Publications

Results 4801–4900 of 99,299

Search results

Jump to search filters

First-principles simulation of light-ion microscopy of graphene

2D Materials

Kononov, Alina K.; Olmstead, Alexandra; Baczewski, Andrew D.; Schleife, Andre

The extreme sensitivity of 2D materials to defects and nanostructure requires precise imaging techniques to verify presence of desirable and absence of undesirable features in the atomic geometry. Helium-ion beams have emerged as a promising materials imaging tool, achieving up to 20 times higher resolution and 10 times larger depth-of-field than conventional or environmental scanning electron microscopes. Here, we offer first-principles theoretical insights to advance ion-beam imaging of atomically thin materials by performing real-time time-dependent density functional theory simulations of single impacts of 10-200 keV light ions in free-standing graphene. We predict that detecting electrons emitted from the back of the material (the side from which the ion exits) would result in up to three times higher signal and up to five times higher contrast images, making 2D materials especially compelling targets for ion-beam microscopy. This predicted superiority of exit-side emission likely arises from anisotropic kinetic emission. The charge induced in the graphene equilibrates on a sub-fs time scale, leading to only slight disturbances in the carbon lattice that are unlikely to damage the atomic structure for any of the beam parameters investigated here.

More Details
TYPE Journal Article YEAR 2022
DOIOSTIScopus

Rachel Wood Consulting - Viga Span Tables

Bosiljevac, Thomas B.

The purpose and scope of the viga span tables project for Rachel Wood Consulting (RWC) is focused on producing tabulated beam span tables for three species of wood vigas commonly used in New Mexico to allow producers, designers and builders to incorporate vigas into their building designs in a prescriptive manner similar to the span tables for sawn lumber incorporated into the International Residential Code (IRC) or the International Log Builders Association (ILBA) publication. The information provided in this report and the associated viga span tables also attempts to address and clarify questions raised by RWC during their review of the 2018 Los Alamos National Laboratory (LANL) New Mexico Small Business Assistance (NMSBA) program report by August Mosimann pertaining to span lengths, loading, deflection calculations, and log grading certification prior to submitting the span tables to the Construction Industries Division (CID) of New Mexico.

More Details
TYPE Other Report YEAR 2022
OSTIDOI

Viability of S3 Object Storage for the ASC Program at Sandia

Kordenbrock, Todd; Templet, Gary J.; Ulmer, Craig; Widener, Patrick

Recent efforts at Sandia such as DataSEA are creating search engines that enable analysts to query the institution’s massive archive of simulation and experiment data. The benefit of this work is that analysts will be able to retrieve all historical information about a system component that the institution has amassed over the years and make better-informed decisions in current work. As DataSEA gains momentum, it faces multiple technical challenges relating to capacity storage. From a raw capacity perspective, data producers will rapidly overwhelm the system with massive amounts of data. From an accessibility perspective, analysts will expect to be able to retrieve any portion of the bulk data, from any system on the enterprise network. Sandia’s Institutional Computing is mitigating storage problems at the enterprise level by procuring new capacity storage systems that can be accessed from anywhere on the enterprise network. These systems use the simple storage service, or S3, API for data transfers. While S3 uses objects instead of files, users can access it from their desktops or Sandia’s high-performance computing (HPC) platforms. S3 is particularly well suited for bulk storage in DataSEA, as datasets can be decomposed into object that can be referenced and retrieved individually, as needed by an analyst. In this report we describe our experiences working with S3 storage and provide information about how developers can leverage Sandia’s current systems. We present performance results from two sets of experiments. First, we measure S3 throughput when exchanging data between four different HPC platforms and two different enterprise S3 storage systems on the Sandia Restricted Network (SRN). Second, we measure the performance of S3 when communicating with a custom-built Ceph storage system that was constructed from HPC components. Overall, while S3 storage is significantly slower than traditional HPC storage, it provides significant accessibility benefits that will be valuable for archiving and exploiting historical data. There are multiple opportunities that arise from this work, including enhancing DataSEA to leverage S3 for bulk storage and adding native S3 support to Sandia’s IOSS library.

More Details
TYPE SAND Report YEAR 2022
DOIOSTI

Magnetically Ablated Reconnection on Z (MARZ) collaboration

Hare, Jack; Datta, Rishabh; Lebedev, Sergey; Chittenden, Jeremy P.; Crilly, Aidan; Halliday, Jack; Chandler, Katherine M.; Jennings, Christopher A.; Ampleford, David J.; Bland, Simon; Aragon, Carlos; Yager-Elorriaga, David A.; Hansen, Stephanie B.; Shipley, Gabriel A.; Webb, Timothy J.; Harding, Eric H.; Robertson, G.K.; Montoya, Michael M.; Kellogg, Jeffrey; Harmon, Roger; Molina, Leo

Abstract not provided.

More Details
TYPE Conference Presentation YEAR 2022
DOIOSTI

Perspectives on the integration between first-principles and data-driven modeling

Computers and Chemical Engineering

Bradley, William; Kim, Jinhyeun; Kilwein, Zachary A.; Blakely, Logan; Eydenberg, Michael S.; Jalvin, Jordan; Laird, Carl; Boukouvala, Fani

Efficiently embedding and/or integrating mechanistic information with data-driven models is essential if it is desired to simultaneously take advantage of both engineering principles and data-science. The opportunity for hybridization occurs in many scenarios, such as the development of a faster model of an accurate high-fidelity computer model; the correction of a mechanistic model that does not fully-capture the physical phenomena of the system; or the integration of a data-driven component approximating an unknown correlation within a mechanistic model. At the same time, different techniques have been proposed and applied in different literatures to achieve this hybridization, such as hybrid modeling, physics-informed Machine Learning (ML) and model calibration. In this paper we review the methods, challenges, applications and algorithms of these three research areas and discuss them in the context of the different hybridization scenarios. Moreover, we provide a comprehensive comparison of the hybridization techniques with respect to their differences and similarities, as well as advantages and limitations and future perspectives. Finally, we apply and illustrate hybrid modeling, physics-informed ML and model calibration via a chemical reactor case study.

More Details
TYPE Journal Article YEAR 2022
DOIOSTIScopus

Reconfiguration of the Respiratory Tract Microbiome to Prevent and Treat Burkholderia Infection

Branda, Steven; Collette, Nicole; Aiosa, Nicole; Garg, Neha; Mageeney, Catherine M.; Williams, Kelly P.; Phillips, Ashlee; Hern, Kelsey; Arkin, Adam; Ricken, Bryce; Wilde, Delaney; Dogra, Sahiba; Humphrey, Brittany; Poorey, Kunal; Courtney, Colleen

New approaches to preventing and treating infections, particularly of the respiratory tract, are needed. One promising strategy is to reconfigure microbial communities (microbiomes) within the host to improve defense against pathogens. Probiotics and prebiotics for gastrointestinal (GI) infections offer a template for success. We sought to develop comparable countermeasures for respiratory infections. First, we characterized interactions between the airway microbiome and a biodefense-related respiratory pathogen (Burkholderia thailandensis; Bt), using a mouse model of infection. Then, we recovered microbiome constituents from the airway and assessed their ability to re-colonize the airway and protect against respiratory Bt infection. We found that microbiome constituents belonging to Bacillus and related genuses frequently displayed colonization and anti-Bt activity. Comparative growth requirement profiling of these Bacillus strains vs Bt enabled identification of candidate prebiotics. This work serves as proof of concept for airway probiotics, as well as a strong foundation for development of airway prebiotics.

More Details
TYPE SAND Report YEAR 2022
DOIOSTI

Grey Zone Test Range Social Model

Doyle, Casey L.; Gunda, Thushara; Bernard, Michael

The Grey Zone Test Range (GZTR) social model operates as a piece of the overall GZTR modeling effort. It works in conjunction with supply models for resources, an electric grid model for power availability, and a traffic model for road congestion, as well as a general controller framework that allows external system effects. The social model functions as an aggregate model where the entire population of the city is divided into groups based on the Transportation Analysis Zones (TAZs), a common geospatial boundary present in all GZTR models. These groups will act as a singular community; each time step the state of the system around them will be assessed and then community will come up with a general plan of action that they will attempt to follow for the day. Additionally, they will track values for their general emotional state and memory about negative impacts in the near past.

More Details
TYPE Other Report YEAR 2022
DOIOSTI
Results 4801–4900 of 99,299
Results 4801–4900 of 99,299