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At least 865 records · Page 48

Challenges for a QCD axion at the 10 MeV scale

We report on an interesting realization of the QCD axion, with mass in the range $\mathcal{O}$(10) MeV. It has previously been shown that although this scenario is stringently constrained from multiple sources, the model remains viable for a range of parameters that leads to an explanation of the Atomki experiment anomaly. In this article we study in more detail the additional constraints proceeding from recent low energy experiments and study the compatibility of the allowed parameter space with the one leading to consistency of the most recent measurements of the electron anomalous magnetic moment and the fine structure constant. We further provide an ultraviolet completion of this axion variant and show the conditions under which it may lead to the observed quark masses and CKM mixing angles, and remain consistent with experimental constraints on the extended scalar sector appearing in this Standard Model extension. In particular, the decay of the Standard Model-like Higgs boson into two light axions may be relevant and leads to a novel Higgs boson signature that may be searched for at the LHC in the near future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Unraveling the Hsp70-ROS-autophagy axis in pentachlorophenol-challenged lung and liver epithelial cells

Pentachlorophenol (PCP) was extensively utilized as an organochlorine pesticide and wood preservative in the United States from the 1930s until the Environmental Protection Agency (EPA) imposed restrictions due to concerns about its toxicity and potential carcinogenic properties. Although it is no longer widely used, PCP remains a concern due to its environmental persistence and potential for long-term health effects. Significant occupational and environmental exposures have likely occurred, with the health and economic costs of PCP exposure potentially being substantial given its known toxicity. Notably, PCP exhibits rapid absorption through both the skin and respiratory system and has been shown to cause hepatotoxicity, developmental toxicity, immunotoxicity, irritation, and carcinogenicity in laboratory animal studies. PCP exposure induces oxidative stress, a key mechanism underlying its inflammatory and toxic effects, which can activate cellular stress responses including upregulation of heat shock protein 70 (Hsp70). Previous studies in lung and liver epithelial cells have shown that Hsp70 and oxidative stress play pivotal roles in triggering autophagy. This study establishes the critical role of the Hsp70-reactive oxygen species (ROS)-autophagy axis in regulating cellular responses to PCP exposure in human alveolar (A549) and liver carcinoma (HepG2) epithelial cells. Our research elucidated the molecular mechanisms underlying PCP's cellular effects, demonstrating that its exposure resulted in increased expression of autophagy-related proteins (Beclin-1, LC3B, ATG12, and ATG16), subunits of NADPH oxidase (NCF-1, NCF-2, NOX2, and Rac), and antioxidant proteins (SOD and GPx) in both lung and liver cell types. Notably, PCP augmented the interaction between Hsp70 and the autophagy regulator Beclin-1. Pretreatment with the ROS inhibitor N-acetylcysteine or Hsp70 knockdown markedly reversed PCP-induced responses. Our in-silico protein–protein docking analysis and molecular dynamics simulation studies revealed enhanced interactions and/or stable confirmations maintained throughout the simulations for TLR4-Hsp70 and Hsp70-Beclin-1 complexes in the presence of PCP. These findings provide a strong foundation for future studies, employing in vivo experimental models and human populations to identify promising targets for PCP-induced toxicity and cellular injury. As a result, these findings may have far-reaching implications for public health and environmental policy, ultimately leading to the identification of biomarkers and the development of more effective interventions for environmentally induced toxicity and diseases.

97 MATHEMATICS AND COMPUTING↗

Progress and Challenges in Self-Healing Cementitious Materials

Concrete is the most used man-made material today consisting of a mixture of aggregates (sand, gravel, crashed rock) and paste. The paste component, made up of cement and water, cracks with time. Despite this shortcoming, research towards next-generation cement and concrete has only taken a boost in the past 10-15 years. In particular, self-healing cementitious materials is a research area that has attracted a great deal of attention. A number of reported novel formulations have demonstrated an increase in mechanical and chemical stability with respect to conventional Portland cement, through the addition of inorganic, organic, and even biological additives. This review reports on the latest advances in cement research related to the synthesis of self-healing cements applied in concrete structures. These include geopolymers, engineered cementitious materials (ECC), bacterial cement composites, microencapsulated self-healing materials, shape memory alloys (SMA), and polymer-cement composites. This work describes the performance of each cementitious material and the mechanism responsible for self-healing, including a section on the latest computational modeling studies towards this end. A detailed understanding of these various self-healing cement technologies, including their strengths and weaknesses, is critical at the time of determining the type of structures that these materials could be used for.

Fernandez, Carlos A.↗

Additive manufacturing: a challenge to nuclear nonproliferation

Additive manufacturing (AM) is a rapidly developing technology that allows industries to automate and simplify the production of highly complicated items. Recently, there are concerns that AM techniques have the potential to be utilized in the fields of nuclear weapons and nuclear enrichment technology. Presently, there are very few international or domestic export controls that apply to AM's role in the nuclear industry, constituting an unmanaged proliferation pathway. Pre-existing export controls focus on general concepts and processes and do not consider specific nuances of various techniques that are categorized as additive manufacturing. To introduce legislation and controls that will be effective in monitoring proliferation pathways, one must investigate and characterize AM techniques and their nuclear applications. This paper categorizes and ranks 33 AM techniques based on their potential impact on the nuclear fuel cycle and the development of nuclear weapons. Through this method of characterization and categorization, export controls would address specific AM nuclear proliferation risks without disrupting the entire industry and fuel cycle. Additionally, legislation employing this method would identify loopholes in export controls using a holistic approach to managing and monitoring proliferation pathways.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Interlaboratory Study of Digital Volume Correlation Error Due to X-Ray Computed Tomography Equipment and Scan Parameters: an Update from the DVC Challenge

Background: The quality of Digital Volume Correlation (DVC) full-field displacement measurements depends directly on the characteristics of the X-ray Computed Tomography (XCT) equipment, and scan procedures used to acquire the tomographic images. Objective: In this work, we seek to experimentally study the effects of XCT equipment and tomographic scan procedures on the quality of these images for DVC analysis, and to survey the level of DVC error that may be achieved using standard XCT operating procedures. Methods: Six participants in an interlaboratory study acquired high-quality XCT scans of a syntactic foam before and after rigid body motion. The resulting images were correlated using commercial DVC software to quantify error sources due to random image noise, reconstruction artifacts, as well as systematic spatial or temporal distortion. Results: In the absence of rigid body motion, the standard deviation of the displacement measurements ranged from 0.012 to 0.043 voxels using a moderate subvolume size, indicating that subvoxel measurement resolution could readily be achieved with a variety of XCT equipment and scan recipes. Comparison of consecutive scans without rigid body motion showed transient dilatational displacement gradients due to self-heating of the X-ray source and/or thermal expansion of the foam. Evaluation of the scans after rigid body motion showed significant, machine-specific spatial distortion in the displacement fields of up to 0.5 voxels; new approaches to remove this error need to be developed. Conclusions: Analysis of the scan protocols used in the interlaboratory study, as well as a complementary parametric sensitivity study, showed that the DVC error was strongly influenced by the XCT equipment, but could be mitigated by adjusting the total scan duration.

47 OTHER INSTRUMENTATION↗

Solving Recent Challenges for Wrought Ni-Base Superalloys

This paper reviews the status of technology in design and manufacture of new wrought 21 polycrystalline Ni-base superalloys for critical engineering applications. There is a strong 22 motivation to develop new alloys that are capable of operating at higher temperatures to 23 realise improvements in thermal efficiency, which are necessary to achieve environmental 24 targets for reduced emissions of harmful green-house gases. From the aerospace sector, 25 the development of new powder metallurgy and ingot metallurgy alloys are discussed for 26 disk rotor and static applications. New compositions for powder metallurgy contain about 27 50-55% of gamma prime (γ') strengthening precipitates to ensure components operate 28 successfully at temperatures up to 788°C (1450°F). In contrast, new compositions for ingot 29 metallurgy aim to occupy a design space in temperature capability between Alloy 718 and 30 current powder alloys that are in-service, and show levels of γ' of about 30-44%. The focus 31 in developing these alloys was design for manufacturability. To complement the aerospace 32 developments, a review of work to understand the suitability of candidate alloys for multiple 33 applications in Advanced-Ultra Supercritical (AUSC) power plants has been undertaken by 34 Detrois, Jablonski and Hawk from the National Energy Technology Laboratory. In these 35 power plants, steam temperatures are required to reach 700-760°C. The common thread is 36 to develop alloys that demonstrate a combination of high temperature properties, which are 37 reliant on both the alloy composition and microstructure and can be produced readily at the 38 right price. For the AUSC applications, the emphasis is on high temperature strength, long 39 term creep life, phase stability, oxidation resistance and robust welding for fabrications. 40 Whereas for powder disk rotors in aircraft engines, the priority is enhanced resistance to 41 time dependent crack growth, phase stability and resistance to environmental damage, while 42 extending the current strength levels, which are shown by existing alloys, to higher 43 temperatures.

36 MATERIALS SCIENCE↗

Data Science Techniques, Assumptions, and Challenges in Alloy Clustering and Property Prediction

Data analytics methods have been increasingly applied to understanding materials chemistry, processing due to the manufacturing approach, and uni-axial and cyclic property relationships in the highly complex space of alloy design. There are several benefits to applying data analytics to this space, including the ability to manage non-linearities in the responses of the alloy attributes and the resulting mechanical properties. However, key difficulties in applying and understanding the results of data analytics include the often lack of reported assumptions and data processing steps necessary to improve interpretation and reproducibility in derived results. In this work, the methods used to generate clustering and correlation analyses for experimental 9% Cr ferritic-martensitic steel data were investigated and the resulting implications for mechanical property predictions were assessed. This work uses principal component analysis, partitioning around medoids, t-SNE, and k-means clustering to investigate trends in composition, processing and microstructure information with creep and tensile properties, building on work done previously using a smaller version of the same dataset. The initial assumptions, preprocessing steps and methods are investigated and outlined in order to depict the fine level of detail required to convey the steps taken to process data and produce analytical results. Here, the variations in the resulting analyses are explored due to the influence of new and more varied data.

36 MATERIALS SCIENCE↗

Electrification of industrial boilers in the USA: potentials, challenges, and policy implications

Decarbonization of the industrial heat demand through electrification could contribute significantly to climate change mitigation efforts. In the US industry, thermal processes accounted for 75% of the total final energy demand in 2018, of which 17% is consumed by conventional industrial boilers (excluding cogeneration) for steam generation. Electric boilers have a small share in the US industrial steam generation due to several techno-economic reasons. Here, this study employs a bottom-up approach to investigate the sector-level and state-level techno-enviro-economic potentials of deploying electric boilers in the US industry in different timeframes. The results show that the technical potential energy and CO 2 savings by electrifying industrial boilers are 595 PJ and 200 MtCO 2 per year in 2050, respectively; however, these incur additional costs in each sector. Although there may be individual cost-effective opportunities for electrifying boilers in specific industrial sites, the overall costs are high in all industrial sectors and states due to the large disparity between electricity and combustion fuel prices. To overcome the highlighted techno-economic barriers, a comprehensive action plan for different stakeholders is also formulated. This study provides novel insights that should inform policymakers’ and executives’ decisions about the electrification of the current and future US industrial boiler systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Challenges and opportunities of machine learning control in building operations

Machine learning control (MLC) is a highly flexible and adaptable method that enables the design, modeling, tuning, and maintenance of building controllers to be more accurate, automated, flexible, and adaptable. The research topic of MLC in building energy systems is developing rapidly, but to our knowledge, no review has been published that specifically and systematically focuses on MLC for building energy systems. Here this paper provides a systematic review of MLC in building energy systems. We review technical papers in two major categories of applications of machine learning in building control: (1) building system and component modeling for control, and (2) control process learning. We identify MLC topics that have been well-studied and those that need further research in the field of building operation control. We also identify the gaps between the present and future application of MLC and predict future trends and opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗