto Slice and View G3 software. The sample was a heavy metal stained and resin embedded Caenorhabditis elegans (C. elegans) that were exposed to 60 nm Au nanoparticles. Detailed descriptions of the worm preparation and resin block processing are described in Johnson, M.E. et al. (ACS Nano, 2016).