Unravelling the Influence of Surface Modification on the Ultimate Performance of Carbon Fiber/Epoxy Composites
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This report documents work completed in FY21 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program’s Molten Salt Reactor (MSR) Application Drivers activity at Argonne. The common focus was on identifying the modeling and simulation functional requirements for designing, licensing, and operating MSRs and applying those capabilities already developed in NEAMS tools to example problems of interest. The four main parts of this report each focuses on a specific area of simulation physics as it relates to MSR phenomena: fuel evolution, chemistry, computational fluid dynamics (CFD), and systems analysis. In terms of fuel evolution, which includes depletion, decay, on-line separations, and transmutation, the current state of computational capabilities for modeling this behavior in liquid-fueled molten salt reactor is discussed. Some of the functional requirements to accomplish the various applications of MSR fuel depletion modeling are highlighted, followed by a summary of recent approaches and code development activities. The chemistry functional requirements were discussed in the context of several applications of high importance for MSRs, such as corrosion, salt chemistry, and species transport. Each of these types of chemistry modeling have considerable impact on various aspects of reactor applications, including informing on reactor designs, improving operational efficiencies, analyzing safety and reactivity concerns, and estimating the mechanistic source term of the reactor. A brief overview is also provided on code development activities ongoing under NEAMS relevant to chemistry modeling of MSRs. In terms of CFD applications, the state-of-the-art spectral element code, Nek5000 was used to model the fluid dynamics within a full core of the Molten Salt Fast Reactor (MSFR) concept designed as part of the Euratom EVOL project. This concept was selected as the challenge problem because of its similar features to several U.S. industry concepts. The goal was to model some of the fast MSR design challenges, including potential large internal re-circulations, the need of accurate tracking of delayed neutron precursors (DNP), and the lack of relevant thermal-hydraulics models/correlations, etc. Therefore, a series of CFD models were created for the MSFR core cavity using a k – τ model two-equation model for the turbulence. These first full core results demonstrated that any potential recirculation zones could be properly identified with the current NEAMS CFD capabilities. The development of these models will also set the stage for future testing of Nek5000’s functionalities to model other MSR thermal-fluid phenomena. Lastly, the validation of SAM against experimental data from the Molten Salt Reactor Experiment, which started in FY19, continues with the inclusion of modeling the reactivity insertion tests. This involved using SAM and its point kinetics model for flowing fuel salt to recreate the time dependent power changes and response after positive reactivity insertions at the 1, 5, and 8 MWt power levels. Through these exercises, several code modifications were suggested to the SAM development team and accommodated to enable closer agreement with solid technical and physical justifications. These include adding a moderator reactivity feedback coefficient as an available input and modifying the solution approach for the point kinetics model. Additional SAM development suggestions for flowing fuel MSRs include adding the capability to allow the moderator power change proportionally with the reactor power and enabling specification of the power and DNP distributions separately.
Solar photovoltaic (PV) technology is being deployed at an unprecedented rate. However, utility-scale solar energy development is land intensive and its large-scale installation can have negative impacts on the environment. In particular, solar energy infrastructure can require extensive landscape modification that transforms soil ecological functions, thereby impacting hydrologic, vegetative, and carbon dynamics. However, reintroducing native vegetation to solar PV sites may be a means of restoring their soils. To this end, we investigated critical soil physical and chemical parameters at a revegetated photovoltaic array and an adjacent reference grassland in Colorado, United States. Seven years after revegetation, we found that carbon and nitrogen remained lower in the PV soil than in the reference soil and contained a greater fraction of coarse particles. We also found that the PV modules introduced heterogeneity in the soil moisture distribution, with precipitation accumulating along the lower edges of panels. The redistribution of soil moisture by panel arrays could potentially be used in concert with planting strategies to maximize plant growth or minimize soil erosion, and should be considered when evaluating the potential to co-locate vegetation with solar infrastructure.
Doped ceria electrolytes are the state of the art low‐temperature solid oxide electrolytes because of their high ionic conductivity and good material compatibility. However, cerium tends to reduce once exposed to reducing environments, leading to an increase in electronic conduction and a decrease in efficiency. Here, the leakage current is mitigated in ceria‐based electrolytes by controlling the defect chemistry through an engineered cathode side microstructure. This functional layer effectively addresses the problematic electronic conduction issue in ceria‐based electrolytes without adding significant ohmic resistance and increases the ionic transference number to over 0.93 in a thin 20 µm ceria‐based electrolyte at 500 °C, compared to a of 0.8 for an unmodified one. Based on this design, solid oxide fuel cells (SOFCs) are further demonstrated with the remarkable peak power density of 550 mW at 500 °C and excellent stability for over 2000 h. This approach enables a potential breakthrough in the development of ceria‐based low‐temperature solid oxide electrolytes.
Enzymes have in vivo life spans. Analysis of life spans, i.e., lifetime totals of catalytic turnovers, suggests that nonsurvivable collateral chemical damage from the very reactions that enzymes catalyze is a common but underdiagnosed cause of enzyme death. Analysis also implies that many enzymes are moderately deficient in that their active-site regions are not naturally as hardened against such collateral damage as they could be, leaving room for improvement by rational design or directed evolution. Enzyme life span might also be improved by engineering systems that repair otherwise fatal active-site damage, of which a handful are known and more are inferred to exist. Unfortunately, the data needed to design and execute such improvements are lacking: there are too few measurements of in vivo life span, and existing information about the extent, nature, and mechanisms of active-site damage and repair during normal enzyme operation is too scarce, anecdotal, and speculative to act on. Fortunately, advances in proteomics, metabolomics, cheminformatics, comparative genomics, and structural biochemistry now empower a systematic, data-driven approach for identifying, predicting, and validating instances of active-site damage and its repair. These capabilities would be practically useful in enzyme redesign and improvement of in-use stability and could change our thinking about which enzymes die young in vivo, and why.
Process intensification is a design philosophy aimed at making chemical processes safer and more efficient. Its implementation often results in significant modifications to the design and structure of the process, with several conventional unit operations occurring in the same physical device. Traditionally, process intensification has focused on steady-state operation. In our previous works, we introduced dynamic process intensification (DPI) as a new intensification paradigm based on operational changes for conventional or intensified units. DPI is predicated on switching operation between two auxiliary steady states selected via a steady-state optimization calculation that ensures that the system generates, on average and over time, the same products as in nominal steady-state operation, but with favorable economics. This paper extends the DPI concept and introduces a novel dynamic optimization-based DPI strategy (Do-DPI) that involves imposing a true cyclic operation rather than switching between two discrete states. We discuss its implementation using surrogate dynamic models learned via system identification. Here, an extensive case study concerning a ternary distillation column separating a canonical hydrocarbon mixture shows that Do-DPI can reduce energy use by more than 4% relative to steady-state operation, with no significant deviations in product quality and production rate.
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In these proceedings we report a recent calculation of the jet charge modification in heavy-ion relative to proton collisions at the LHC. Jets have played an essential role in constraining theories of in-medium parton shower evolution and in determining the properties of the quark-gluon plasma created in ultra-relativistic nuclear reactions. It is important to extend these studies to flavor-tagged jets and explore observables that are sensitive to their partonic origin. The average jet charge, introduced early on in the history of quantum chromodynamics, is a proxy for the electric charge of the quark or gluon that initiates the jet. In the framework of soft-collinear effective theory, we show how to evaluate the jet charge in a dense strongly-interacting matter environments. We identify observables that can isolate the contribution of in-medium branching from isospin effects and present predictions for the transverse momentum dependence of the jet charge distribution in nucleus-nucleus collisions and its modification relative to the proton case.
We discuss neutrino magnetic moments as a way of constraining physics beyond the Standard Model. In fact, new physics at the TeV scale can easily generate observable neutrino magnetic moments, and there exists a multitude of ways of probing them. We highlight in particular direct dark matter detection experiments (which are sensitive to neutrino magnetic moments because of the predicted modifications to the solar neutrino scattering rate), stellar cooling, and cosmological constraints.
Organic electrochemical transistors (OECTs) feature a polymer channel capable of conducting both ions and electronic charges. The choice of the channel material is critical for OECT performance. Many efforts have focused on improving performance via the chemical tunability of conjugated polymers – through backbone, side chain, and molar mass engineering – leading to useful design principles for accumulation-mode OECT materials. However, tuning the chemical structure of conjugated polymers often requires time-consuming optimization of the synthesis route. Meanwhile, variations in molar mass, dispersity, structural defects, and metal content present challenges when attempting to analyze the detailed effects of structural modifications, as multiple performance-determining factors are often (unintentionally) changed at the same time. Therefore, this study explores blended channel materials obtained by physically mixing glycolated and alkoxylated polymers in different ratios, and compares their OECT performance with the corresponding statistical copolymers. It is shown that mixing two well-performing materials creates blends that enable rational tuning of the transistor properties without compromising on performance. Thus, channels based on blends of alkoxylated and glycolated polymers hold promise for OECT technology with tailored response, as only two materials are needed to achieve any desired side chain ratio, simplifying the optimization of OECT characteristics.
Here we find that it is possible to increase sensitivity to low energy physics in a third or fourth Deep Underground Neutrino Experiment (DUNE)-like module with careful controls over radiopurity and targeted modifications to a detector similar to the DUNE Far Detector design. In particular, sensitivity to supernova and solar neutrinos can be enhanced with improved MeV-scale reach. A neutrinoless double beta decay search with 136 Xe loading appears feasible. Furthermore, sensitivity to Weakly-Interacting Massive Particle (WIMP) Dark Matter becomes competitive with the planned world program in such a detector, offering a unique seasonal variation detection that is characteristic of the nature of WIMPs.
A convenient enzymatic strategy is reported for the modification of cell surfaces. Using a tyrosinase enzyme isolated from Agaricus bisporus, unique tyrosine residues introduced at the C-termini of nanobodies can be site-selectively oxidized to reactive o-quinones. These reactive intermediates undergo rapid modification with nucleophilic thiol, amine, and imidazole residues present on cell surfaces, producing novel nanobody–cell conjugates that display targeted antigen binding. We extend this approach toward the synthesis of nanobody–NK cell conjugates for targeted immunotherapy applications. The resulting NK cell conjugates exhibit targeted cell binding and elicit targeted cell death.
Both the dispersion state of nanoparticles (NPs) within polymer nanocomposites (PNCs) and the dynamical state of the polymer altered by the presence of the NP/polymer interfaces have a strong impact on the macroscopic properties of PNCs. In particular, mechanical properties are strongly affected by percolation of hard phases, which may be NP networks, dynamically modified polymer regions, or combinations of both. In this article, the impact on dispersion and dynamics of surface modification of the NPs by short monomethoxysilanes with eight carbons in the alkyl part (C 8 ) is studied. As a function of grafting density and particle content, polymer dynamics is followed by broadband dielectric spectroscopy and analyzed by an interfacial layer model, whereas the particle dispersion is investigated by small-angle X-ray scattering and analyzed by reverse Monte Carlo simulations. NP dispersions are found to be destabilized only at the highest grafting. The interfacial layer formalism allows the clear identification of the volume fraction of interfacial polymer, with its characteristic time. The strongest dynamical slow-down in the polymer is found for unmodified NPs, while grafting weakens this effect progressively. The combination of all three techniques enables a unique measurement of the true thickness of the interfacial layer, which is ca. 5 nm. Finally, the comparison between longer (C 18 ) and shorter (C 8 ) grafts provides unprecedented insight into the efficacy and tunability of surface modification. It is shown that C 8 -grafting allows for a more progressive tuning, which goes beyond a pure mass effect.
While evasion attacks on computer vision systems have been widely studied, creating attacks that remain effective under significant changes in viewpoint continues to be challenging. Traditional approaches often rely on affine transformations of images, but these approaches degrade at larger perspective shifts and often produce unrealistic or ineffective perturbations. Recent methods use differentiable renderers to improve viewpoint robustness, but they typically depend on manually constructed 3D models. We introduce a semi-automated pipeline that generates physically printable and perspective-invariant adversarial patches using only a small set of 2D images. Our method integrates 3D reconstruction, neural rendering, adversarial patch optimization, and an object detection victim model into a unified workflow. We use 2D Gaussian Splatting for high fidelity mesh reconstruction and FlexPara for surface parameterization that produces texture maps suitable for patch editing. Together, these components form a fully differentiable pipeline in PyTorch3D that links texture modification to model outputs, enabling efficient optimization of patches that remain effective across many viewpoints. The complete process, from image capture to patch printing and physical evaluation, can be completed within a few hours. We demonstrate the effectiveness of the resulting patches through attacks on the YOLOv8 object detection model and discuss remaining challenges and opportunities for improving robustness and scalability.
The Crossroads supercomputer was designed to simulate some of the most complex physical devices in the world. These simulations routinely require 1/2 petabyte or more of system memory running on thousands of compute nodes for months at a time on the most powerful supercomputers. Improvements in time to solutions for these workloads can have major impact on our mission capabilities. In this paper we present early results of representative application workloads on 4th Gen Intel Xeon and Intel Xeon Processors codenamed Sapphire Rapids with HBM. These results demonstrate an extremely promising 8.57x improvement (node to node) over our prior generation Intel Broadwell (BDW) based HPC systems. No code modifications were required to achieve this speedup, providing a compelling path forward toward major reductions in time to solution and the complexity of physical systems that can be simulated in the future.
In this work, we have investigated the thermal annealing effect on the physical properties of an AlB 2 -type ternary intermetallic compound, Tb 2 Ni 0.90 Si 2.94 , that undergoes spin freezing behaviour coexisting with spatially limited antiferromagnetic phase below 9.9 K in as-cast form. Thermal annealing effect is found to result in considerable changes in the magnetic ground state properties of the system. Though only one magnetic transition around 9.9 K is observed for as-cast compound, the annealed sample exhibits two distinct magnetic transitions; one around T N ~ 13.5 K and another around T f ~ 4 K. The magnetization measurements and zero field neutron diffraction study reveal that the high temperature transition is antiferromagnetic type, though of limited correlation length, while the low temperature transition corresponds to spin freezing behaviour. The ac susceptibility and heat capacity studies also confirm the existence of frustrated cluster glass state at lower temperature than the antiferromagnetic ordering temperature. Additionally, ac susceptibility data exhibits signature of an additional peak in the even lower temperature region (at 2.2 K for zero frequency) that tends to shift in opposite direction with frequency in contrast to that observed for conventional glassy transitions. The change in intrinsic local structural disorder of Ni and Si ions associated with annealing has been argued to be responsible for the different magnetic behaviour in as-cast and annealed samples.
This perspective considers the enormous promise of epitaxial functional transition metal oxide thin films for future applications in low power electronic and energy applications since they offer wide-ranging and highly tunable functionalities and multifunctionalities, unrivaled among other classes of materials. It also considers the great challenges that must be overcome for transition metal oxide thin films to meet what is needed in the application domain. These challenges arise from the presence of intrinsic defects and strain effects, which lead to extrinsic defects. Current conventional thin film deposition routes often cannot deliver the required perfection and performance. Since there is a strong link between the physical properties, defects and strain, routes to achieving more perfect materials need to be studied. Several emerging methods and modifications of current methods are presented and discussed. The reasons these methods better address the perfection challenge are considered and evaluated.
This is the final technical report for DOE Award DE-SC0005132 entitled “Discovery of Dielectric Response and Forces in Sub-Nanoscale Objects.” This award originated on August 15, 2010 with Principle Investigator Prof. Phil Batson of Rutgers, The State University of New Jersey. Prof. Batson transitioned to Professor Emeritus status on January 31, 2023. At that time PI status was transferred to Prof. Robert Bartynski of the Department of Physics and Astronomy at Rutgers, The State University of New Jersey, and Director of the Rutgers Laboratory for Surface Modification. The central theme of the research performed under this award is develop and refine a NION aberration-corrected Scanning Transmission Electron Microscope to attain atomic spatial resolution and sub 10meV energy resolution in electron energy loss spectroscopy (EELS) performed on the transmitted electron beam. These capabilities allow examination of the excitation properties (primarily plasmonic and vibrational [ie., phonons] of nanoscale objects when excited with a highly-localized (~ Angstrom-scale) high energy (~ 60 keV) electron beam. Direct excitations (i.e., the response to electrons impinging directly on the sample) as well as excitations in response to the dynamic electric (and magnetic!) fields of an aloof electron beam (i.e., a beam that is close to but displaced from the target) have been studied. Our experimental work has benefited greatly from close collaborations with theoretical colleagues, but at Rutgers and from around the world, providing a much more complete understanding of the observed phenomena and suggesting avenues for further study and practical applications. This report summarizes the technical and scientific achievements accomplished during the entire award period. More extensive details are available in the Progress Reports that have already been filed with the Department of Energy. The report is divided into six sections. The first four sections focus on exploring, developing and understanding several unique capabilities and phenomena discovered and accessible owing to the high spatial- and energy-resolution we have been able to achieve. The latter two sections focus on applications of the STEM’s novel capabilities to study atomic- and nanometer-scale properties of solids, as well as broader applications to advanced and bio-materials.