Optimal composition of heterogeneous multi-agent teams for coverage problems with performance bound guarantees
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Sun, Chuangchuang↗
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Results for “composite optimization”
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Establishing a Scientific Basis for Optimizing Compositions, Process Paths and Fabrication Methods for Nanostructured Ferritic Alloys for Use in Advanced Fission Energy Systems
The broad objective of this NEUP was to further develop a class of 12-15Cr ferritic alloys that are dispersion strengthened and made radiation tolerant by an ultrahigh density of Y-Ti-O nanofeatures (NFs) in the size range of less than 5 nm. We call these potentially transformable materials nanostructured ferritic alloys (NFAs). NFAs are typically processed by ball milling pre-alloyed rapidly solidified powders and yttria (Y2O3) powders. Proper milling effectively dissolves the Ti, Y and O solutes that precipitate as NFs during hot consolidation.
36 MATERIALS SCIENCE↗
Optimized Compositional Design and Processing-Fabrication Paths for Larger Heats of Nanostructured Ferritic Alloys
The objective of this work was to characterize the alloy 14YWT-PM2, which is an extruded and cross-rolled precursor alloy to a large heat of 14YWT being produced using an alternative processing path that incorporates Y during gas atomization process.
36 MATERIALS SCIENCE↗
Resin Testing and Modeling for Optimal Composite Processing
Polymer composites have properties such as high strength and stiffness, low weight, good thermal and chemical stability, as well as impact and abrasion resistance that make them ideal for high-performance applications. The chemistries of these materials are continuously improving, so determining their properties is vital for successfully producing them and achieving the desired results. Multiple methods can be employed to monitor characteristics such as heat flow, weight, dimension, and modulus as a function of time and temperature. By analyzing this information, models can be developed to predict outcomes of parameters not tested for. In one application, materials proposed for wet filament winding and the production of high pressure vessels can be analyzed to verify they will have the necessary low viscosity for good fiber wetting and long pot life for the extended handling inherent to this process. Such data about a prospective system provides valuable information on how that material could ultimately be processed to yield the desired part.
36 MATERIALS SCIENCE↗
Alloy Composition Optimization for High Critical Current Density of (Nb,Ta,Ti)3Sn High Field Superconductor
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43 PARTICLE ACCELERATORS↗
Hybrid Data‐Driven Discovery of High‐Performance Silver Selenide‐Based Thermoelectric Composites
Optimizing material compositions often enhances thermoelectric performances. However, the large selection of possible base elements and dopants results in a vast composition design space that is too large to systematically search using solely domain knowledge. To address this challenge, a hybrid data-driven strategy that integrates Bayesian optimization (BO) and Gaussian process regression (GPR) is proposed to optimize the composition of five elements (Ag, Se, S, Cu, and Te) in AgSe-based thermoelectric materials. Data is collected from the literature to provide prior knowledge for the initial GPR model, which is updated by actively collected experimental data during the iteration between BO and experiments. Within seven iterations, the optimized AgSe-based materials prepared using a simple high-throughput ink mixing and blade coating method deliver a high power factor of 2100 µW m −1 K −2 , which is a 75% improvement from the baseline composite (nominal composition of Ag 2 Se 1 ). In conclusion, the success of this study provides opportunities to generalize the demonstrated active machine learning technique to accelerate the development and optimization of a wide range of material systems with reduced experimental trials.
36 MATERIALS SCIENCE↗
Optimization of the compositions of polyanionic sodium-ion battery cathode NaFe 2-x V x (PO 4 )(SO 4 ) 2
Sodium (Na) super ionic conductor (NASICON) polyanionic compounds have recently attracted much attention from the battery community because of their electroactive properties and reasonably high ionic conductivities, leading to their use as a cathode in sodium-ion batteries. This article describes the compositional optimizations, crystallographic evaluations, and electrochemical behavior of a new mixed NASICON polyanionic compound, NaFe 2-x V x (PO 4 )(SO 4 ) 2 . By doping the characteristic Fe 3+ sites of the FeO 6 octahedrons with varying amounts of V 3+ , the electrochemical stability and charge transport in NaFe 2 (PO 4 )(SO 4 ) 2 were enhanced. The resulting best composition, with crystal structure NaFe 1.4 V 0.6 (PO 4 )(SO 4 ) 2 resolved through the Rietveld method, exhibited a stable capacity compared with the other synthesized compositions. In situ powder x-ray diffraction measurements, a single-phase intercalation/deintercalation mechanism of the NASICON structure in the measured sodium concentration window was observed with no impurity phase formation. Further electrochemical assessments revealed the interfacial charge transfer kinetics to be the rate-limiting step in the sodium concentration window. Also, the measured sodium-ion diffusivity values in the range of 6 × 10 -11 to 7 × 10 -11 cm 2 /s in the measured sodium concentration range. The results reported here highlight the potential of compositionally and morphologically optimized NaFe 1.4 V 0.6 (PO 4 )(SO 4 ) 2 with higher particle surface areas as a cathode material for high-performance sodium-ion batteries.
25 ENERGY STORAGE↗
Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization
Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, for a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.
42 ENGINEERING↗
Dendrite-Free and Performance-Enhanced Lithium Metal Batteries through Optimizing Solvent Compositions and Adding Combinational Additives
The instability of lithium (Li) metal anode due to the dendritic growth and low Coulombic efficiency hinders the practical application of the well-regarded high-energy-density Li metal batteries. Here we report the systematic studies of improving the stability of Li metal anode and the electrochemical performances of the related Li metal batteries through the addition of combinational additives and the optimization of solvent compositions in dual-salt/carbonate electrolytes. A dendrite-free and high Coulombic efficiency of 98.1% for Li metal anode is achieved. The well protection of the Li metal anode and the excellent cyclability and rate capability of the 4-V Li metal batteries have been obtained. This is attributed to the formation of a robust, denser, more polymeric and higher ionic conductive surface film on the Li metal anode via the electrochemical reductive decompositions of the electrolyte components and the ring-opening polymerization of additives and cyclic carbonate solvents. The key findings of this work emphasize that the optimization of solvent compositions and the manipulation of the additives are facile and effective to enhance the Li metal battery performances.
Li metal batteries, dual-salt electrolyte, additiv↗
A Quick Screening Approach for Design of Multi-Principle Element Alloy with Solid Solution Phase
Multi-principle element alloys (MPEAs) provide an innovative way to design materials with potential applications in extreme conditions, such as high-dose irradiation in nuclear reactors, high temperatures in aeronautic and aerospace engineering, etc. However, the composition design and optimization of MPEAs are challenging due to the vast options and complexity which make traditional theory and methods insufficient or even invalid. To effectively design MPEAs, a two-parameter approach is developed based on newly proposed enthalpy and entropy-enthalpy competition parameters. This approach can not only be used to classify conventional steels, high-entropy steels (HESs), high-entropy alloys (HEAs) and amorphous alloys, but also to predict the optimal composition of MPEAs with stable solid solution (SS) phases. The optimal compositions of three sets of Fe-Mn-Cr-Co-Ni alloys are quickly screened from millions of options to form HESs or HEAs with stable SS phases. This quick screening approach can also be applied to design other alloys and facilitate the research and development of MPEAs possessing the targeted properties and economic acceptability.
Zheng, Mingjie↗
Formation of Plastic Inclusions in U71Mnk High-Speed Heavy-Rail Steel Refined by CaO-SiO{sub 2}-Al{sub 2}O{sub 3}-MgO Slag
To precisely control the characteristics of nonmetallic inclusions with high plasticity in U71Mnk high-speed heavy-rail steel deoxidized by Si and Mn, the chemical composition of CaO-SiO{sub 2}-Al{sub 2}O{sub 3}-MgO slag in the ladle furnace (LF) refining process was optimized by thermodynamic calculations. Relationships among the refining slag, nonmetallic inclusions, and elemental concentrations in the steels were analyzed to obtain the conditions for determining the optimal composition of refining slag. The optimal compositions and the component activities of CaO-SiO{sub 2}-Al{sub 2}O{sub 3}-MgO refining slag were determined and discussed according to calculations using FactSage 7.0. Finally, ten industrial experiments were performed. Variations in the compositions of LF refining slag, inclusions, and steel, as well as the sizes of the inclusions, and metallographic classification assessment of the U71Mnk steel product, were investigated and discussed to verify the feasibility and effectiveness of the optimized LF refining slag. Kinetics of steel–slag and steel-inclusion reactions during LF refining was studied and compared. The results show that to obtain low [O], [Al], and [S] contents and inclusions with high plasticity in molten steel, the optimal composition of the LF refining slag should be CaO: 44.2 to 51.7 wt pct, SiO{sub 2}: 41.4 to 47.0 wt pct, Al{sub 2}O{sub 3}: 0 to 4.7 wt pct and MgO 5.0 to 7.0 wt pct, where the basicity R is above 1.00 and the C/A ratio is above 9.00. After the LF refining process, the contents of total oxygen (T.O.), [Al], and [S] gradually stabilized in the range of 0.0008 to 0.0012 wt pct, 0.002 to 0.0028 wt pct and 0.0026 to 0.0037 wt pct, respectively. The densities of the three kinds of typical inclusions (CaO-SiO{sub 2}-Al{sub 2}O{sub 3}-MgO, MnS, and CaO-SiO{sub 2}-Al{sub 2}O{sub 3}-MgO-MnS) also decreased and reached approximately 0.25/mm{sup 2}, and no inclusion larger than 6.0 μm was found. The composition of the inclusions gradually changed into the optimal range in the CaO-SiO{sub 2}-Al{sub 2}O{sub 3}-MgO slag system during the LF refining process.
36 MATERIALS SCIENCE↗
The theoretical ultimate magnetoelectric coefficients of magnetoelectric composites by optimization design
This paper investigates what is the largest magnetoelectric (ME) coefficient of ME composites, and how to realize it. From the standpoint of energy conservation, a theoretical analysis is carried out on an imaginary lever structure consisting of a magnetostrictive phase, a piezoelectric phase, and a rigid lever. This structure is a generalization of various composite layouts for optimization on ME effect. The predicted theoretical ultimate ME coefficient plays a similar role as the efficiency of ideal heat engine in thermodynamics, and is used to evaluate the existing typical ME layouts, such as the parallel sandwiched layout and the serial layout. These two typical layouts exhibit ME coefficient much lower than the theoretical largest values, because in the general analysis the stress amplification ratio and the volume ratio can be optimized independently and freely, but in typical layouts they are dependent or fixed. To overcome this shortcoming and achieve the theoretical largest ME coefficient, a new design is presented. In addition, it is found that the most commonly used electric field ME coefficient can be designed to be infinitely large. We doubt the validity of this coefficient as a reasonable ME effect index and consider three more ME coefficients, namely the electric charge ME coefficient, the voltage ME coefficient, and the static electric energy ME coefficient. We note that the theoretical ultimate value of the static electric energy ME coefficient is finite and might be a more proper measure of ME effect.
36 MATERIALS SCIENCE↗
Fabrication of compact and stable perovskite films with optimized precursor composition in the fast-growing procedure
The fast-growing procedure (FGP) provides a simple, high-yield and lead (Pb)-release free method to prepare perovskite films. In the FGP, the ultra-dilute perovskite precursor solution is drop-cast onto a hot (~240 degrees C) substrate, where a perovskite film grows immediately accompanied by the rapid evaporation of the host solvent. In this process, all the raw materials in the precursor solution are deposited into the final perovskite film. The potential pollution caused by Pb can be significantly reduced. Properties of the FGP-processed perovskite films can be modulated by the precursor composition. While CH3NH3Cl (MACl) affects the crystallization process and leads to full surface coverage, CH(NH2)2I (FAI) enhances the thermal stability of the film. Based on the optimized precursor composition of PbI2(1-x)FAI xMACl, x=0.75, FGP-processed planar heterojunction perovskite solar cells exhibit power conversion efficiencies (PCEs) exceeding 15% with suppressed hysteresis and excellent reproducibility.
14 SOLAR ENERGY↗
Optimization of Composite Cloud Service Processing with Virtual Machines
By leveraging virtual machine (VM) technology, we optimize cloud system performance based on refined resource allocation, in processing user requests with composite services. Our contribution is three-fold. (1) We devise a VM resource allocation scheme with a minimized processing overhead for task execution. (2) We comprehensively investigate the best-suited task scheduling policy with different design parameters. (3) We also explore the best-suited resource sharing scheme with adjusted divisible resource fractions on running tasks in terms of Proportional-share model (PSM), which can be split into absolute mode (called AAPSM) and relative mode (RAPSM). We implement a prototype system over a cluster environment deployed with 56 real VM instances, and summarized valuable experience from our evaluation. As the system runs in short supply, lightest workload first (LWF) is mostly recommended because it can minimize the overall response extension ratio (RER) for both sequential-mode tasks and parallel-mode tasks. In a competitive situation with over-commitment of resources, the best one is combining LWF with both AAPSM and RAPSM. It outperforms other solutions in the competitive situation, by 16 + % w.r.t. the worst-case response time and by 7.4 + % w.r.t. the fairness.
cloud resource allocation↗
Optimizing Phase Change Composite Thermal Energy Storage Using the Thermal Ragone Framework
The thermal Ragone framework can be applied to the design of thermal energy storage heat exchangers to identifying relationships between their power requirements and energy capabilities. This presentation focuses on the design of planar thermal energy storage heat exchangers with phase change materials and thermal conductivity additives. Finite-difference models were used to optimize thermal storage heat exchanger designs focusing on key design parameters of conductivity additive volume fraction, spacing between tubes, and the phase transition temperatures. Design trends were developed for optimal designs based on varying thermal power requirements. To aid in future device design, models of reduced complexity were developed with the ability to predict optimal designs with computational speeds up to 5,000 times faster than finite-difference models.
ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗
Development of a Kollidon 90F-PEG300-Glycerin Binder for PZT 95/5 Ceramic Processing
This SAND Report documents the development of organic binder system for PZT 95/5 consisting of Kollidon 90F, PEG300, and glycerin. Binders are a critical component in the manufacture of ceramic components. Low performing binders can result in poor yield and lower performance of ceramic components. This study sought to develop a well performing binder system for PZT 95/5 ceramics to support Ferroelectric Neutron Generator manufacturing. The study explored the glass transition temperature, powder compaction properties, green strengths, and thermal decomposition over a wide composition range. An optimal composition was found consisting of 1.3 wt.% Kollidon 90F, 0.5 wt.% PEG300, and 0.2 wt.% glycerin, and incorporating humidity conditioning . The results showed that the optimized binder exhibited improved compaction performance and enhanced green strength compared to a baseline binder and at lower loading. Further, sintered PZT 95/5 parts prepared using the optimized binder exhibited ~5% improved polarization performance without alteration to the microstructure.
36 MATERIALS SCIENCE↗
Optimizing the Composite Cathode Microstructure in All‐Solid‐State Batteries by Structure‐Resolved Simulations
Abstract All‐solid‐state batteries are considered as an enabler for applications requiring high energy and power density. However, they still fall short of their theoretical potential due to various limitations. One issue is poor charge transport kinetics resulting from both material inherit limitations and non‐optimized design. Therefore, a better understanding of the relevant properties of the cathode microstructure is necessary to improve cell performance. In this article, we identify optimization potentials of the composite cathode by structure‐resolved electrochemical 3D‐simulations. In our simulation study, we investigate the influence of cathode active material fraction, density, particle size, and active material properties on cell performance. Special focus is set on the impact of grain boundaries on the cathode design. Based on our simulation results, we can predict target values for cell manufacturing and reveal promising optimization strategies for an improved cathode design.
25 ENERGY STORAGE↗