The Manufacturing Cost Guide is a tool that estimates the costs that US manufacturers face and can be used to help gauge the potential returns on manufacturing industry research projects through cost reductions. These costs are grouped into various standardized categories such as the North American Industry Classification System (NAICS) and the Standard Occupational Classification (SOC) system along with other non-standardized costs.

The tool can be used to answer questions such as:

This dataset contains results of our simulation experiments carried out for the Optimal Dynamic Spectrum Access Scheme to utilize white space in LTE Systems. The results were published in the proceedings of IEEE WCNC 2019 with the title "Optimal Dynamic Spectrum Access Scheme for Utilizing White Space in LTE Systems". One set of data belongs to output of experiments run against LTE data captured in our lab and corresponds to various configurations used in our experiment (please see the paper for different configuration).

This dataset contains the result from simulation experiments carried out for our study of analytical modeling of white space utilization for a Dynamic Spectrum Access (DSA) system. It contains the data for the results obtained while comparing analytical and simulated white space utilization (WSU) for synthetic data. It also contains Q-Q plot data which was used to show that the data collected from the metro Philadelphia area is approximately exponentially distributed. It has the histogram of channel 15 and 16 of Philadelphia LTE uplink data.

Data for figures presented in "Quantum amplification of mechanical oscillator motion"

This dataset contains the results of simulated deployments of Environmental Sensing Capability (ESC) sensors along the coasts of the contiguous United States in the 3.5 GHz band. Commercial-federal spectrum sharing in the 3.5 GHz band requires the ESC sensors to detect federal incumbent shipborne radar in order to protect it from harmful interference from commercial users. We use existing tower sites as candidate locations for the sensors and the Irregular Terrain Model (ITM) in point-to-point mode to compute the path loss.

Data for "Quantum gate teleportation between separated qubits in a trapped-ion processor"

We present the development of pyLLE, a freely accessible Lugiato-Lefever equation solver programmed in Python and Julia and optimized for the simulation of microresonator frequency combs. Examples illustrating its operation and performance are presented.

This dataset is associated with NIST TN publication: Review of Smart Grid Standards for Testing and Certification (T&C) landscape analysis. It includes a list of 240 reviewed smart grid standards for T&C landscape analysis using a set of functional metrics that include information models and model mapping, communication protocols and protocol mapping, device physical performance, test method, guide and practice, and cybersecurity of standards. These functional metrics are used to analyze smart grid standards and their T&C program availability.

Hourly methane mole fraction data collected from four tower sites in the Washington DC and Baltimore MD region as part of NIST's Northeast Corridor project. Dataset accompanying publication "Seasonally resolved excess urban methane emissions from the Baltimore/Washington, DC metropolitan region" by Huang, Y., Kort, E. A., Gourdji, S., Karion, A., Mueller, K., and Ware, J.: Seasonally Resolved Excess Urban Methane Emissions from the Baltimore/Washington, DC Metropolitan Region, Environ. Sci. Technol., 10.1021/acs.est.9b02782, 2019.

pyMCR is an open-source software library for performing multivariate curve resolution (MCR) analysis with an alternating regression scheme (MCR-AR). MCR is a chemometric method for elucidating signatures of analytes and their relative abundance from a series of mixture measurements, without any knowledge of these values a priori. This software library, written in Python, enables users to perform MCR analysis with their choice of constraints, regressors, and error functions to minimize. Further, users can apply different constraints and regressors for signature and abundance calculations.