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At least 343 records · Page 19

Towards libraries of different ultrasmall amorphous silica cage topologies

Cage topology controlled at the nanometer length scale is expected to enable original functionalities, e.g., in catalysis and therapeutics. Cages are fundamental structural motifs of clathrates and their topological duals, Frank-Kasper phases, and are constituents of mesoporous silica frameworks. However, with one exception, they have not been synthesized as discrete particles. By varying reactant ratios of surfactant, oil, and silane, we report the discovery of 5(12)6(2) and 5(12)6(8) amorphous silica polyhedra, each coexisting with the previously identified 5(12) cage, using combined cryo-transmission electron microscopy (cryo-TEM) and single-particle reconstruction (SPR). Notably, the 5(12)6(8) polyhedron represents a topology not previously observed in mesoporous silica frameworks. Control over structural features is demonstrated, and insights into cage formation mechanisms are provided. Structural outcomes are summarized in a ternary morphology diagram alongside prior results, bridging serendipitous discovery and intentional design of silica cages displaying a level of control over silica polymerization rivaling nature.

Jang, Dong June [Department of Materials Science a↗

Density functional modeling of the binding energies between aluminosilicate oligomers and different metal cations

Interactions between negatively charged aluminosilicate species and positively charged metal cations are critical to many important engineering processes and applications, including sustainable cements and aluminosilicate glasses. In an effort to probe these interactions, here we have calculated the pair-wise interaction energies (i.e., binding energies) between aluminosilicate dimer/trimer and 17 different metal cations M n+ (M n+ = Li + , Na + , K + , Cu + , Cu 2+ , Co 2+ , Zn 2+ , Ni 2+ , Mg 2+ , Ca 2+ , Ti 2+ , Fe 2+ , Fe 3+ , Co 3+ , Cr 3+ , Ti 4+ and Cr 6+ ) using a density functional theory (DFT) approach. Analysis of the DFT-optimized structural representations for the clusters (dimer/trimer + M n+ ) shows that their structural attributes (e.g., interatomic distances) are generally consistent with literature observations on aluminosilicate glasses. The DFT-derived binding energies are seen to vary considerably depending on the type of cations (i.e., charge and ionic radii) and aluminosilicate species (i.e., dimer or trimer). A survey of the literature reveals that the difference in the calculated binding energies between different M n+ can be used to explain many literature observations associated with the impact of metal cations on materials properties (e.g., glass corrosion, mineral dissolution, and ionic transport). Analysis of all the DFT-derived binding energies reveals that the correlation between these energy values and the ionic potential and field strength of the metal cations are well captured by 2nd order polynomial functions ( R 2 values of 0.99–1.00 are achieved for regressions). Given that the ionic potential and field strength of a given metal cation can be readily estimated using well-tabulated ionic radii available in the literature, these simple polynomial functions would enable rapid estimation of the binding energies of a much wider range of cations with the aluminosilicate dimer/trimer, providing guidance on the design and optimization of sustainable cements and aluminosilicate glasses and their associated applications. Finally, the limitations associated with using these simple model systems to model complex interactions are also discussed.

Gong, Kai↗

Networked Microgrid Energy Management Considering Ownership and Control Structures: A Comparison

With the growing deployment of microgrids, networked microgrids have emerged for their additional advantages of economy, reliability and resilience by coordinating the operation of multiple microgrids. As microgrids are operated with different ownership, objectives and functionalities, the formed networked microgrids show characteristics of mixed ownership, inconsistent objectives and various functionalities. To enable the coordinated operation of networked microgrids, three control structures, i.e., centralized, distributed and decentralized, have been constructed in the literature. However, the data sharing enabling these different paradigms and the resulted value propositions are not well defined, leading to poor resource management and resilience, etc. To solve this issue, a complete comparison of networked microgrid energy management under centralized, distributed and decentralized structures are performed. As a novel contribution, the required minimum data exchange of networked microgrid energy management under three control structures are identified, respectively. The value propositions are calculated and compared against each other by the results of case studies.

control structures↗

Constraining Genome-Scale Models to Represent the Bow Tie Structure of Metabolism for 13 C Metabolic Flux Analysis

Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13 C Metabolic Flux Analysis ( 13 C MFA) and Two-Scale 13 C Metabolic Flux Analysis (2S- 13 C MFA) are two techniques used to determine such fluxes. Both operate on the simplifying approximation that metabolic flux from peripheral metabolism into central “core” carbon metabolism is minimal, and can be omitted when modeling isotopic labeling in core metabolism. The validity of this “two-scale” or “bow tie” approximation is supported both by the ability to accurately model experimental isotopic labeling data, and by experimentally verified metabolic engineering predictions using these methods. However, the boundaries of core metabolism that satisfy this approximation can vary across species, and across cell culture conditions. Here, we present a set of algorithms that (1) systematically calculate flux bounds for any specified “core” of a genome-scale model so as to satisfy the bow tie approximation and (2) automatically identify an updated set of core reactions that can satisfy this approximation more efficiently. First, we leverage linear programming to simultaneously identify the lowest fluxes from peripheral metabolism into core metabolism compatible with the observed growth rate and extracellular metabolite exchange fluxes. Second, we use Simulated Annealing to identify an updated set of core reactions that allow for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13 C MFA or 2S- 13 C MFA, as well as provide for a substantially lower set of flux bounds for fluxes into the core as compared with previous methods. We provide an open source Python implementation of these algorithms at https://github.com/JBEI/limitfluxtocore.

13C metabolic flux analysis↗

Dynamical Scaling Reveals Topological Defects and Anomalous Evolution of a Photoinduced Phase Transition

Nonequilibrium states of quantum materials can exhibit exotic properties and enable unprecedented functionality and applications. These transient states are inherently inhomogeneous, characterized by the formation of topologically protected structures, requiring nanometer spatial resolution on femtosecond timescales to resolve their evolution. Using ultrafast total x-ray scattering at a free electron laser and a sophisticated scaling analysis, we gain unique access to the dynamics on the relevant mesoscopic lengthscales. Our results provide direct evidence that ultrafast excitation of LaTe$_3$ leads to formation of topological vortex strings of the charge density wave. These dislocations of the charge density wave exhibit anomalous, subdiffusive dynamics, slowing the equilibration process, providing rare insight into the nonequilibrium mesoscopic response in a quantum material. Our findings establish a general framework to investigate properties of topological defects, which are expected to be ubiquitous in nonequilibrium phase transitions and may arrest equilibration and enhance competing orders.

FOS: Physical sciences↗

Human Factors Design for Particle Accelerator Control Room Interfaces

Fermilab, the birthplace of many scientific discoveries in physics and particle accelerator sciences, is in the midst of a widescale modernization effort. The Accelerator Control Operations Research Network (ACORN project’s goal is to modernize the accelerator control system by replacing end-of-life power supplies and enhance future operations of the Fermilab accelerator complex with megawatt particle beams. Within ACORN, opportunities for process improvement concerning software development, human-system interface design, and task performance are also being considered. Human factors researchers from Idaho National Laboratory in collaboration with usability experts from Fermilab, are currently investigating human-centered design improvements for the accelerator control system. For example, substantial tribal knowledge and memory recall are required to effectively operate the accelerator system. This contributes to high cognitive workload and potential burnout of accelerator operators. Developing guidance for consistent visual and functional design enables a more intuitive interaction and relieves operators of cognitive burden. Additionally, developing more intuitive and integrated interfaces can also lead to improved accelerator efficacy by empowering operators with greater understanding and control of the systems. The challenge in developing such interfaces is in designing for a wide variety of user goals, system specifications, and level of experience in users. The challenges need to be met while e also considering the maintainability of the control system. The purpose of this paper is to detail the human factors process and design within the ACORN project, describe results gathered thus far, and discuss the larger implications for this work.

43 PARTICLE ACCELERATORS↗

Polarization rotation in a ferroelectric BaTiO$_3$ film through low-energy He-implantation

Domain engineering in ferroelectric thin films is crucial for next-generation microelectronic and photonic technologies. Here, a method is demonstrated to precisely control domain configurations in BaTiO$_3$ thin films through low-energy He ion implantation. The approach transforms a mixed ferroelectric domain state with significant in-plane polarization into a uniform out-of-plane tetragonal phase by selectively modifying the strain state in the film's top region. This structural transition significantly improves domain homogeneity and reduces polarization imprint, leading to symmetric ferroelectric switching characteristics. The demonstrated ability to manipulate ferroelectric domains post-growth enables tailored functional properties without compromising the coherently strained bottom interface. The method's compatibility with semiconductor processing and ability to selectively modify specific regions make it particularly promising for practical implementation in integrated devices. This work establishes a versatile approach for strain-mediated domain engineering that could be extended to a wide range of ferroelectric systems, providing new opportunities for memory, sensing, and photonic applications where precise control of polarization states is essential.

Luo, Liang [Ames Laboratory (AMES), Ames, IA (Unit↗

Inorganic resins for clinical use of 213 Bi generators

Applicant's invention is a radionuclide generator resin material for radiochemical separation of daughter radionuclides, particularly 213 Bi, from a solution of parental radionuclides, the resin material capable of providing clinical quantities of 213 Bi of at least 20-mCi, wherein the resin material comprises a silica-based structure having at least one bifunctional ligand covalently attached to the surface of the silica-based structure. The bifunctional ligand comprises a chemical group having desirable surface functionality to enable the covalent attachment of the bifunctional ligand thereon the surface of the structure and the bifunctional ligand further comprises a second chemical group capable of binding and holding the parental radionuclides on the resin material while allowing the daughter radionuclides to elute off the resin material. The bifunctional ligand has a carbon chain with a limited number of carbons to maintain radiation stability of the resin material.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Ultrafast optical pump-probe spectroscopy is used to reveal the coexistence of coupled antiferromagnetic (AFM)/ferroelectric (FE) and ferromagnetic (FM) orders in multiferroic TbMnO3 films, which can guide researchers in creating new kinds of multiferroic materials.

Multiferroic materials have attracted much interest in the past decade, due not only to their novel device applications, but also their manifestations of coupling and interactions between different order parameters (particularly electric polarization and magnetic order). Recently, much attention has been focused on perovskite manganites, RMnO{sub 3} (R = rare earth ions), due to the discovery of a large magnetoelectric effect in these materials. The first member of this family to be discovered was TbMnO{sub 3} (TMO), which is now well established as a typical magnetoelectric multiferroic. Extensive experimental and theoretical studies have already been done on single crystal TMO (SC-TMO). In brief, SC-TMO, with a distorted orthorhombic perovskite structure, has an antiferromagnetic (AFM) phase transition at T{sub N} {approx}40 K with sinusoidally ordered Mn moments. Below T{sub FE} {approx} 28 K, ferroelectric (FE) order develops owing to the appearance of cycloidal spiral spin structure. In contrast, there are relatively few reports describing the properties of TMO thin films (typically grown on SrTiO{sub 3} (STO) substrates). In general, thin films can enable new functionality in materials, as their physical parameters can be changed by modifying their structure via strain imposed by the substrate. Strain in particular has the potential to directly couple FE and FM orders, which is very rare. This could benefit electronic device applications by providing low power consumption, high speed operation, and greater electric/magnetic field controllability. Previous investigations of magnetic properties in TMO films revealed an unexpected ferromagnetic (FM) order, in contrast to SC-TMO. However, several important questions regarding these films are still unanswered for instance: (1) What mechanism induces FM order? (2) Can FM, sinusoidal AFM and spiral AFM (or FE) orders coexist? (3) Can FM order be coupled to FE order? To fully understand these unique materials, experimental techniques capable of dynamically unraveling the interplay between these degrees of freedom on an ultrafast timescale are needed. Here, we use ultrafast optical pump-probe spectroscopy to reveal coexisting coupled magnetic orders in epitaxial TMO thin films grown on (001)-STO, which were not observed in previous work. Our temperature (T)-dependent transient differential reflectivity ({Delta}R/R) measurements show clear signatures of sinusoidal AFM, spiral AFM (FE) and FM phases developing as the film thickness changes. We carry out first-principle density functional theory (DFT) calculations to explain the coupling between AFM/FE and FM orders. These results reveal that the coupling between different magnetic orders observed in our multiferroic TMO thin films may offer greater control of functionality as compared to bulk single crystal multiferroics.

36 MATERIALS SCIENCE↗

OpenADR Open Source Toolkit: Developing Open Source Software for the Smart Grid

Demand response (DR) is becoming an increasingly important part of power grid planning and operation. The advent of the Smart Grid, which mandates its use, further motivates selection and development of suitable software protocols to enable DR functionality. The OpenADR protocol has been developed and is being standardized to serve this goal. We believe that the development of a distributable, open source implementation of OpenADR will benefit this effort and motivate critical evaluation of its capabilities, by the wider community, for providing wide-scale DR services

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modular space vehicle boards, control software, reprogramming, and failure recovery

A space vehicle may have a modular board configuration that commonly uses some or all components and a common operating system for at least some of the boards. Each modular board may have its own dedicated processing, and processing loads may be distributed. The space vehicle may be reprogrammable, and may be launched without code that enables all functionality and/or components. Code errors may be detected and the space vehicle may be reset to a working code version to prevent system failure.

33 ADVANCED PROPULSION SYSTEMS↗

Modular space vehicle boards, control software, reprogramming, and failure recovery

A space vehicle may have a modular board configuration that commonly uses some or all components and a common operating system for at least some of the boards. Each modular board may have its own dedicated processing, and processing loads may be distributed. The space vehicle may be reprogrammable, and may be launched without code that enables all functionality and/or components. Code errors may be detected and the space vehicle may be reset to a working code version to prevent system failure.

97 MATHEMATICS AND COMPUTING↗

FLISR in the Presence of DERs ADMS Test Bed Use Case

Fault location, isolation, and restoration (FLISR) is one of the distribution automation applications that utilities are most interested in. It operates groups of switches on distribution feeders to improve the reliability of power delivery after localizing outages. FLISR is an essential function for enabling a self-healing grid, and it directly affects grid reliability and resilience. The presence of DERs brings both new opportunities and challenges for FLISR applications. For instance, some DERs can work as backup generation sources and help energize local networks so more switching options can be achieved with the coordination of FLISR operations; however, the existence of DERs also brings new challenges. The bidirectional power flow resulting from DERs might require dynamic changes to protective devices' fault current settings, and thus the FLISR application will need to dynamically adjust its operations in coordination with the dynamic protection settings. Also, some FLISR applications make their service restoration decisions and close tie-switches based on predefined rules; however, the presence of DERs and their impact on altering net loads on the local feeder network are not considered. For this use case, the project team is using the FLISR application of the Survalent ADMS operating on a real-time simulation of a feeder from Central Georgia EMC, a cooperative electric utility. The performance of the FLISR application is being evaluated for different locations and combinations of DERs, including grid-forming battery energy storage systems.

ADMS↗

Search for High-Pressure Silicon Phases: Reaching the Extreme Conditions with High-Intensity Laser Irradiation

Controlling electronic and optical properties of semiconducting materials could substantially expand their functionality and enable new pathways for the formation of ‘smart’ materials for emerging innovative applications. An emerging new path for the synthesis of exotic silicon (Si) polymorphs is irradiation of bulk diamond-cubic Si by ultrashort laser pulses at relativistic intensity above 1019 W/cm2. Exotic polymorphs are formed due to interaction with MeV-energy electrons generated in laser-produced high-temperature plasma state. The unusual Si structures are found in the form of 5–10 nm nanoparticles confined deep in the bulk of 500-μm-thick Si samples. Raman spectroscopy, electron microscopy and X-ray diffraction studies provide an unequivocal evidence of exotic Si phase formation. A key advantage of such relativistic irradiation lies thereby in the fact that large quantities of such exotic Si is synthesised embedded within the bulk diamond-cubic Si and that further the formed Si polymorphs are stable at ambient temperature and pressure. They are thus available for further studies for electronic applications in selective band gap engineering.

Rapp, Ludovic↗

Chapter 14: Surface plasmon resonance enhanced artificial photosynthesis of chemical fuels for energy storage

Nanostructured noble metals such as Au, Ag, and Cu have interesting optical properties because of the oscillation motions of their surface electrons upon strong coupling with light under resonance conditions. This resonant oscillation motion of conduction electrons refers to surface plasmon resonance (SPR) and localized SPR (LSPR) when localized near the surface of a nanoparticle. The extinction spectrum of a solution of plasmonic nanoparticles has tunable wavelength responses from UV to NIR due to strong light scattering and absorption which are highly sensitive to the permittivity of the nanoparticles, their sizes and shapes, and chemical environment. Strong light scattering due to the LSPR of plasmonic nanoparticles creates a strong localized and far-field intensity capable of enhancing light absorption characteristics of a chromophore near a plasmonic surface. Engineering the chromophores’ radiative decay dynamics can be done by 1) increasing its radiative decay rate to increase its photoluminescence intensity and 2) increasing its nonradiative decay rates associated to direct charge transfer to the metal surface. Such interesting photophysical properties of a chromophore can be extended to other light-absorbing materials such as semiconductor thin films and nanostructures. This plasmonic effect on the photophysics of a light-absorbing material can be theoretically and experimentally validated. The phenomenon has also been applied to advanced optoelectronic devices such as organic light-emitting diodes (OLED)1 and organic photovoltaics (OPV).2-4 The local field created by the SPR can provide an intense EM field to enhance photoluminescence emission of an organic chromophore5-8 and Raman scattering of an organic molecule, and single-molecule Raman9-10 can be detected on specially designed LSPR substrate. (Figure 1 on SPR for energy) Recent studies suggest that LSPR can be incorporated in light-harvesting and conversion systems to increase energy conversion in a solar cell and photoelectrochemical cell and chemical transformations of CO2 to chemical fuels.11-12 Plasmonic active metals naturally exhibit catalytic activities for electrochemical fuel conversion that can be enhanced by engineering their structures to form unique catalytic structures such as symmetry-broken Au-Cu Janus nanocrystals.13 These studies are critical to addressing the global challenges of energy14-15 and CO2 emission from nonrenewable sources such as coal, petroleum, and natural gas.16-17 Electrochemical systems comprised of unique photonic structures and functions that enable efficient and affordable energy harvesting/conversion/storage are highly desired for providing safe and environment-friendly energy sources. This chapter reviews our recent work of LSPR enabled photoelectrochemical water splitting and recent advances in LSPR-enabled CO2 reduction and photochemical reactions reported in the literature. Scientific and technical challenges of applying LSPR to enhance these energy conversion and storage systems are discussed at the conclusion of this chapter.

Pan, Shanlin↗

Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks

There has been much recent interest in designing symmetry-aware neural networks (NNs) exhibiting relaxed equivariance. Such NNs aim to interpolate between being exactly equivariant and being fully flexible, affording consistent performance benefits. In a separate line of work, certain structured parameter matrices -- those with displacement structure, characterized by low displacement rank (LDR) -- have been used to design small-footprint NNs. Displacement structure enables fast function and gradient evaluation, but permits accurate approximations via compression primarily to classical convolutional neural networks (CNNs). In this work, we propose a general framework -- based on a novel construction of symmetry-based structured matrices -- to build approximately equivariant NNs with significantly reduced parameter counts. Our framework integrates the two aforementioned lines of work via the use of so-called Group Matrices (GMs), a forgotten precursor to the modern notion of regular representations of finite groups. GMs allow the design of structured matrices -- resembling LDR matrices -- which generalize the linear operations of a classical CNN from cyclic groups to general finite groups and their homogeneous spaces. We show that GMs can be employed to extend all the elementary operations of CNNs to general discrete groups. Further, the theory of structured matrices based on GMs provides a generalization of LDR theory focussed on matrices with cyclic structure, providing a tool for implementing approximate equivariance for discrete groups. We test GM-based architectures on a variety of tasks in the presence of relaxed symmetry. We report that our framework consistently performs competitively compared to approximately equivariant NNs, and other structured matrix-based compression frameworks, sometimes with a one or two orders of magnitude lower parameter count.

Samudre, Ashwin↗

RADIOISOTOPE IDENTIFICATION OF SHIELDED AND MASKED SNM RDD MATERIALS

Sonar and speech techniques have been investigated to improve functionality and enable handheld and other man-portable, mobile, and portal systems to positively detect and identify illicit nuclear materials, with minimal data and with minimal false positives and false negatives. RadSonar isotope detection and identification is an algorithm development project funded by NA-22 and employing the resources of Savannah River National Laboratory and three University Laboratories (JHU-APL, UT-ARL, and UW-APL). Algorithms have been developed that improve the probability of detection and decrease the number of false positives and negatives. Two algorithms have been developed and tested. The first algorithm uses support vector machine (SVM) classifiers to determine the most prevalent nuclide(s) in a spectrum. It then uses a constrained weighted least squares fit to estimate and remove the contribution of these nuclide(s) to the spectrum, iterating classification and fitting until there is nothing of significance left. If any Special Nuclear Materials (SNMs) were detected in this process, a second tier of more stringent classifiers are used to make the final SNM alert decision. The second algorithm is looking at identifying existing feature sets that would be relevant in the radioisotope identification context. The underlying philosophy here is to identify parallels between the physics and/or the structures present in the data for the two applications (speech analysis and gamma spectroscopy). The expectation is that similar approaches may work in both cases. The mel-frequency cepstral representation of spectra is widely used in speech, particularly for two reasons: approximation of the response of the human ear, and simplicity of channel effect separation (in this context, a 'channel' is a method of signal transport that affects the signal, examples being vocal tract shape, room echoes, and microphone response). Measured and simulated gamma-ray spectra from a hand-held Radioisotope Identification Device were used to evaluate the algorithms. This paper will present and discuss results of the Test and Evaluation performed on two algorithms produced from the project.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Electronic spectra from TDDFT and machine learning in chemical space

Due to its favorable computational efficiency, time-dependent (TD) density functional theory (DFT) enables the prediction of electronic spectra in a high-throughput manner across chemical space. Its predictions, however, can be quite inaccurate. We resolve this issue with machine learning models trained on deviations of reference second-order approximate coupled-cluster (CC2) singles and doubles spectra from TDDFT counterparts, or even from DFT gap. We applied this approach to low-lying singlet-singlet vertical electronic spectra of over 20 000 synthetically feasible small organic molecules with up to eight CONF atoms. The prediction errors decay monotonously as a function of training set size. For a training set of 10 000 molecules, CC2 excitation energies can be reproduced to within ±0.1 eV for the remaining molecules. Analysis of our spectral database via chromophore counting suggests that even higher accuracies can be achieved. Based on the evidence collected, we discuss open challenges associated with data-driven modeling of high-lying spectra and transition intensities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗