ZENO computes hydrodynamic and electronic properties using numerical path integration techniques based on Brownian motion Monte Carlo methods. These methods provide stochastic solutions to elliptic partial differential equations, which represent the desired material properties or serve as intermediates for their computation. The mathematical framework maps these problems onto the electrostatic capacitance problem, where the stochastic solution corresponds to the probability of a random walk from infinity hitting the material's surface.

Numerical values of data points and figure generation scripts for manuscript "Sawtooth wave adiabatic passage in a grating magneto-optical trap" submitted for publication and available on ArXiv (2602.06230).

These data are associated with the paper “Quantifying rheology and microstructure of hydrating Portland-Limestone Cement blends to address additive manufacturing needs” by the same authors [1]. The data are associated with in situ dielectric rheological small-angle neutron scattering (rheo-SANS) studies of Portland limestone cement (PLC) blends and Ordinary Portland Cement (OPC) control [2]. The rheo-SANS data were collected on the NIST Center for Neutron Research (NCNR) VSANS instrument [3] as a function of cement hydration time.

We compare the calculated, quantum-based output of a radio-frequency Josephson arbitrary waveform synthesizer (RF-JAWS) with its measured output that is calibrated through the established NIST RF power traceability path, a necessary first step towards quantum-based RF metrology. An array of

This paper evaluates the short-term and long-term performance of a new type of dc secondary voltage standard at 10 V by direct comparison to a programmable Josephson voltage standard. Allan deviation measurements indicated a noise floor of 4.5 nV, enabling potential new applications in voltage metrology and possibly reducing uncertainty along the dissemination chain from primary calibration laboratories to calibration laboratories.

This publication contains the data presented in the associated proceeding paper ”Pushing the Envelope in Mechanical Characterization of Copper in Hybrid-Bonding Patterns for Advanced Packaging: from Instrumented Indentation to Multimodal Atomic Force Microscopy” submitted for publication in the proceedings of the 2026 IEEE 76th Electronic Components and Technology Conference.
The datasets were obtained in single-step and multi-step indentations using instrumented indentation (IIT) and atomic force microscope (AFM) on hybrid-bonding copper at room temperature.

SpherIndent is a modular, open-source software package with graphical user interface (GUI) for analysis of quasi-static spherical indentation experiments conducted in single-step or multi-step loading sequences. All components are developed in Python programming language with the GUI built on Tkinter. The software package is essentially constructed using libraries including NumPy, Pandas, SciPy, Sklearn, Matplotlib, and OpenCV. Data storage, from raw to processed and analyzed data (including figures) is handled via Pickle with traceability, efficient retrieval and sharing in mind.

This paper evaluates the performance of a new type of 2 V traveling cryocooled Programmable Josephson Voltage Standard for performing on-site verification of quantum voltage standards. Direct comparison with a 10 V system showed agreement of 8 parts in 10^11 at 2 V. This result shows that, despite the lower voltage, the direct Josephson-to-Josephson system comparison method provides a two orders-of-magnitude improvement over traveling Zener standards for verifying Josephson voltage standards.

This dataset contains two-port S-parameter measurements (S2P format) acquired in a typical mode-stirred reverberation chamber. The measurements support training of artificial neural networks to infer optimal mechanical stirrer and turntable positions for realizing a target wireless channel response. Data provides dense sampling of scattering parameters across mechanical configurations for four fixed excitation antennas.

This database contains Near Infrared (NIR) spectroscopy and optical microscopy data on an assortment of fabric specimens used for applications including fiber content classification, systems and software development, and systems and process validation of textile feedstock identification systems.