drtsans: The data reduction toolkit for small-angle neutron scattering at Oak Ridge National Laboratory
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97 MATHEMATICS AND COMPUTING↗
Engineering topics
Doucet, Mathieu
Publications and source records attributed to Doucet, Mathieu.
A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory
In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. The study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and ii) data management requirements for data-driven science using artificial intelligence.
Bernholdt, David↗
On-the-fly autonomous control of neutron diffraction via physics-informed Bayesian active learning
We demonstrate the first live, autonomous control over neutron diffraction experiments by developing and deploying ANDiE: the autonomous neutron diffraction explorer. Neutron scattering is a unique and versatile characterization technique for probing the magnetic structure and behavior of materials. However, instruments at neutron scattering facilities in the world is limited, and instruments at such facilities are perennially oversubscribed. We demonstrate a significant reduction in experimental time required for neutron diffraction experiments by implementation of autonomous navigation of measurement parameter space through machine learning. Prior scientific knowledge and Bayesian active learning are used to dynamically steer the sequence of measurements. We show that ANDiE can experimentally determine the magnetic ordering transition of both MnO and Fe 1.09 Te all while providing a fivefold enhancement in measurement efficiency. Furthermore, in a hypothesis testing post-processing step, ANDiE can determine transition behavior from a set of possible physical models. ANDiE's active learning approach is broadly applicable to a variety of neutron-based experiments and can open the door for neutron scattering as a tool of accelerated materials discovery.
36 MATERIALS SCIENCE↗
Understanding the Solution Dynamics and Binding of a PVDF Binder with Silicon, Graphite, and NMC Materials and the Influence on Cycling Performance
The impact of the binding, solution structure, and solution dynamics of poly(vinylidene fluoride) (PVDF) with silicon on its performance as compared to traditional graphite and Li 1.05 Ni 0.33 Mn 0.33 Co 0.33 O 2 (NMC) electrode materials was explored. Through refractive index (RI) measurements, the concentration of the binder adsorbed on the surface of electrode materials during electrode processing was determined to be less than half of the potentially available material resulting in excessive free binder in solution. Using ultrasmall-angle neutron scattering (USANS) and small-angle neutron scattering (SANS), it was found that PVDF forms a conformal coating over the entirety of the silicon particle. This is in direct contrast to graphite–PVDF and NMC–PVDF slurries, where PVDF only covers part of the graphite surface, and the PVDF chains make a network-like graphite–PVDF structure. Conversely, a thick layer of PVDF covers NMC particles, but the coating is porous, allowing for ion and electronic transport. The homogeneous coating of silicon breaks up percolation pathways, resulting in poor cycling performance of silicon materials as widely reported. These results indicate that the Si–PVDF interactions could be modified from a binder to a dispersant.
25 ENERGY STORAGE↗
Lithium-Mediated Electrochemical Nitrogen Reduction: Tracking Electrode–Electrolyte Interfaces via Time-Resolved Neutron Reflectometry
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Secure Collaborative Environment for Seamless Sharing of Scientific Knowledge
In a secure collaborative environment, tera-bytes of data generated from powerful scientific instruments are used to train secure machine learning (ML) models on exascale computing systems, which are then securely shared with internal or external collaborators as cloud-based services. Devising such a secure platform is necessary for seamless scientific knowledge sharing without compromising individual, or institute-level, intellectual property and privacy details. By enabling new computing opportunities with sensitive data, we envision a secure collaborative environment that will play a significant role in accelerating scientific discovery. Several recent technological advancements have made it possible to realize these capabilities. In this paper, we present our efforts at ORNL toward developing a secure computation platform. We present a use case where scientific data generated from complex instruments, like those at the Spallation Neutron Source (SNS), are used to train a differential privacy enabled deep learning (DL) network on Summit, which is then hosted as a secure multi-party computation (MPC) service on ORNL’s Compute and Data Environment for Science (CADES) cloud computing platform for third-party inference. In this feasibility study, we discuss the challenges involved, elaborate on leveraged technologies, analyze relevant performance results and present the future vision of our work to establish secure collaboration capabilities within and outside of ORNL.
Yoginath, Srikanth↗
Study of Chromium Migration in a Nickel-Based Alloy Using Polarized Neutron Reflectometry and Rutherford Backscattering Spectrometry
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Competitive adsorption within electrode slurries and impact on cell fabrication and performance
We ask why do battery researchers use 10-20 wt% binder in research cells when commercial chemistries use much less? This report seeks to explore this question by understanding the ordering and structure of polyimide binder with a silicon/pitch-carbon black electrode system. Correlating the effect of binder concentration on electrode architecture and electrochemical properties is vital to enhancing silicon anode cycle and calendar life. Using ultra-small angle neutron scattering (USANS) and binder adsorption isotherms an optimal region of polyimide (PI) binder coverage was found. Further, there is a preferential adsorption of PI to carbon black that has to be completed before PI binds to the silicon. Optimizing the concentration of binder leads to a 50% increase in capacity due to the optimization of binder-silicon-carbon interactions.
25 ENERGY STORAGE↗
A high temperature cell for investigating interfacial structure on the molecular scale in molten salt/alloy systems
In this work, we describe the design and development of an in situ neutron reflectometry cell for high temperature investigations of structural changes occurring at the interface between inorganic salts, in their molten state up to 800 °C, and corrosion resistant alloys or other surfaces. In the cell, a molten salt is confined by an annular ring of single crystal sapphire constrained between the sample substrate and a sapphire plate using two gold O-rings, enclosing a liquid salt volume of 20 ml, along with a dynamic cell volume to accommodate expansion of the liquid with heating. Further, as a test case for the cell, we report on an in situ neutron reflectometry measurement of the interface between a eutectic salt mixture of MgCl 2 –KCl (32:68 molar ratio) and a single crystal sapphire substrate at 450 °C, resulting in the formation of a 60 Å layer having a scattering length density of 1.72 × 10 –6 Å –2 . While the origin of this layer is uncertain, it is likely to have resulted from the salt reacting with an existing impurity layer on the sapphire substrate.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
drtsans
drtsans is highly modular, allowing users to customize collected data as well as test hypothetical or simulated neutron events data. Instrument scientists can use the advance features of drtsans to calibrate their instruments and reduced large quantities of datasets in a streamlined mode. Users can correct the collected data with dark current subtraction and normalization by neutron flux, detector sensitivity, solid angle subtended by the detectors, and scaling to absolute units. Conversion from time-of-flight and/or wavelength to 1D or 2D momentum transfer renders the final scattering quantities amenable to analysis.
Bilheux, JeanC↗
Additively Manufactured NdFeB Polyphenylene Sulfide Halbach Magnets to Generate Variable Magnetic Fields for Neutron Reflectometry
Halbach arrays are the most efficient closed structures for generating directed magnetic fields and gradients, and are widely used in various electric machines. We utilized fused deposition modeling-based Big Area Additive Manufacturing technology to print customized, compensated concentric Halbach array rings, using polyphenylene sulfide-bonded NdFeB permanent magnets for polarized neutron reflectometry. The Halbach rings could generate a 0 ≤ B ≤ 0.30 T field, while preserving 90% polarization of an axial neutron beam. Polarized neutron beams are used to study a wide range of structural and magnetic phenomena spanning physics, chemistry, and biology. In this study, we demonstrate the effectiveness of additive manufacturing for producing prototype Halbach arrays, characterize their magnetic properties, and generated magnetic fields, and discuss the conservation of neutron beam polarization as a function of magnetic field.
36 MATERIALS SCIENCE↗
Structure and dynamics of small polyimide oligomers with silicon as a function of aging
The effect of UV curing and shearing on the structure and behavior of a polyimide (PI) binder as it disperses silicon particles in a battery electrode slurry was investigated. PI dispersant effectiveness increases with UV curing time, which controls the overall binder molecular weight. Here, the shear force during electrode casting causes higher molecular weight PI to agglomerate, resulting in battery anodes with poorly dispersed Si particles that do not cycle well. It is hypothesized that when PI binder is added above a critical amount, it conformally coats the silicon particles and greatly impedes Li ion transport. There is an “interzonal region” for binder loading where it disperses silicon well and provides a coverage that facilitates Li transport through the anode material and into the silicon particles. These results have implications in ensuring reproducible electrode manufacturing and increasing cell performance by optimizing the PI structure and coordination with the silicon precursor.
36 MATERIALS SCIENCE↗
Solid Electrolyte Interphase Architecture Determined through In Situ Neutron Scattering
We demonstrate through a combination of in operando solvent exchange and depth-sensitive neutron reflectometry that the solid electrolyte interphase (SEI) formed after the initial lithiation of a silicon anode, using a standard LiPF6 ethylene carbonate/ethyl methyl carbonate electrolyte, is chemically homogeneous across the liquid-solid interface. The data show the SEI is accessible to solvent/salt exchange throughout the layer indicating the poorly bound nature of the SEI components. Further, the data indicates that P-F species, from the decomposition of the LiPF6 salt, are highly mobile and removed from the SEI with solvent exchange. Critically, the SEI layer is structurally homogenous, in contrast to the reports in the literature of an inorganic/organic bilayer, which is important to our understanding of SEI formation and chemistry.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Role of Low Molecular Weight Polymers on the Dynamics of Silicon Anodes During Casting
This work probes the slurry architecture of a high silicon content electrode slurry with and without low molecular weight polymeric dispersants as a function of shear rate to mimic electrode casting conditions for poly(acrylic acid) (PAA) and lithium neutralized poly(acrylic acid) (LiPAA) based electrodes. Rheology coupled ultra-small angle neutron scattering (rheo-USANS) was used to examine the aggregation and agglomeration behavior of each slurry as well as the overall shape of the aggregates. The addition of dispersant has opposing effects on slurries made with PAA or LiPAA binder. With a dispersant, there are fewer aggregates and agglomerates in the PAA based silicon slurries, while LiPAA based silicon slurries become orders of magnitude more aggregated and agglomerated at all shear rates. The reorganization of the PAA and LiPAA binder in the presence of dispersant leads to a more homogeneous slurry and a more heterogeneous slurry, respectively. This reorganization ripples through to the cast electrode architecture and is reflected in the electrochemical cycling of these electrodes.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Machine learning for neutron reflectometry data analysis of two-layer thin films
Neutron reflectometry (NR) is a powerful tool for probing thin films at length scales down to nanometers. We investigated the use of a neural network to predict a two-layer thin film structure to model a given measured reflectivity curve. Application of this neural network to predict a thin film structure revealed that it was accurate and could provide an excellent starting point for traditional fitting methods. Employing prediction-guided fitting has considerable potential for more rapidly producing a result compared to the labor-intensive but commonly-used approach of trial and error searches prior to refinement. A deeper look at the stability of the predictive power of the neural network against statistical fluctuations of measured reflectivity profiles showed that the predictions are stable. We conclude that the approach presented here can provide valuable assistance to users of NR and should be further extended for use in studies of more complex n-layer thin film systems. This result also opens up the possibility of developing adaptive measurement systems in the future.
36 MATERIALS SCIENCE↗
Probing Clustering Dynamics between Silicon and PAA or LiPAA Slurries under Processing Conditions
This work explores the complex interplay between slurry aggregation, agglomeration, and conformation (i.e., shape) of poly(acrylic acid) (PAA)- and lithiated PAA-based silicon slurries as a function of the shear rate and the resulting slurry homogeneity. These values were measured by small-angle neutron scattering (SANS) and rheology-coupled ultra-SANS at conditions relevant to battery electrode casting. Different binder solution preparation methods, either a ball milling (BM) process or a planetary centrifugal mixing (PCM) process, dramatically modify the resulting polymer dynamics and organization around a silicon material. This is due to the different energy profiles of mixing where the more violent and higher energy PCM causes extensive breakdown and reformation of the binder, which is now likely in a branched conformation, while the lower energy BM results in simply lower-molecular weight linear polymers. In conclusion, the breakdown and reorganization of the polymer structure affect silicon slurry homogeneity, which affects subsequent electrode architecture.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Performance Improvements on SNS and HFIR Instrument Data Reduction Workflows Using Mantid
Performance of data reduction workflows at the High Flux Isotope Reactor (HFIR) and the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) is mainly determined by the time spent loading raw measurement events stored in large and sparse datasets. This paper describes: (1) our long-term view to leverage SNS and HFIR data management needs with our experience at ORNL’s world-class high performance computing (HPC) facilities, and (2) our short-term efforts to speed up current workflows using Mantid, a data analysis and reduction community framework used across several neutron scattering facilities. We show that minimally invasive short-term improvements in metadata management have a moderate impact in speeding up current production workflows. We propose a more disruptive domain-specific solution: the No Cost Input Output (NCIO) framework, we provide an overview, the risks and challenges in NCIO’s adoption by HFIR and SNS stakeholders.
Godoy, William↗
From smart homes to smart laboratories: connected instruments for materials science
The current focus on artificial intelligence and machine learning in the scientific community has the potential to greatly speed up discovery. In this article, we explore what a “smart facility” would mean for materials science. We propose to capture meta-data at every step of an experiment, including materials synthesis, sample production and characterization, simulation, and the analysis software used to extract information. Although most of this information is captured in various institutional systems and staff logbooks, more insight could be obtained by connecting this information through a system that allows automation. AI-enabled processes built on such a system would have the potential of making experiment planning easier and minimize the time between experiment and publication.
Doucet, Mathieu↗