Lawrence Berkeley National Laboratory

Abstract: The ATLAS Google Project was established as part of an ongoing evaluation of the use of commercial clouds by the ATLAS Collaboration, in anticipation of the potential future adoption of such resources by WLCG grid sites to fulfil or complement their computing pledges. Seamless integration of Google cloud resources into the worldwide ATLAS distributed computing infrastructure was achieved at large scale and for an extended period of time, and hence cloud resources are shown to be an effective mechanism to provide additional, flexible computing capacity to ATLAS. For the first time a total cost of ownership analysis has been performed, to identify the dominant cost drivers and explore effective mechanisms for cost control. Network usage significantly impacts the costs of certain ATLAS workflows, underscoring the importance of implementing such mechanisms. Resource bursting has been successfully demonstrated, whilst exposing the true cost of this type of activity. A follow-up to the project is underway to investigate methods for improving the integration of cloud resources in data-intensive distributed computing environments and reducing costs related to network connectivity, which represents the primary expense when extensively utilising cloud resources.

The discovery of ~80 K superconductivity in nickelate La3Ni2O7 under pressure has ignited intense interest. Here, we present a comprehensive first-principles study of the electron-phonon (e-ph) coupling in La3Ni2O7 and its implications on the observed superconductivity. Our results conclude that the e-ph coupling is too weak (with a coupling constant λ ≲ 0.5) to account for the high Tc, albeit interesting many-electron correlation effects exist. While Coulomb interactions (via GW self-energy and Hubbard U) enhance the e-ph coupling strength, electron doping (oxygen vacancies) introduces no major changes. Additionally, different structural phases display varying characteristics near the Fermi level, but do not alter the conclusion. The e-ph coupling landscape of La3Ni2O7 is intrinsically different from that of infinite-layer nickelates. These findings suggest that a phonon-mediated mechanism is unlikely to be responsible for the observed superconductivity in La3Ni2O7, pointing instead to an unconventional nature.

Artificial Intelligence (AI) applications critically depend on data. Poor-quality data produces inaccurate and ineffective AI models that may lead to incorrect or unsafe use. Evaluation of data readiness is a crucial step in improving the quality and appropriateness of data usage for AI. R&D efforts have been spent on improving data quality. However, standardized metrics for evaluating data readiness for use in AI training are still evolving. In this study, we perform a comprehensive survey of metrics used to verify data readiness for AI training. This survey examines more than 140 papers published by ACM Digital Library, IEEE Xplore, journals such as Nature, Springer, and Science Direct, and online articles published by prominent AI experts. This survey aims to propose a taxonomy of data readiness for AI (DRAI) metrics for structured and unstructured datasets. We anticipate that this taxonomy will lead to new standards for DRAI metrics that would be used for enhancing the quality, accuracy, and fairness of AI training and inference.

This study presents the results from in-well hydraulic fracture monitoring within a horizontal well in an unconventional reservoir utilizing Distributed Fiber Optic Sensing (DFOS). An in-house-developed Brillouin-based Distributed Strain Sensing (DSS) interrogator was deployed to obtain strain measurements, complemented by a commercial Raman-based Distributed Temperature Sensing (DTS) interrogator for temperature measurements and a commercial Rayleigh-based Low-Frequency Distributed Acoustic Sensing (LF-DAS) interrogator for strain-rate measurements. Examined over a ten-day period, the spatio-temporal distribution of temperature-compensated strain obtained from DSS and DTS revealed distinct signatures of the multi-stage hydraulic fracturing process. These signatures were analyzed with respect to fracture width growth and closure, residual strain effects, and fracture conductivity near the wellbore. Fracture widths within the fracture zone were estimated for individual stages. The findings were assessed with LF-DAS measurements for further evaluation. This work integrates DFOS-measured strain, temperature, and strain-rate data for monitoring in-well hydraulic fracturing, with the goal of supporting future studies in interpreting DFOS measurements for improved understanding of hydraulic fracturing in unconventional reservoirs.

Cement production is a large global industry that is a significant source of carbon dioxide (CO2) emissions, from both energy-derived and process-derived sources. Cement is crucial for concrete, the most widely used building material. There are growing pushes for policies that encourage cement production with net-zero greenhouse gas emissions. Effective policymaking requires understanding the barriers to adoption of emission-lowering strategies, the existing policy framework, and potential regulations for emission reduction. In this work, we examine these parameters within the context of California’s recent net-zero emissions cement bill, Senate Bill 596, focusing on six key decarbonization strategies. We highlight key barriers for these mechanisms and policy strategies that could support a transition to lower emissions. Some crucial actions are public procurement and replacement of prescriptive design codes with performance-based approaches to create a marketplace for novel cements; refine models and conduct pilot projects to study novel cement or mixture performance, durability and costs; and increase awareness with education and communication campaigns directed at stakeholders. Policy actions can be adopted and adapted in other regions that will design net-zero emissions policies.

Methods to sequester and store atmospheric CO2 are critical to combat climate change. Alkaline-rich bioashes are potential carbon fixing materials. This work investigates potential co-benefits from mineralizing carbon in biomass ashes and partially replacing high embodied greenhouse gas (GHG) Portland cement (PC) in cement-based materials with these ashes. Specifically, rice hull ash (RHA), wheat straw ash (WSA), and sugarcane bagasse ash (SBA) were treated to mineralize carbon, and their experimental carbon content was compared to modeled potential carbonation. To understand changes in the cement-based storage materials, mortars made with CO2-treated WSA and RHA were experimentally compared to PC-only mortars and mortars made with ashes without prior CO2 treatment. Life cycle assessment methodology was applied to understand potential reductions in GHG emissions. The modeled carbonation was ∼18 g-CO2/kg-RHA and ∼180 g-CO2/kg-WSA. Ashes oxidized at 500 °C had the largest measured carbon content (5.4 g-carbon/kg-RHA and 35.3 g-carbon/kg-WSA). This carbon appeared to be predominantly residual from the biomass. Isothermal calorimetry showed RHA-PC pastes had similar heat of hydration to PC-pastes, while WSA-PC pastes exhibited an early (at ∼1.5 min) endothermic dip. Mortars with 5 % and 15 % RHA replacement had 1–12 % higher compressive strength at 28 days than PC-only mortars, and milled WSA mortars with 5 % replacement had 3 % higher strength. A loss in strength was noted for the milled 15 % WSA, the CO2-treated 5 %, and the 15 % WSA mortars. Modeled reductions in GHG emissions from CO2-treated ashes were, however, marginal (<1 %) relative to the untreated ashes.

The persistence of bacteria in the root canal system is the primary cause of recurrent apical periodontitis. The adaptability of residual bacteria to changing environmental conditions is a key survival strategy of biofilms, often leading to endodontic treatment failure. DJK-5 is a protease-resistant, broad-spectrum D-enantiomeric peptide that degrades or prevents the accumulation of guanosine penta- and tetraphosphates, which are important for biofilm formation. We evaluated the effects of primary antimicrobial agents and nutrient conditions on the recovery, metabolism, diversity, and composition of oral biofilms, and investigated how these factors affect the efficacy of DJK-5 and chlorhexidine (CHX) during re-exposure. Primary irrigants and nutrient conditions significantly influenced biofilm recovery, metabolic activity, diversity, and composition. Biofilm recovery was slower in nutrient-poor groups compared to nutrient-rich ones, and nutrient availability had the greatest effect on shaping both the diversity and composition of the biofilms. Water and DJK-5 groups showed similar biofilm diversity trends, while CHX generally led to lower diversity. Results indicate that primary irrigants and nutrient conditions significantly impact biofilm composition, diversity, and recovery. However, these changes did not compromise DJK-5s effectiveness in killing of biofilm microbes during re-exposure of recovered biofilms.