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At least 829 records · Page 46

Precursor reaction pathway leading to BiFeO 3 formation: insights from text-mining and chemical reaction network analyses

BiFeO 3 (BFO) is a next-generation non-toxic multiferroic material with applications in sensors, memory devices, and spintronics, where its crystallinity and crystal structure directly influence its functional properties. Designing sol–gel syntheses that result in phase-pure BFO remains a challenge due to the complex interactions between metal complexes in the precursor solution. Here, we combine text-mined data and chemical reaction network (CRN) analysis to obtain novel insight into BFO sol–gel precursor chemistry. We perform text-mining analysis of 340 synthesis recipes with the emphasis on phase-pure BFO and identify trends in the use of precursor materials, including that nitrates are the preferred metal salts, 2-methoxyethanol (2 ME) is the dominant solvent, and adding citric acid as a chelating agent frequently leads to phase-pure BFO. Our CRN analysis reveals that the thermodynamically favored reaction mechanism between bismuth nitrate and 2ME interaction involves partial solvation followed by dimerization, contradicting assumptions in previous literature. We suggest that further oligomerization, facilitated by nitrite ion bridging, is critical for achieving the pure BFO phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High pressure synthesis and crystal structure of a ternary superconductor Ca{sub 2}Al{sub 3}Si{sub 4} containing layer structured calcium sub-network isomorphous with black phosphorus

The Zintl compound CaAl{sub 2}Si{sub 2} is peritectically decomposed to a mixture of Ca{sub 2}Al{sub 3}Si{sub 4} and aluminum metal at temperatures above 600 Degree-Sign C under a pressure of 5 GPa. The new ternary compound Ca{sub 2}Al{sub 3}Sl{sub 4} crystalizes with the space group Cmc2{sub 1} and the lattice parameters a=5.8846(8), b=14.973(1), and c=7.7966(5) A. The structure is composed of aluminum silicide framework [Al{sub 3}Si{sub 4}] and layer structured [Ca{sub 2}] network interpenetrating with each other. The electron probe microanalysis (EPMA) shows the formation of solid solutions Ca{sub 2}Al{sub 3-x}Si{sub 4+x} (x<0.6). The layer structured [Ca{sub 2}] sub-network is isomorphous with black phosphorus. The new ternary compound shows superconductivity with a transition temperature (T{sub c}) of 6.4 K. The band structure calculation suggests that the superconductivity should occur through the conduction bands mainly composed of 3p orbitals of the aluminum silicide framework. - Graphical abstract: A new ternary superconductor Ca{sub 2}Al{sub 3}Si{sub 4} has been prepared under high pressure and high temperature conditions, which includes layer structured calcium sub-network isomorphous with black phosphorus. Highlights: Black-Right-Pointing-Pointer A typical Zintl compound CaAl{sub 2}Si{sub 2} melts congruently at ambient pressure. Black-Right-Pointing-Pointer Under high pressure CaAl{sub 2}Si{sub 2} decomposes to Ca{sub 2}Al{sub 3}Si{sub 4} and Al at {approx}600 Degree-Sign C. Black-Right-Pointing-Pointer Ca{sub 2}Al{sub 3}Si{sub 4} contains Ca sub-network isomorphous with black phosphorus. Black-Right-Pointing-Pointer Ca{sub 2}Al{sub 3}Si{sub 4} shows superconductivity with a transition temperature of 6.4 K.

36 MATERIALS SCIENCE↗

Improving Alkylamine Incorporation in Porous Polymer Networks through Dopant Incorporation

The industrial scale capture of CO 2 from flue gas streams is becoming an increasingly important environmental issue. However, many of the existing CO 2 capture systems either have regenerative energy demands that are too high or are cost prohibitive. A promising solution is the utilization of functionalized solid sorbents, such as porous polymer networks (PPNs). PPNs are attractive due to their inherent structural stability, flexibility, high surface areas, and ability to incorporate various functional groups within the chemical scaffold. Herein, a low cost, scalable alternative to common carbon capture systems using a series of robust mesoporous melamine-formaldehyde resins (mPMFs) loaded with active alkylamine sorbents is presented, which is dubbed as the PPN-150 family. The variants within this material class are differentiated based on the incorporation of functionalized dopants; small molecules added at low molar percent concentrations to impart additional functionality into the PPN in order to achieve low cost noncovalent tethering of alkylamines. The cyanuric acid doped PPN-151-DETA (DETA = diethylenetriamine) demonstrate unique features such as improved cycling capacity and heat of adsorption. To show its scalability, PPN-151-DETA is successfully synthesized at the 250 g scale without loss of the sorbent properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Grid Optimization Competition on Synthetic and Industrial Power Systems

This paper summarizes a grid optimization (GO) competition effort in the United States to find the best solution strategies for up to interconnect-scale power system networks with around 32,000 buses. The optimization problem is a mixedinteger, non-convex non-linear problem, (MINLP) and includes discrete variables such as unit commitment and line switching, control settings (transformer taps and phase shifters with impedance correction tables), and bus shunts. The case study includes six actual industry grids as well as 16 realistic synthetic grids created by three different dataset teams. The winners are selected and ranked based on scoring criteria, which consider the solution quality (such as objective functions) within time limits. Nine winner teams are selected from 26 competitor teams. The results achieved by different teams are described and the performance of different algorithms on synthetic grids and actual industry grids are compared and analyzed.

mixed-integer non-linear programming↗

Characterization of CdZnTeSe Nuclear Detector Chemically Etched in Bromine Methanol

Semiconductor nuclear radiation detectors made from tertiary and quaternary compounds of cadmium telluride (CdTe) can operate at room temperature without cryogenic cooling. One of such materials that have become of great interest is cadmium zinc telluride selenide (CdZnTeSe). Compared to other CdTe-based materials, such as cadmium zinc telluride (CdZnTe), CdZnTeSe can be grown with much less Te inclusions and sub-grain boundary networks. Chemical etching is often used to smoothen wafer surfaces during detector fabrication. This paper presents the characterization of CdZnTeSe that is chemically etched using bromine methanol solution. Infrared imaging shows that the wafer has no sub-grain boundary networks that often limit detector performance. The current-voltage (I-V) characterization experiment gave a resistivity of 4.6 × 10 10 Ω-cm for the sample. The I-V curve was linear in the ±10 to ±50 volts range. An energy resolution of 7.2% was recorded at 100 V for the 59.6-keV gamma line of 241 Am.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Network testbed creation and validation

Embodiments of network testbed creation and validation processes are described herein. A "network testbed" is a replicated environment used to validate a target network or an aspect of its design. Embodiments describe a network testbed that comprises virtual testbed nodes executed via a plurality of physical infrastructure nodes. The virtual testbed nodes utilize these hardware resources as a network "fabric," thereby enabling rapid configuration and reconfiguration of the virtual testbed nodes without requiring reconfiguration of the physical infrastructure nodes. Thus, in contrast to prior art solutions which require a tester manually build an emulated environment of physically connected network devices, embodiments receive or derive a target network description and build out a replica of this description using virtual testbed nodes executed via the physical infrastructure nodes. This process allows for the creation of very large (e.g., tens of thousands of network elements) and/or very topologically complex test networks.

97 MATHEMATICS AND COMPUTING↗

Network testbed creation and validation

Embodiments of network testbed creation and validation processes are described herein. A "network testbed" is a replicated environment used to validate a target network or an aspect of its design. Embodiments describe a network testbed that comprises virtual testbed nodes executed via a plurality of physical infrastructure nodes. The virtual testbed nodes utilize these hardware resources as a network "fabric," thereby enabling rapid configuration and reconfiguration of the virtual testbed nodes without requiring reconfiguration of the physical infrastructure nodes. Thus, in contrast to prior art solutions which require a tester manually build an emulated environment of physically connected network devices, embodiments receive or derive a target network description and build out a replica of this description using virtual testbed nodes executed via the physical infrastructure nodes. This process allows for the creation of very large (e.g., tens of thousands of network elements) and/or very topologically complex test networks.

97 MATHEMATICS AND COMPUTING↗

Microstructure evolution in the fusion zone of laser-welded Mg–Gd–Y–Zr alloy during solution and aging treatment

The microstructure evolution in the fusion zone of laser-welded Mg-Gd-Y-Zr alloy during solution and aging treatment is investigated. The morphology of the Mg{sub 24}(Gd,Y){sub 5} in the divorced eutectic at the grain boundary transforms from a continuous network to disconnected and fragmentized islands and then to spheroidal particles before complete dissolution during the solution treatment at 430 °C. During the subsequent aging treatment at 225 °C, the precipitation sequence in the fusion zone follows the order of supersaturated solid solution (SSSS) → βʺ(D0{sub 19}) → βʹ(cbco) → β{sub 1}(fcc) → β(fcc). High-density precipitates are present at the original grain boundaries of the fusion zone from the welded structure but there are less precipitates in the interior of the original grains. The grain growth during the solution treatment at 430 °C comprises the slowly increasing stage, rapidly increasing stage, and stable stage. The network-distributed Mg{sub 24}(Gd,Y){sub 5} impedes migration of the grain boundaries, restricts grain growth in the first slowly increasing stage, and segregation of zirconium near the grain boundaries also affects migration of the grain boundaries. - Highlights: •Different quantities of precipitates are present at different location of grain. •The network-distributed Mg{sub 24}(Gd,Y){sub 5} restricts grain growth. •Segregation of Zr affects migration of grain boundaries.

36 MATERIALS SCIENCE↗

Tenth Goddard Conference on Mass Storage Systems and Technologies in Cooperation with the Nineteenth IEEE Symposium on Mass Storage Systems

This document contains copies of those technical papers received in time for publication prior to the Tenth Goddard Conference on Mass Storage Systems and Technologies which is being held in cooperation with the Nineteenth IEEE Symposium on Mass Storage Systems at the University of Maryland University College Inn and Conference Center April 15-18, 2002. As one of an ongoing series, this Conference continues to provide a forum for discussion of issues relevant to the ingest, storage, and management of large volumes of data. The Conference encourages all interested organizations to discuss long-term mass storage requirements and experiences in fielding solutions. Emphasis is on current and future practical solutions addressing issues in data management, storage systems and media, data acquisition, long-term retention of data, and data distribution. This year's discussion topics include architecture, future of current technology, storage networking with emphasis on IP storage, performance, standards, site reports, and vendor solutions. Tutorials will be available on perpendicular magnetic recording, object based storage, storage virtualization and IP storage.

Kobler, Benjamin↗

A Self-Stabilizing Hybrid Fault-Tolerant Synchronization Protocol

This paper presents a strategy for solving the Byzantine general problem for self-stabilizing a fully connected network from an arbitrary state and in the presence of any number of faults with various severities including any number of arbitrary (Byzantine) faulty nodes. The strategy consists of two parts: first, converting Byzantine faults into symmetric faults, and second, using a proven symmetric-fault tolerant algorithm to solve the general case of the problem. A protocol (algorithm) is also present that tolerates symmetric faults, provided that there are more good nodes than faulty ones. The solution applies to realizable systems, while allowing for differences in the network elements, provided that the number of arbitrary faults is not more than a third of the network size. The only constraint on the behavior of a node is that the interactions with other nodes are restricted to defined links and interfaces. The solution does not rely on assumptions about the initial state of the system and no central clock nor centrally generated signal, pulse, or message is used. Nodes are anonymous, i.e., they do not have unique identities. A mechanical verification of a proposed protocol is also present. A bounded model of the protocol is verified using the Symbolic Model Verifier (SMV). The model checking effort is focused on verifying correctness of the bounded model of the protocol as well as confirming claims of determinism and linear convergence with respect to the self-stabilization period.

Malekpour, Mahyar R.↗

Power, data latency, and radio frequnecy interference issues in Mars Realy Network scheduling

At different time periods in the future, missions to Mars will overlap. Previous studies indicate that during such periods, existing deep space communication infrastructure cannot handle all Mars communication needs. A plausible solution is to take into account the end-to-end communication performances of network along with operational constraints, and optimize the resource usage by scheduling communication at highest possible data throughputs. As a result, shorter communication time is required and more missions can be accommodated. This principle is demonstrated in this paper for a Mars relay communication network; a network consisting of multiple surface units and orbiters on Mars and the Deep Space Stations.

power latency RFI Mars Relay Network scheduling↗

Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching

Integrating genome-scale metabolic networks with reactive transport models (RTMs) provides a detailed description of the dynamic changes in microbial growth and metabolism. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated application of linear programming (LP) to obtain flux balance analysis (FBA) solutions in every time step and spatial grid. To address this challenge, we propose a new simulation method where we train and validate artificial neural networks (ANNs) using randomly sampled FBA solutions and incorporate the resulting surrogate FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study of Shewanella oneidensis MR-1. During aerobic growth on lactate, S. oneidensis produces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred nutrients are depleted. To effectively simulate these complex dynamics, we used a cybernetic approach that models metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based surrogate models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Moreover, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.

59 BASIC BIOLOGICAL SCIENCES↗

Quantum annealing algorithms for Boolean tensor networks

Abstract Quantum annealers manufactured by D-Wave Systems, Inc., are computational devices capable of finding high-quality heuristic solutions of NP-hard problems. In this contribution, we explore the potential and effectiveness of such quantum annealers for computing Boolean tensor networks. Tensors offer a natural way to model high-dimensional data commonplace in many scientific fields, and representing a binary tensor as a Boolean tensor network is the task of expressing a tensor containing categorical (i.e., $$\{0, 1\}$$ { 0 , 1 } ) values as a product of low dimensional binary tensors. A Boolean tensor network is computed by Boolean tensor decomposition, and it is usually not exact. The aim of such decomposition is to minimize the given distance measure between the high-dimensional input tensor and the product of lower-dimensional (usually three-dimensional) tensors and matrices representing the tensor network. In this paper, we introduce and analyze three general algorithms for Boolean tensor networks: Tucker, Tensor Train, and Hierarchical Tucker networks. The computation of a Boolean tensor network is reduced to a sequence of Boolean matrix factorizations, which we show can be expressed as a quadratic unconstrained binary optimization problem suitable for solving on a quantum annealer. By using a novel method we introduce called parallel quantum annealing, we demonstrate that Boolean tensor’s with up to millions of elements can be decomposed efficiently using a DWave 2000Q quantum annealer.

97 MATHEMATICS AND COMPUTING↗

Enabling large-scale viscoelastic calculations via neural network acceleration

One of the most significant challenges involved in efforts to understand the effects of repeated earthquake cycle activity is the computational costs of large-scale viscoelastic earthquake cycle models. Computationally intensive viscoelastic codes must be evaluated at thousands of times and locations, and as a result, studies tend to adopt a few fixed rheological structures and model geometries and examine the predicted time-dependent deformation over short (<10 years) time periods at a given depth after a large earthquake. Training a deep neural network to learn a computationally efficient representation of viscoelastic solutions, at any time, location, and for a large range of rheological structures, allows these calculations to be done quickly and reliably, with high spatial and temporal resolutions. We demonstrate that this machine learning approach accelerates viscoelastic calculations by more than 50,000%. Finally, this magnitude of acceleration will enable the modeling of geometrically complex faults over thousands of earthquake cycles across wider ranges of model parameters and at larger spatial and temporal scales than have been previously possible.

58 GEOSCIENCES↗

Millimeter-wave home area network prospect with cost-effective RoF links

The growth towards the millimeter-wave band in the home area networks (HAN) leads to high data rate transmission to satisfy the new user services. Unfortunately, the transmission coverage in this band is limited to short distances because of the strong air absorption and obstacles such as walls. The effort is then focused on the extension of the network coverage of the wireless link in this band. Solutions based on multiple connected access points to optical fibers are useful methods to ensure wireless connectivity to the entire home. For HAN applications, radio-over-fiber (RoF) using intensity modulation and direct detection technique is the mostly favorite technology for the transmission of a broadband wireless signal because dealing with a cost-effective solution. We investigate in this paper the performance of such RoF-wireless architecture with low-cost optoelectronic modules through the error vector magnitude (EVM) metric. The RoF links investigated are a directly modulated VCSEL with integrated photoreceiver module, an electroabsorption-modulated laser with PIN photodiode and a Mach–Zehnder Modulator with PIN photodiode. A simulation approach based on equivalent electrical circuit models of photonic components is developed in ADS (Advanced Design System) by using a co-simulation technique that combines both analog and digital signals. The downlink channel of the complete transmission system including wireless channel and frequency conversion circuits to millimeter-wave (mm-wave) band is studied by simulation. The obtained results of EVM show good performances of cost-effective links with QPSK and 16-QAM modulation over a dynamic range of 15 dB.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Roles of Hydrogen Bonds and Alignment in Oriented Attachment of Gibbsite Nanoparticles: Insights from Molecular Dynamics

Oriented attachment (OA) of nanoparticles is an important crystal growth pathway in the synthesis of hierarchical structures. Although a significant understanding of OA has been made, the effect of atomistic misalignment and the roles of solvent/particle and particle/particle interactions on the structure–energy relationship during an OA remain elusive. In this study, we perform molecular dynamics simulations to calculate the potential of mean force (PMF) profile for gibbsite particle translation on a gibbsite slab with 1 or 2 intervening water layers (1W or 2W). The structures of the gibbsite surfaces and the confined water are analyzed to determine how the number and type of hydrogen bonds (H-bonds) influence the free energy profile during the translation. The PMF profile exhibits a periodicity of length 5.078 Å, consistent with the gibbsite unit cell size along the translation direction. The changes in the surface–water and water–water hydrogen bond network and water and surface OH groups’ orientations during the translation are strongly coupled with the changes in the PMF profile in the 1W case. However, when increasing the number of intervening water layers from 1W to 2W, the particle/slab misalignment becomes a dominant factor controlling the behavior of the PMF profile. We also establish a method to quantify misalignment between the particle and the slab, which exhibits a strong correlation with the free energy for the 2W case. These results shed more light into the roles of particle/slab misalignment and hydrogen bond network in the OA of mineral particles in aqueous solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Particle-Based Conditional Sampling Scheme for the Simulation of Transport in Fractured Rock With Diffusion Into Stagnant Water and Rock Matrix

In situ experiments and field-scale characterization studies have pointed out that, in fractured crystalline media, groundwater flow is highly channelized. This implies that, at the scale of a single fracture, only part of the fracture surface area is in contact with flowing water, while the rest of in-plane water is essentially stagnant and can be accessed by solutes via molecular diffusion. Despite their importance for contaminant retention, to date, there are no numerical or analytical approaches that could be used to assess the implication of stagnant water zones on solute transport in realistic large-scale Discrete Fracture Network-based models. In this study, we present an efficient and flexible algorithm for the simulation of transport in fractured rock with diffusion into stagnant water and rock matrix. The algorithm is a generalization of a previously developed numerical framework for time domain particle tracking in sparsely fractured rock. The key of the generalization is that total time in fracture (τ f ) is first evaluated using a Monte Carlo sampling and then a second sampling is performed conditioned on τ f . The algorithm has been successfully validated against existing independent solutions and the implication of diffusion into stagnant water and secondary diffusion into the matrix has been assessed for a realistic modeling scenario. The results show that, due to diffusion into stagnant water, contaminants are more strongly retarded. This increased retention is more significant for sorbing species, as a larger number of sorption sites is accessible. A high sensitivity to the flowing channel/stagnant water zone geometry has also been observed.

54 ENVIRONMENTAL SCIENCES↗

Arrested Phase Separation in Double-Exchange Models: Large-Scale Simulation Enabled by Machine Learning

In this work, we present large-scale dynamical simulations of electronic phase separation in the single-band double-exchange model based on deep-learning neural-network potentials trained from small-size exact diagonalization solutions. We uncover an intriguing correlation-induced freezing behavior as doped holes are segregated from half filled insulating background during equilibration. While the aggregation of holes is stabilized by the formation of ferromagnetic clusters through Hund’s coupling between charge carriers and local magnetic moments, this stabilization also creates confining potentials for holes when antiferromagnetic spin-spin correlation is well developed in the background. The dramatically reduced mobility of the self-trapped holes prematurely disrupts further growth of the ferromagnetic clusters, leading to an arrested phase separation. Implications of our findings for phase separation dynamics in materials that exhibit colossal magnetoresistance effect are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗