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Gaithersburg

FIB SEM image data set of Caenorhabditis elegans exposed to 60 nm Au nanoparticles

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 was 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). Although the images were collected over 14 different sessions, they represent a contiguous section of a worm.

Neuromorphic Device Measurements

Neuromorphic computing is a radical new approach to information processing for artificial intelligence where, instead of using digital electronics, inspiration

2017 Workshop Presentations

September 11-12, 2017 Presentations Application of Phase Field and CALPHAD methods to Additive Manufacturing in IN625 , Trevor Keller...

Polymer Mechanics

Polymers play a central role in high rate impact mitigation applications ranging from helmets, to body armor, to aircraft and spacecraft protective coatings. A

Clear Talk for First Responders

For first responders, such as firefighters, police officers and emergency medical technicians, a successful outcome to a mission—and perhaps the difference...

It’s All About the Mix

A marriage between 3-D printer plastic and a versatile material for detecting and storing gases could lead to inexpensive sensors and fuel cell batteries alike...

Object Oriented Finite Elements (OOF)

OOF is a collaborative effort between the Information Technology Laboratory and the Material Measurement Laboratory at NIST. The intended audience of the OOF

DFT Benchmarking

DFT is a widely used computational technique in the material science community and it provides interpretative tools for understanding experimental results as

Materials Design Toolkit

This framework provides the generic environment for materials design. The ICME (Integrating Computational Materials Engineering) approach is implemented for
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