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With the advent of vSANS, CANDOR, and MACS, which provide accelerated data rates, and the deployment of the new, more flexible, data acquisition system at NIST, coupled with the rise of machine learning and AI, CHRNS is well-positioned to supply the advanced neutron capabilities required to characterize materials out of equilibrium. Through this initiative, CHRNS will be able to offer the academic community access to exceptional neutron scattering capabilities to address pressing scientific issues.
Description
High level composition of the Kinetics Initiative
The MACS, vSANS, and CANDOR instruments will be upgraded to allow new approaches for time- resolved experiments.
New hardware will allow CHRNS users to remotely reduce and analyze their data.
New data formats that incorporate the multiple time-resolved data streams and a new methodology of maintaining the data in an accessible database will be implemented.
Software will be implemented for experimental optimization on CANDOR and vSANS.
A combination of computational power and software tools will be developed to treat the time-stamped data in almost real time for immediate user feedback and AI-based experimental control.
Time-stamping of the instrumental configuration and constant sample rotation will increase the effective data rates on MACS.
New electrochemical and stopped-flow capabilities will be developed
Unscheduled Outage Progress
With CHRNS efforts split over improving FAIR-data implementations here are the major milestones achieved during the outage
Resource loaded project management plans for FAIR-related activities
Rebalancing CHRNS Non-Equilibrium Structure of Materials Initiative to take advantage of the outage
Procurements on schedule:
Potentiostat received and passed acceptance testing
MACS rotational stage design and engineering
CANDOR liquid exchange system robotics components in procurement
All significant network hardware and computational resources (despite global supply chain issues)
Prototype sample-environment and instrument event-mode system
Server-client architecture
High-level Standards and Protocols defined
Version control of Labview libraries
Concepts for device discovery
Concepts for including device and hardware information in data files for FAIR
1-2 shear cell control redesign to work with event-mode and current NICE controls
Improved furnace and temperature control on
Event-mode is to be expanded on other rheometers
In-house stopped-flow system
Proof-of-principle flow system with 3 sec effective resolution
Instrument control scripts and rudimentary automatic data reduction/visualization
Engagement with key users and experts; feedback has been important in deciding priorities and capabilities
proof of principle
Improved temperature controlled sample environment
Autonomous Formulations Lab (nSOFT)
Inspiration for CANDOR liquid exchange system
Autonomous data collection for NR
Demonstrate viability of autonomous experimentation, where data are analyzed in the context of a predetermined model in real time
Full McStas simulation of MACS
allows full characterization of timing delays from sample to detector (~1 ms) with detection uncertainties
allows full characterization of resolution function for data fitting and physics model assignment
Estimates of timing resolution and delays between sample and detectors for Candor and MACS
Visualization of MACS event mode data using DAVE Mslice
CANDOR Biological reflectivity workflow
Transcribed C++ Library to Python (solid-supported lipid bilayer, membrane-associated protein, peptide, or small molecule)
Jupyter Notebook workflow for data fitting, v1.0
Improved functionality to Notebook (post-processing of fit, publication-ready graphs)
In progress to having web-based functionality;
Bayesian optimization of experiments
from above workflow added support for experimental optimizations
Goal: complete with remote execution capabilities
Implementing experimental optimization methods for SANS
Synthetic data generation including measurement uncertainties for SANS underway
Coordination with SASView underway
Goal: complete with remote execution capabilities
Remote fitting of SANS data in SASView
Multi-CPU and GPU support for remote fitting
Separation of computational code from GUI
Staff Training Course Focused on writing new models and code structure