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At least 829 records · Page 46

Molecular dynamics simulation of thermal transport in UO 2 containing uranium, oxygen, and fission-product defects

Uranium dioxide (UO 2 ) is the most commonly used fuel in light-water nuclear reactors and thermal conductivity controls the removal of heat produced by fission, thereby governing fuel temperature during normal and accident conditions. The use of fuel performance codes by the industry to predict operational behavior is widespread. A primary source of uncertainty in these codes is thermal conductivity, and optimized fuel utilization may be possible if existing empirical models are replaced with models that incorporate explicit thermal-conductivity-degradation mechanisms during fuel burn up. This approach is able to represent the degradation of thermal conductivity due to each individual defect type, rather than the overall burn-up measure typically used, which is not an accurate representation of the chemical or microstructure state of the fuel that actually governs thermal conductivity and other properties. To generate a mechanistic thermal conductivity model, molecular dynamics (MD) simulations of UO 2 thermal conductivity including representative uranium and oxygen defects and fission products are carried out. These calculations employ a standard Buckingham-type interatomic potential and a potential that combines the many-body embedded-atom-method potential with Morse-Buckingham pair potentials. Potential parameters for UO 2+x and ZrO 2 are developed for the latter potential. Physical insights from the resonant phonon-spin-scattering mechanism due to spins on the magnetic uranium ions are introduced into the treatment of the MD results, with the corresponding relaxation time derived from existing experimental data. High defect scattering is predicted for Xe atoms compared to that of La and Zr ions. Uranium defects reduce the thermal conductivity more than oxygen defects. For each defect and fission product, scattering parameters are derived for application in both a Callaway model and the corresponding high-temperature model typically used in fuel-performance codes. The model is validated by comparison to low-temperature experimental measurements on single-crystal hyperstoichiometric UO 2+x samples and high-temperature literature data. Furthermore, this work will enable more accurate fuel-performance simulations and will extend to new fuel types and operating conditions, all of which improve the fuel economics of nuclear energy and maintain high fuel reliability and safety.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Modeling MTS pyrolysis and SiC deposition kinetics using principal component analysis and neural networks

Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.

autoencoder neural networks↗

Deadtime Determination of Helium Detector Using MCNP Code

In detector systems, the minimum time separation between the events is called detector's deadtime. The The intrinsic properties of the detector and the pulse processing circuitry's characteristics are the sources of deadtime. Researchers have been working on improving a detector deadtime model that can implicitly characterize a detection system's behavior while reducing counting errors. There are two commonly known dead-time models: the 'Paralyzing' and the 'Non-paralyzing' models. In reality, detection systems fit neither of these idealized models perfectly, instead falling somewhere between the two models. The paralyzing model is mathematically expressed by eq. 1, where m is the measured count rate, n is the true count rate and t is dead-time. This model assumes that each event during the dead-time will reset it to a fixed duration, thus extending the deadtime. The dead-time extension depends on the count rate. According to the non-paralyzing model, deadtime is fixed after each detected event, and all events occurring during deadtime are lost. The fraction of time during which an apparatus is sensitive is 1-mt. Therefore, the fraction of the true number of events can be recorded. In this study, a Canberra {sup 3}He neutron detector (0.5NH1/1K) deadtime value was estimated using a combination of experimental subcritical assembly measurements and theoretical MCNP simulations. The deadtime of the Canberra 10 mm diameter {sup 3}He tube detector was calculated by comparing measured counts from different locations in the subcritical assembly at Missouri University of Science and Technology Reactor (MSTR) with MCNP (Monte Carlo N-Particle Code) simulations. The deadtime calculations are provided for both the paralyzing and non-paralyzing models for the Canberra 10 mm diameter {sup 3}He tube detector. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Electrolytic Oxide Reduction of Plutonium Oxide Surrogates

Our research team has investigated electrolytic oxide reduction (EOR) as an improved metal production process versus the currently employed multiple cycle direct oxide reduction (MCDOR) process for the conversion of plutonium oxide to plutonium metal. Inherent advantages in safety, waste generation, efficiency, and operational ease make EOR an attractive alternative to traditional metal production practices. Phase I of the project consisted of the construction of a prototype electrochemical cell, and proof of concept experiments towards the reduction of SnO 2 and CeO 2 compounds. Phase II of the project was focused on the optimization of the cerium system in preparation for future plutonium EOR experiments. We observed the electrolytic reduction of cerium oxide resulting in mixed degrees of success, and discovered this was a result of parasitic side reactions and partial reduction. We employed cyclic voltammetry (CV) to identify the products of these side reactions and characterize partially reduced species. We also observed that, when metal was successfully produced by EOR, a large amount of passed charge was required. We concluded that this observation was due to several inefficiencies of the process relating to the reduction mechanism (e.g. inefficient use of cathodically produced calcium). We used our CV results to guide our optimization of the EOR of CeO 2 by refining our electrochemical method, cell geometry, and materials of construction. Finally, we developed a next generation cell, worked to establish a new molten salt electrochemical capability in the Plutonium Facility, and completed a strategy for plutonium experiments. Our electrochemical method to produce plutonium metal clearly supports the core mission of the laboratory. Furthermore, this project has allowed for the development of capabilities that will provide valuable data to programs interested in characterization and detection, as well as science of signatures. Additionally, establishing this capability in the plutonium facility will facilitate future safeguard studies that can assist with safeguard development in molten salt reprocessing flowsheets, and molten salt reactor designs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring Acceleration Schemes for Nonlinear Heat Equations in Fusion Reactor Modeling

Plasma modeling inside a tokamak reactor poses a challenging and often times computationally expensive endeavor. The process of running these simulations has the potential to increase the predictive capabilities of these models. Here we investigate the effect particular acceleration schemes, mainly Anderson Acceleration, have on a nonlinear transport equation solver, Tango, developed by Parker et al. We show that Anderson acceleration offers a method for decreasing the computational cost through a test problem developed by Shestakov et al, which shows promise towards utilizing Anderson Acceleration in complex transport simulations

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA Reactor Facility Hazards Summary

The Lewis Research Center of the National Aeronautics and Space Administration proposes to build a nuclear research reactor which will be located in the Plum Brook Ordnance Works near Sandusky, Ohio. The purpose of this report is to inform the Advisory Committee on Reactor Safeguards of the U. S. Atomic Energy Commission in regard to the design Lq of the reactor facility, the characteristics of the site, and the hazards of operation at this location. The purpose of this research reactor is to make pumped loop studies of aircraft reactor fuel elements and other reactor components, radiation effects studies on aircraft reactor materials and equipment, shielding studies, and nuclear and solid state physics experiments. The reactor is light water cooled and moderated of the MTR-type with a primary beryllium reflector and a secondary water reflector. The core initially will be a 3 by 9 array of MTR-type fuel elements and is designed for operation up to a power of 60 megawatts. The reactor facility is described in general terms. This is followed by a discussion of the nuclear characteristics and performance of the reactor. Then details of the reactor control system are discussed. A summary of the site characteristics is then presented followed by a discussion of the larger type of experiments which may eventually be operated in this facility. The considerations for normal operation are concluded with a proposed method of handling fuel elements and radioactive wastes. The potential hazards involved with failures or malfunctions of this facility are considered in some detail. These are examined first from the standpoint of preventing them or minimizing their effects and second from the standpoint of what effect they might have on the reactor facility staff and the surrounding population. The most essential feature of the design for location at the proposed site is containment of the maximum credible accident.

Source record↗

Small CaH{sub 2} Moderated Thermal Reactor for Surface Power Generation II: Core Neutronics Design

National Aeronautics and Space Administration (NASA) is considering to adopt a small nuclear reactor for the planned Mars surface mission. The required specifications of the reactor system are: 10- to 100-kW electric power with power density above 5 We/kg; 8-year stable operation. In the proposed study, stretch goals for this surface power system were set as: electric power of 20 kWe with total system weight below 1000 kg. Furthermore, nuclear security and nuclear safety in the case of launch accidents must be considered for surface power systems, therefore, selecting low enriched uranium (LEU, = 20 wt% of {sup 235}U/U) is preferable due to its lower criticality. However, the reactor core weight tends to increase in the case of a reactor with LEU fuel, because relatively larger-mass core is required to achieve the critical. The essential feature of the space reactor core neutronics design is to balance between the nuclear security and safety, and the mass reduction of the core. Some feasible methods to reduce the core mass in the case of the LEU core are: (1) optimized neutron moderation, (2) reduce neutron leakage, and (3) increase multiplication of neutron. A solid moderator has been proposed by Kimura et.al.: neutron leakage control and neutron multiplicity will be featured in the current study. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Theoretical Calculation and Simulation Studies of Balancing Forces and Axisymmetric Poloidal Halo Current in EAST

A new technology for developing fusion energy is to use hydrogen isotopes i.e., deuterium (D) and tritium (T) which is a combine effort for building up of International Thermonuclear Reactor (ITER) named as Tokamak, which will come into operation in 2020. Handsome amount of work has already been performed by many scientists contingent with plasma shape, halo current and plasma equilibrium properties by numerical techniques. Halo current calculation is the most important work in fusion reactors. In this paper, halo current and plasma cross-section energy have been calculated. The research covers calculation of plasma energy and determines the force on the vessel by magnetic field transformation method, which is the essential part of calculating halo current. Further, vertical displacement event (VDE) up/down halo current models have been calculated. These models give total magnetic field, asymmetric forces, conducting points and poloidal halo current.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modular fabrication and characterization of complex silicon carbide composite structures Advanced Reactor Technologies (ART) Research Final Report (Feb 2015 – May 2017)

Advanced ceramic materials exhibit properties that enable safety and fuel cycle efficiency improvements in advanced nuclear reactors. In order to fully exploit these desirable properties, new processing techniques are required to produce the complex geometries inherent to nuclear fuel assemblies and support structures. Through this project, the state of complex SiC-SiC composite fabrication for nuclear components has advanced significantly. New methods to produce complex SiC-SiC composite structures have been demonstrated in the form factors needed for in-core structural components in advanced high temperature nuclear reactors. Advanced characterization techniques have been employed to demonstrate that these complex SiC-SiC composite structures provide the strength, toughness and hermeticity required for service in harsh reactor conditions. The complex structures produced in this project represent a significant step forward in leveraging the excellent high temperature strength, resistance to neutron induced damage, and low neutron cross section of silicon carbide in nuclear applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quantifying irradiation defects in zirconium alloys: a comparison between transmission electron microscopy and whole-pattern diffraction line-profile analysis - 2016-0089

Irradiation-induced dislocations significantly affect the mechanical properties of zirconium alloys, altering slip and influencing creep and growth. Thus, the quantitative characterization of irradiation defects as a function of fluence, cold work, and/or thermal treatments is important for models that attempt to predict their impact on properties. Whole-pattern diffraction line-profile analysis (DLPA) is a well-established modern tool for microstructure characterization based on first-principle physical models for dislocation density measurements in plastically deformed materials. However, applying these DLPA methods directly to irradiated materials yields higher than expected dislocation density values compared with historical transmission electron microscopy (TEM) measurements and past line-broadening analysis studies calibrated to TEM observations. In an effort to understand these differences, a new microstructural model was developed for DLPA to specifically address dislocation structures consisting of elliptical - and -component loops. To compare the refined DLPA method with TEM measurements, high-resolution neutron diffraction patterns on nonirradiated and irradiated Zr-2.5Nb samples were collected with the Neutron Powder Diffractometer instrument at the Los Alamos Neutron Science Center and were evaluated. High-resolution TEM measurements were performed at the Reactor Materials Testing Laboratory, Queen's University, for comparison with the DLPA results. The capabilities and inherent uncertainties of both the refined DLPA and TEM methods are compared and discussed in detail. We show that the differences between the density values provided by DLPA and TEM are inherent to the methods and can be reconciled with the interpretation of the data. (authors)

36 MATERIALS SCIENCE↗

A Benchmarking Framework for Evaluating Large Language Model Capabilities in Nuclear Reactor Safety Applications

Large language models (LLMs) are increasingly capable of answering technical questions, synthesizing domain knowledge, and supporting engineering workflows. For nuclear science and engineering, these capabilities require careful, domain-specific evaluation before they can be credibly incorporated into safety-related activities, regulatory review, or technical decision support. This paper presents preliminary results from benchmarking framework for evaluating LLM capabilities in nuclear contexts. The framework is organized into three evaluation categories: nuclear fundamentals, general dual-use knowledge, and plant specific knowledge. These categories are intended to distinguish general nuclear engineering competence from broader technical reasoning and more context-dependent nuclear knowledge. Initial evaluations focus on nuclear fundamentals using questions representative of the knowledge expected of a nuclear professional engineer. Results indicate that contemporary frontier models perform at a high level and substantially exceed the performance of older model generations, with some models approaching saturation of the current benchmark. These findings suggest both the rapid improvement of LLM capabilities in specialized technical domains and the need for more discriminating evaluation methods. The paper presents the benchmark structure, preliminary model-comparison results, and ongoing work. This work supports development of verifiable, responsible, and safety-conscious methods for assessing AI systems in nuclear engineering applications.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Validating a Dynamic PWR Safety and Security Model?

Nuclear power plants (NPPs) are assessed for safety and security using separate models that cannot capture how an attacker's decisions and a plant's response unfold together in real time, leaving regulators and operators without a complete picture of true plant vulnerability. Traditional probabilistic risk assessment (PRA) methods treat adversarial events as fixed initiators with predetermined outcomes, and are structurally incapable of representing the time-dependent interplay between physical security events, safety system response, and operator mitigative actions. At Idaho National Laboratory (INL), I contributed to the development and validation of Modeling and Analysis for Safety and Security using the Dynamic EMRALD Framework (MASS-DEF). Where static PRA relies on event-tree logic that cannot evolve mid-scenario, MASS-DEF couples a time-dependent dynamic PRA tool EMRALD (Event Modeling Risk Assessment using Linked Diagrams) with attack simulation software, allowing attacker behavior, plant system states, and operator actions to interact across time. My work focused on validating a general Pressurized Water Reactor (PWR) model. I traced model logic against PWR plant to identified errors in logic and confirm accuracy. I then built and tested attack scenarios against a general PWR model to verify that the model produced expected outcomes across all logical pathways. I also contributed a section to a related technical paper applying the same EMRALD platform to radiation dose modeling. Results show that MASS-DEF can quantitatively demonstrate that many plants exceed their regulatory security thresholds. This demonstrated margin provides a technically defensible basis for reducing the number of guards without compromising regulatory compliance. Physical security costs represent roughly 10% of annual operating budgets, making such reductions directly meaningful to INL's mission of sustaining existing commercial NPPs. This internship strengthened my understanding of nuclear systems, probabilistic modeling, and technical writing, and has solidified my pursuit of a career at a national laboratory.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗

MHD, disruptions and control physics: Chapter 4 of the special issue: on the path to tokamak burning plasma operation

In this chapter, we review the progress in MHD stability, disruptions and control in magnetic fusion research that has occurred over the past (more than) one and a half decades since the publication by Hender et al in 2007 on the same topic as part of the update of ITER Physics Basis. During this period, remarkable progress has been achieved in the understanding of the basic physics and overall control of MHD instabilities through a wide spectrum of dedicated experiments, theory and modeling. The sawtooth activities are probably today one of the best understood of MHD events and very robust control schemes have been developed for reliable operation of tokamaks through core heating. Similarly, significant improvements have been achieved in understanding and control of neoclassical tearing modes, resistive wall modes or locked modes and their control through ECCD or error field control. The field of disruption prediction through application of artificial intelligence, machine learning or deep learning methods, which had already started at the time of the 2007 review, has progressed significantly due to general progress in these fields and application of newer, more sophisticated algorithms. However, although remarkable progress has been achieved in the field of Disruptions, their understanding, prediction, possible avoidance and mitigation still remain probably the most active fields of R&D globally in this field. This is especially because reactor grade machines like ITER and DEMO will be much less tolerant in respect of disruptions and runaway currents, and their occurrences must be either avoided altogether or minimized to an acceptable value without causing any significant hindrance to robust machine operations. This review is intended to present a broad spectrum of the R&D that has occurred in this field in support of ITER, which will also be of immense significance for all future machines, especially reactors like DEMO.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Demonstration of Microwave Resonant Cavity Transducer Performance in Fluid Flow Sensing: Development of Sensor Performance Model of Microwave Cavity Flow Meter for Advanced Reactor High Temperature Fluids

We are investigating a microwave cavity-based transducer for in-core high-temperature fluid flow sensing in molten salt cooled reactors (MSCR) and sodium fast reactors (SFR). This sensor is a hollow metallic cylindrical cavity. The principle of sensing consists of making one wall of the cylindrical cavity flexible enough so that dynamic pressure, which is proportional to fluid velocity, will cause membrane deflection. Membrane deflection causes cavity volume change, which leads to a shift in the resonant frequency. To validate sensor physics, we have performed proof-of-principle test of flow sensing in water. For this test, we have developed a cylindrical resonator for K-band, which was machined from brass. The cavity was excited through WR-42 waveguide through a subwavelength hole on the side of the wall of the cylinder. To increase the spectral signal visibility, we developed a signal processing method for baseline subtraction. A flow loop for proof-of-principle test of transducer performance in water was assembled. A commercial flow meter was installed in the loop for reference measurements. Cylindrical cavity was excited in the TEM 011 mode with resonant frequency f ≈ 17.8GHz. Frequency shift of cavity spectral response was obtained by gradually increasing water flow rate from 0 to 60gpm. Corresponding monotonic increase of resonant frequency shift by several MHz was observed.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Summary report on UO 2 thermal conductivity model refinement and assessment studies

Uranium dioxide (UO 2 ) is the most commonly used fuel in light water nuclear reactors and thermal conductivity controls the removal of heat produced by fission, therefore, governing fuel temperature during normal and accident conditions. The use of fuel performance codes by the industry to predict operational behavior is widespread. A primary source of uncertainty in these codes is thermal conductivity, and optimized fuel utilization may be possible if existing empirical models were replaced with models that incorporate explicit thermal conductivity degradation mechanisms during fuel burn-up. This approach is able to represent the degradation of thermal conductivity due to each individual defect type, rather than the overall burn-up measure typically used which is not an accurate representation of the chemical or microstructure state of the fuel that actually governs thermal conductivity and other properties. To generate a mechanistic thermal conductivity model, molecular dynamics (MD) simulations of UO 2 thermal conductivity including representative uranium and oxygen defects and fission products are carried out. These calculations employ a standard Buckingham type interatomic potential and a potential that combines the many-body embedded atom method potential with Morse-Buckingham pair potentials. Potential parameters for UO 2+x and ZrO 2 are developed for the latter potential. Physical insights from the resonant phonon-spin scattering mechanism due to spins on the magnetic uranium ions have been introduced into the treatment of the MD results, with the corresponding relaxation time derived from existing experimental data. High defect scattering is predicted for Xe atoms compared to that of La and Zr ions. Uranium defects reduce the thermal conductivity more than oxygen defects. For each defect and fission product, scattering parameters are derived for application in both a Callaway model and the corresponding high-temperature model typically used in fuel performance codes. The model is validated by comparison to low-temperature experimental measurements on single crystal hyper-stoichiometric UO 2+x samples and high-temperature literature data. Ongoing works include investigation of the effect of phase separation to UO 2 +U 4 O 9 on the low temperature thermal conductivity of UO 2+x , and modeling of thermal conductivity using the Green-Kubo method. Ultimately, this work will enable more accurate fuel performance simulations as well as extension to new fuel types and operating conditions, all of which improve the fuel economics of nuclear energy and maintain high fuel reliability and safety.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Novel Laser 3D Printing Method for the Advanced Manufacturing of Protonic Ceramics

Protonic ceramics (PCs) with high proton conductivity at intermediate temperatures (300–600 °C) have attracted many applications in energy conversion and storage devices such as PC fuel/electrolysis cells, PC membrane reactors, hydrogen pump, hydrogen or water-permeable membranes, and gas sensors. One of the essential steps for fulfilling the practical utilization of these intermediate-temperature PC energy devices is the successful development of advanced manufacturing methods for cost-effectively and rapidly fabricating them with high energy density and efficiency in a customized demand. In this work, we developed a new laser 3D printing (L3DP) technique by integrating digital microextrusion-based 3D printing and precise and rapid laser processing (sintering, drying, cutting, and polishing), which showed the capability of manufacturing PCs with desired complex geometries, crystal structures, and microstructures. The L3DP method allowed the fabrication of PC parts such as pellets, cylinders, cones, films, straight/lobed tubes with sealed endings, microchannel membranes, and half cells for assembling PC energy devices. The preliminary measurement of the L3DP electrolyte film showed a high proton conductivity of ≈7 × 10−3 S/cm. This L3DP technique not only demonstrated the potential to bring the PCs into practical use but also made it possible for the rapid direct digital manufacturing of ceramic-based devices.

08 HYDROGEN↗

2019 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is necessary to meet the continual challenging national workforce needs that arise as computational science and engineering problems continue to grow in scope and complexity. Computational science and engineering (CSE) is a multidisciplinary approach that uses scientific computing to solve practical problems methods and to supply technical tools across the scientific discovery spectrum. In particular, the DOE CSGF emphasizes high-performance computing (HPC) that enables CSE that advances science and engineering in directions important to the DOE and the economy in general. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines, such as biology and cosmology, have been transformed through the augmentation of scientific observation via HPC. At government laboratories and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, renewable energy, fusion-reactor design, additive manufacturing, nanomaterials for next-generation batteries and transistors, and turbine and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development — including continuing to rise to the challenge of pandemic-related research. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing.” An explosion in scientific and technological data has driven the need for increasingly sophisticated HPC to transform those data into scientific understanding. With access to more and more data and the proliferation of HPC, Machine Learning and Artificial Intelligence are experiencing a renaissance, complementing the now well-established use of computational simulation. Indeed, in its September 2020 subcommittee report on “AI/ML, Data Intensive Science and High-Performance Computing”, the DOE Advanced Scientific Computing Advisory Committee (ASCAC) explicitly called for a fellowship program to train computational and data scientists to tackle exascale and data-intensive computing challenges. This collaboration of empirical and theory-based modeling will increasingly inform federal policymakers whose decisions affect American society and future generations, and it requires highly skilled and intellectually agile computational scientists who can support the fast-moving DOE National Laboratory research environment. In fact, the DOE CSGF program has explicitly and consistently addressed this need.

97 MATHEMATICS AND COMPUTING↗

Structural-dimensional effects and their application in the 'core—nanoshell' systems synthesized by the molecular layering

In connection with the development of nanotechnology in the last 15—20 years, the method of molecular layering (ML), created in the middle of the last century in the USSR, has attracted increasing attention. The features of structural-dimensional effects in the products obtained by new chemical nanotechnology and promising directions of their practical application in 'core—nanoshell' compositions are considered in the review. In accordance with the synthetic capabilities of the ML method, the functional properties of the 'core—nanoshell' type materials are affected by the 'monolayer effect' and the substrate shielding effect, as well as the multicomponent nature of the system, and mutual structural coordination effect of the substrate and the build-up nanolayer. The review presents theoretical and experimental data on the application of the observed effects in the creation of shell pigments and fillers, modified sorbents, catalytic membrane reactors, nanodoped ceramic materials, polymers, quartz fibers with adjustable optical characteristics, electrets, etc.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗