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At least 541 records · Page 30

Alkali metal – yttrium borohydrides: The link between coordination of small and large rare-earth

The system Li–A–Y–BH{sub 4} (A=K, Rb, Cs) is found to contain five new compounds and four further ones known from previous work on the homoleptic borohydrides. Crystal structures have been solved and refined from synchrotron X-ray powder diffraction, thermal stability of new compounds have been investigated and ionic conductivity measured for selected samples. Significant coordination flexibility for Y{sup 3+} is revealed, which allows the formation of both octahedral frameworks and tetrahedral complex anions with the tetrahydroborate anion BH{sub 4} both as a linker and terminal ligand. Bi- and trimetallic cubic double-perovskites c-A{sub 3}Y(BH{sub 4}){sub 6} or c-A{sub 2}LiY(BH{sub 4}){sub 6} (A=Rb, Cs) form in all the investigated systems, with the exception of the Li–K–Y system. The compounds with the stoichiometry AY(BH{sub 4}){sub 4} crystallize in all investigated systems with a great variety of structure types which find their analog amongst metal oxides. In-situ formation of a new borohydride – closo-borane is observed during decomposition of all double perovskites. - Graphical abstract: The system Li–A–Y–BH{sub 4} (A=K, Rb, Cs) is found to contain five novel compounds and four further ones previously reported. Significant coordination flexibility of Y{sup 3+} is revealed, which can be employed to form both octahedral frameworks and tetrahedral complex anions, very different structural topologies. Versatility is also manifested in three different simultaneously occurring coordination modes of borohydrides for one metal cation, as proposed by DFT optimization of the monoclinic KY(BH{sub 4}){sub 4} structural model observed by powder diffraction. - Highlights: • The system Li-A-Y-BH{sub 4} (A=K, Rb, Cs) contains nine compounds in total. • Y{sup 3+} forms octahedral frameworks and tetrahedral complex anions. • Bi- and trimetallic double-perovskites crystallize in most systems. • Various AY(BH{sub 4}){sub 4} crystallize with structure types analogous to metal oxides. • Double-perovskites decompose and form a novel borohydride-closo-borane.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simple coating synthesis and enhanced luminescence behaviour of LiLa(MoO4)2:Eu3+@NaF

Highlights: • LiLa(MoO{sub 4}){sub 2}:Eu{sup 3+}{sub 0.06} @ (NaF){sub y wt} were synthesized with a simple coating method. • PL intensity can be enhanced as high as 4.80 times by coating NaF. • Enhancement PL intensity is a major effect, and increasing R is a minor effect. • LiLa(MoO{sub 4}){sub 2}:Eu{sup 3+}{sub 0.06} @ (NaF){sub 0.025 wt} was a phosphor with high R values (R = 5.89). - Abstract: A series of LiLa(MoO{sub 4}){sub 2}:Eu{sup 3+}@ (NaF){sub y wt} were prepared with a simple coating method. XRD results confirm that NaF coating will cause the slight expand of the lattice volume for the sample. Strongly enhanced emission effect inducing by NaF coating is observed. The emission spectra (PL) intensity of the optimal sample, LiLa(MoO{sub 4}){sub 2}:Eu{sup 3+}{sub 0.06} @ (NaF){sub 0.025wt} is as high as 4.8 times of that of LiLa(MoO{sub 4}){sub 2}:Eu{sup 3+}{sub 0.06}. Furthermore, dual emission properties inducing by NaF coating are observed. Enhancement emission of Eu{sup 3+} is a major effect, and increasing R is a minor effect. The optimal coating content of NaF is 2.5 wt%, which the corresponding chromaticity coordinates excited at 465 nm is x = 0.6650, y = 0.3347, which is nearly as same as the NTSC (National Television Standard Committee) standard values for red (x = 0.67, y = 0.33). So, it is a potential red-emitting phosphor with high R values (R = 5.89) for blue light-based white LED.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

X-ray Crystal Structure of Thorium Tetrahydroborate, Th(BH 4 ) 4 , and Computational Studies of An(BH 4 ) 4 (An = Th, U)

Here the crystal structure of Th(BH 4 ) 4 is described. Two of the four BH 4 – ions are terminal and tridentate (κ 3 ), whereas the other two bridge between neighboring Th IV centers in a κ 2 ,κ 2 (i.e., bis-bidentate) fashion. Thus, each thorium center is bound to six BH 4 – groups by 14 Th–H bonds. The six boron atoms describe a distorted octahedron in which the κ 3 -BH 4 – ions are mutually cis; the 14 ligating hydrogen atoms define a highly distorted bicapped hexagonal antiprism. The thorium centers are linked into a polymer consisting of interconnected helical chains wound about 4-fold screw axes. The structures of An(BH 4 ) 4 (An = Th, U) were also investigated by DFT. The geometries of [An(BH 4 ) 6 ] 2– , [An3(BH 4 ) 16 ] 4– , and [An 5 (BH 4 ) 26 ] 6– fragments of the polymeric structures were optimized at the B3LYP and/or PBE levels. Most calculated geometries are 14-coordinate and agree with the experimental structures, but isolated [Th(BH 4 ) 6 ] 2– units are predicted to feature 16-coordinate Th IV centers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Trisodium citrate, Na 3 (C 6 H 5 O 7 )

The crystal structure of anhydrous trisodium citrate, Na 3 (C 6 H 5 O 7 ), has been solved and refined using synchrotron X-ray powder diffraction data, and optimized using density functional theory (DFT). There are two independent five-coordinate Na + and one six-coordinate Na + cations in the asymmetric unit. The [NaO 5 ] and [NaO 6 ] polyhedra share edges and corners to form a three-dimensional framework. There are channels parallel to the a and b axes in which the remainder of the citrate anions reside. The only hydrogen bonds are an intramolecular one between the hydroxy group and one of the terminal carboxylate O atoms and an intermolecular one between a methylene group and the hydroxyl O atom.

Rammohan, Alagappa↗

Assembly of a Mechanical Model of MQXFB, the 7.2-m-Long Low-$\beta$ Quadrupole for the High-Luminosity LHC Upgrade

The ${\rm Nb_{3}Sn}$low-$\beta$quadrupole MQXF is being developed as a part of the High-Luminosity large hadron collider (LHC) upgrade project. The magnet will be produced in two different configurations, sharing the same cross section but with different lengths. A 7.2-m mechanical model of MQXFB was recently assembled at european organization for nuclear research (CERN) with one copper coil, two low-grade coils, and one rejected coil. Coil dimensions were measured with a portable coordinate measurement machine. The coil pack shimming was designed in order to optimize the field quality and the contacts between the coils and the collars. The azimuthal preload target was defined using the short models experience. The mechanical behavior during loading was monitored by means of strain gauges. The results demonstrated that the structure can provide the required prestress to the coils.

43 PARTICLE ACCELERATORS↗

SU-E-J-134: An Augmented-Reality Optical Imaging System for Accurate Breast Positioning During Radiotherapy

Purpose: Breast radiotherapy, particularly electronic compensation, may involve large dose gradients and difficult patient positioning problems. We have developed a simple self-calibrating augmented-reality system, which assists in accurately and reproducibly positioning the patient, by displaying her live image from a single camera superimposed on the correct perspective projection of her 3D CT data. Our method requires only a standard digital camera capable of live-view mode, installed in the treatment suite at an approximately-known orientation and position (rotation R; translation T). Methods: A 10-sphere calibration jig was constructed and CT imaged to provide a 3D model. The (R,T) relating the camera to the CT coordinate system were determined by acquiring a photograph of the jig and optimizing an objective function, which compares the true image points to points calculated with a given candidate R and T geometry. Using this geometric information, 3D CT patient data, viewed from the camera's perspective, is plotted using a Matlab routine. This image data is superimposed onto the real-time patient image, acquired by the camera, and displayed using standard live-view software. This enables the therapists to view both the patient's current and desired positions, and guide the patient into assuming the correct position. The method was evaluated using an in-house developed bolus-like breast phantom, mounted on a supporting platform, which could be tilted at various angles to simulate treatment-like geometries. Results: Our system allowed breast phantom alignment, with an accuracy of about 0.5 cm and 1 ± 0.5 degree. Better resolution could be possible using a camera with higher-zoom capabilities. Conclusion: We have developed an augmented-reality system, which combines a perspective projection of a CT image with a patient's real-time optical image. This system has the potential to improve patient setup accuracy during breast radiotherapy, and could possibly be used for other disease sites as well.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Anisotropic Elastic-Waveform Modeling for Fracture Characterization in EGS Reservoirs

Enhanced geothermal systems (EGS) contain newly created fractures in addition to possible existing fractures. Accurate characterization and monitoring of EGS reservoirs are crucial for optimal placement of new wells and effective extraction of geothermal heat. The fractured reservoirs behave as anisotropic media where seismic waves propagate with different velocities along different directions. In addition, the anisotropic properties of fluid-filled fracture zones could be different from those of dry fracture zones. We develop an optimized rotated staggered-grid elastic-wave finite-difference method for simulating seismic-wave propagation in heterogeneous, anisotropic media. Our new method uses a few extra grid points and optimized finite-difference coefficients based on the space-time dispersion relation, and reduce numerical dispersion of the conventional rotated staggered-grid finite-difference scheme. We validate our new method using synthetic vertical-seismic-profiling (VSP) data for an anisotropic geophysical model built with geologic features found at the Raft River EGS reservoir. This improved and optimized rotated staggered-grid finite-difference method provides an essential tool for analyzing VSP data, reverse-time migration, and elastic-waveform inversion in anisotropic, fractured reservoirs.

58 GEOSCIENCES↗

Likeness: a toolkit for connecting the social fabric of place to human dynamics

The ability to produce richly-attributed synthetic populations is key for understanding human dynamics, responding to emergencies, and preparing for future events, all while protecting individual privacy. The Likeness toolkit accomplishes these goals with a suite of Python packages: pymedm/pymedm\_legacy, livelike, and actlike. This production process is initialized in pymedm (or pymedm\_legacy) that utilizes census microdata records as the foundation on which disaggregated spatial allocation matrices are built. The next step, performed by livelike, is the generation of a fully autonomous agent population attributed with hundreds of demographic census variables. The agent population synthesized in livelike is then attributed with residential coordinates in actlike based on block assignment and, finally, allocated to an optimal daytime activity location via the street network. We present a case study in Knox County, Tennessee, synthesizing 30 populations of public K–12 school students \& teachers and allocating them to schools. Validation of our results shows they are highly promising by replicating reported school enrollment and teacher capacity with a high degree of fidelity.

Tuccillo, Joe↗

Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989

Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.

Rodriguez, Guillermo↗

Impedance Eduction in a Duct Using the Linearized Euler Equations

An impedance eduction technique that is based upon a numerical solution to the linearized Euler equations coupled with the minimization of an objective function is presented. The linearized Euler equations are solved numerically using a cubic finite element method and the minimum of the objective function is obtained via a gradient based optimizer. The mean flow is allowed to have a gradient in two coordinate directions and the impedance of the liner may vary arbitrarily over the liner surface. A new regularized wall impedance boundary condition presented by Rienstra which contains the effects of the mean boundary layer thickness is implemented. Impedances are educed for a perforate over honeycomb liner using test data acquired in the Langley Grazing Flow Impedance Tube. The impedance of the liner is educed both with an upstream source and a downstream source. The method is validated by comparing the educed impedance to a benchmark method. The primary conclusion of the study is that the impedances educed for upstream and downstream sources are not well matched and that the primary effect of the boundary thickness is to reduce the resistance of the liner.

Watson, Willie R.↗

Propulsive trajectory optimization to minimize surface contamination

MOTIVATION: We present an optimization technique for propulsive vehicles that autonomously minimizes contamination during surface approach and landing. In addition to short-range hoppers, the optimization technique is also fully applicable to traditional orbit-to-surface landers. This study addresses scenarios where surface alterations from propulsion events are counterproductive or hazardous to the mission objectives. This is of immediate interest for landers (whether human or robotic), that may rely on pristine soils collected in the immediate vicinity of landing sites to accomplish science investigations, mining, or ISRU surface operations. Such missions are averse to various surface-plume interactions such as thermal scoring, physical agitation, and contamination. The capability can be applied with minimal impact to the baseline mission concept. METHODS: Optimization algorithms have been developed to calculate descent trajectories and maneuvers, thrust magnitude, and attitude for various mission cases. These parameters are determined as an optimal solution when minimizing either fuel consumption, contamination deposited at the landing site, or some weighted combination of both. Among constraints imposed on the solution, we examined pitch rate, vertical takeoff and vertical landing (VTVL) requirements, size of the contamination zone, and minimum ground clearance during flight. This tool provides unique, non-intuitive solutions and can be a valuable resource for mission planners. RESULTS: A variety of agile trajectory solutions were obtained, each yielding different reductions in landing site contamination and corresponding to only modest increases in fuel consumption. Several optimal trajectories were obtained by varying the contamination weight in the fitness function. As expected, when the contamination weight is zero, the trajectory appears close to parabolic since the optimization scheme only attempts to minimize for fuel utilization, yielding essentially, the expected ballistic trajectory. Notably for contamination weights greater than zero, trajectory inflections are observed in the descent phase, which manifests as hovering or additional, mini “pseudo hops” before the final touchdown. A trajectory inflection is characterized by arresting the majority of the spacecraft vertical velocity component at a coordinate outside of the landing target, and without violating ground clearance constraints. FUTURE WORK: Our optimization technique is ready for laboratory or field demonstrations to validate the sophisticated maneuvering solutions obtained for fuel optimization and surface preservation. An appropriate testbed would validate the optimal guidance algorithms, the navigation system, and sensor suite by emulating vehicle flight in closed loop robotic tests. Critically, these algorithms could then be ported to flight software for implementation.

surface contamination↗

Hierarchical distributed voltage regulation

Embodiments of the disclosure provide for hierarchically distributed voltage regulation and power flow optimization in a power distribution network. According to one embodiment, a regional coordinator system may determine power flow for an autonomous grid (AG) representing a portion of the distribution network based on a set of voltage parameters from nodes in the AG. The set of voltage parameters my include a current voltage magnitude. The regional coordinator system may provide, to a central controller system of the distribution network, one or more power flow parameters based on the determined power flow for the AG.

Zhou, Xinyang↗

Accelerated Assessment of Critical Infrastructure in Aiding Recovery Efforts During Natural and Human-made Disaster

Relief and recovery from disasters (both natural and human-made) require a coordinated approach across several federal and state government agencies. In order to achieve optimal resource allocation and deployment of first responders, accurate and timely assessment of the impact and extent of destruction are the cornerstones to any recovery effort. Ideally, this knowledge should be gathered and shared within the first 0-24 hours (termed as "Acute Phase" by the U.S. CDC guideline) for informed decision-making. But achieving this poses significant challenges for the data collection and data harmonization processes, particularly when voluminous data are being generated from diverse and distributed sources during the disaster responses. To this end, this work developed a scalable and efficient workflow to dynamically collect and harmonize crowd-sourced geographic multi-modal data, and then assess critical infrastructure (CI) damaged during disaster events. We demonstrate the application of our framework with two real-world experiences in addressing post-disaster recovery efforts - for the Bahamas (Natural - due to Hurricane Dorian, 2019) and Beirut (Human-made - due to explosion caused by the ammonium nitrate stored in a warehouse, 2020). We have illustrated that a coordinated effort is needed for planning as well as for execution to achieve informed decision making.

Thakur, Gautam Malviya↗

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on the Banshee Distribution Network: Preprint

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on Banshee Distribution Network

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Real-Time Big Data Control-Theoretical Framework for Cyber-Physical-Human Systems [Book Chapter]

It is known that cyber-physical-human systems naturally arise from interdependent infrastructure systems and smart connected communities. Such applications require ubiquitous information sensing and processing, intelligent machine-to-machine communication for a seamless coordination, as well as intelligent interactions between humans and machines. This chapter presents a control-theoretical framework to model heterogeneous physical dynamic systems, information and communication, as well as cooperative controls and/or distributed optimization of such interconnected systems. It is shown that efficient analytical and computational algorithms can be modularly designed and hierarchically implemented to operate and optimize cyber-physical-human systems, first to quantify individually the input–output relationship of nonlinear dynamic behaviors of every physical subsystem, then to coordinate locally both cyber-physical interactions of neighboring agents as well as physical-human interactions, and finally to dynamically model and optimize the overall networked system. The hierarchical structure makes the overall optimization and control problem scalable and solvable. Moreover, the three levels integrate individual designs and optimization, distributed cooperative optimization, and decision-making through real-time, data-driven, model-based learning and control. Specifically, one of the contributions of the chapter is to demonstrate how the combination of dissipativity theory and cooperative control serves as a natural framework and promising tools to analyze, optimize, and control such large-scale system. Application to digital grid is investigated as an illustrative example.

97 MATHEMATICS AND COMPUTING↗

New approaches to optimization in aerospace conceptual design

Aerospace design can be viewed as an optimization process, but conceptual studies are rarely performed using formal search algorithms. Three issues that restrict the success of automatic search are identified in this work. New approaches are introduced to address the integration of analyses and optimizers, to avoid the need for accurate gradient information and a smooth search space (required for calculus-based optimization), and to remove the restrictions imposed by fixed complexity problem formulations. (1) Optimization should be performed in a flexible environment. A quasi-procedural architecture is used to conveniently link analysis modules and automatically coordinate their execution. It efficiently controls a large-scale design tasks. (2) Genetic algorithms provide a search method for discontinuous or noisy domains. The utility of genetic optimization is demonstrated here, but parameter encodings and constraint-handling schemes must be carefully chosen to avoid premature convergence to suboptimal designs. The relationship between genetic and calculus-based methods is explored. (3) A variable-complexity genetic algorithm is created to permit flexible parameterization, so that the level of description can change during optimization. This new optimizer automatically discovers novel designs in structural and aerodynamic tasks.

Gage, Peter J.↗

Quantum annealing-assisted lattice optimization

High Entropy Alloys (HEAs) have drawn great interest due to their exceptional properties compared to conventional materials. The configuration of HEA system is considered a key to their superior properties, but exhausting all possible configurations of atom coordinates and species to find the ground energy state is extremely challenging. In this work, we proposed a quantum annealing-assisted lattice optimization (QALO) algorithm, which is an active learning framework that integrates the Field-aware Factorization Machine (FFM) as the surrogate model for lattice energy prediction, Quantum Annealing (QA) as an optimizer and Machine Learning Potential (MLP) for ground truth energy calculation. By applying our algorithm to the NbMoTaW alloy, we reproduced the Nb depletion and W enrichment observed in bulk HEA. We found our optimized HEAs to have superior mechanical properties compared to the randomly generated alloy configurations. Our algorithm highlights the potential of quantum computing in materials design and discovery, laying a foundation for further exploring and optimizing structure-property relationships.

36 MATERIALS SCIENCE↗