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At least 1,423 records · Page 79

Superlattice-Structured Films by Magnetron Sputtering as New Era Electrodes for Advanced Lithium-ion Batteries

Sustaining sound structures in Si-based anodes is extremely challenging because of the high volumetric expansion that occurs upon cycling. To maintain high capacities over cycles, new designs rely on engineering-specific hierarchical geometries and/or optimized composite compositions such that at least one of the multiple elements serves as buffer and/or electron conductive pathways in the electrodes. In this paper, we report an innovative design in which alternating layers of periodic atomic structures involving multiple elements form a new anode material for lithium-ion batteries. In this work, a superlattice-structured amorphous film made using Si, Mo, and Cu is fabricated by a simple and scalable magnetron sputtering process for the first time. This continuous and repetitive superlattice formation along the film thickness provides a homogeneous stress-strain distribution. The Mo-Cu layer in the superlattice acts as an inactive-conductive layer and as a backbone to handle the volume expansion of active Si upon cycling. This nano-functional superlattice approach enables harnessing the high energy density of Si while maintaining its structural stability. As a result, the electrode exhibits high specific capacity and capacity retention even at high cycling rates. The possible use of the film in a full cell is also evaluated by cycling it vs. the LiMn 1.5 Ni 0.5 O 4 cathode. The full cell maintains a stable capacity of about 900 mAh g anode -1 over 150 cycles, at ~600 mA g -1 rate. The remarkable performance of this nano-functional superlattice film is found to be promising as anodes for applications that require high energy, long calendar life, and excellent abuse tolerance such as electric vehicle batteries.

25 ENERGY STORAGE↗

Curiosity driven exploration to optimize structure–property learning in microscopy

Rapidly determining structure–property correlations in materials is an important challenge in better understanding fundamental mechanisms and greatly assists in materials design. In microscopy, imaging data provides a direct measurement of the local structure, while spectroscopic measurements provide relevant functional property information. Deep kernel active learning approaches have been utilized to rapidly map local structure to functional properties in microscopy experiments, but are computationally expensive for multi-dimensional and correlated output spaces. Here, we present an alternative lightweight curiosity algorithm which actively samples regions with unexplored structure–property relations, utilizing a deep-learning based surrogate model for error prediction. We show that the algorithm outperforms random sampling for predicting properties from structures, and provides a convenient tool for efficient mapping of structure–property relationships in materials science.

36 MATERIALS SCIENCE↗

How Certain Physical Considerations Impact Aerostructural Wing Optimization

Wing design optimization has been studied extensively and is of continued interest as optimization tools are developed and become more accessible. In each of these studies, certain assumptions and simplifications are made to make the design problem tractable. However, it is difficult to find systematic studies in which several considerations are added or removed one at a time to study how much impact they have. In this work, we examine how certain physical considerations (viscous drag, wave drag, thrust loads, and inertial relief from structural, fuel, and engine masses), impact the aerostructural optimization results for three distinct aircraft wings. The goal is to help develop a rough idea of how important these physical considerations are. We do this using gradient-based optimization and a multidisciplinary design optimization framework, OpenMDAO. We use the open-source tool OpenAeroStruct that couples a vortex lattice method to a finite element method. We establish a baseline aerostructural design optimization problem then perform a series of optimizations, each with one physical consideration removed from the baseline case. We find that depending on the size of the aircraft and flight conditions, the importance of some of these physical considerations varies considerably whereas the importance of others do not. Specifically, the optimal designs change radically without proper viscous and wave drag considerations and smaller aircraft with more distributed propulsion are more affected by the inclusion of engine loads.

Aeropropulsion↗

A deep learning and finite element approach for exploration of inverse structure–property designs of lightweight hybrid composites

Hybrid composites have important applications, such as high-performance and lightweight materials in aerospace and automotive industries. Hybrid composites utilize the synergy of diverse fillers to achieve desired material properties, but usually have more complicated microstructures. While topology optimization can optimize a particular property, designing hybrid composites for customized mechanical performances, e.g. full-range stress–strain curve, remains challenging. Here, a computational framework that integrated finite element analysis (FEA) and artificial intelligence (AI) methods of Conditional Generative Adversarial Networks (cGAN) deep learning and transfer learning was developed to establish inverse structure–property relationships and design tailor-made hybrid composites. Based on FEA-generated datasets of hybrid fiber-particle–matrix microstructures and their corresponding full-range stress–strain curves, a cGAN architecture was trained to generate tailored microstructures and establish structure–property relationships. Similarity in microstructural features and well-matched stress–strain curves based on the AI-generated composites were achieved. In conclusion, transfer learning was used to expand the pre-trained model for designing different materials systems.

Hybrid composites↗

Neural network accelerator for quantum control

Efficient quantum control is necessary for practical quantum computing implementations with current technologies. Conventional algorithms for determining optimal control parameters are computationally expensive, largely excluding them from use outside of the simulation. Existing hardware solutions structured as lookup tables are imprecise and costly. By designing a machine learning model to approximate the results of traditional tools, a more efficient method can be produced. Such a model can then be synthesized into a hardware accelerator for use in quantum systems. In this study, we demonstrate a machine learning algorithm for predicting optimal pulse parameters. This algorithm is lightweight enough to fit on a low-resource FPGA and perform inference with a latency of 175 ns and pipeline interval of 5 ns with > 0.99 gate fidelity. In the long term, such an accelerator could be used near quantum computing hardware where traditional computers cannot operate, enabling quantum control at a reasonable cost at low latencies without incurring large data bandwidths outside of the cryogenic environment.

43 PARTICLE ACCELERATORS↗

Future Homes in Space: Development of Concepts for Exploration Space Habitats

NASA’s Artemis campaign seeks to return humans to the moon and establish a sustained presence on the lunar surface. This session will emphasize how habitation capabilities on the moon and in cislunar space can potentially contribute to the sustainability objectives of Artemis. Habitable elements represent opportunities to enable longer duration stays, increase the number of crew members present, enhance science and utilization activities, drive technology development for future Mars exploration, perform analog missions, and fuel economic opportunities for US industry. Panelists include Paul Kessler (NASA Marshall Space Flight Center, deputy lead for lunar surface habitation); Andrew Choate (NASA Marshall Space Flight Center, Mars habitation lead); Krystofer Dudzinski (NASA Marshall Space Flight Center, a space architect within the MSFC Advanced Concepts Office); and Larry Toups (retired from NASA Johnson Space Center, currently an adjunct professor at University of Houston in space architecture). The panel is moderated by Tracie Prater (NASA Marshall Space Flight Center, Habitation Systems Development Office). The panel will begin with an overview of the history of habitation concepts and an academic perspective on general considerations in space habitat design (Larry Toups). Paul Kessler and Andrew Choate will introduce NASA’s principle of “architecting from the right” to help define objectives for Artemis missions, needs/characteristics, use cases, and functions (as published in the agency’s Architecture Definition Document) and provide perspective on how this principle informs habitation concept development work. NASA panelists will discuss key engineering challenges identified for developing, deploying, and operating habitable assets on the lunar surface and/or in deep space. These may include dust mitigation, outfitting of inflatable softgoods (for concepts which may use softgoods as a primary structural material), survival in lunar darkness, human health and performance considerations, maintenance/repair/sparing, and autonomy. These identified challenges represent risks for habitation systems development and relate closely to capability gaps identified by the agency. While the work of NASA Marshall Space Flight Center’s habitation development office is primarily focused on habitats which are launched from earth pre-integrated (referred to as Class I in the framework previously developed by NASA space architects Kennedy/Cohen) or launched from earth and deployed at the point of use (Class II), there is also extensive work in NASA, academia, and companies on constructed habitats, which would be built on a planetary surface using indigenous resources (Class III habitats). Panelist Krystopher Dudzinski will discuss potential evolutionary pathways from Class I and Class II habitats to Class III habitats, unique and common architectural challenges within each habitat class, and key gaps in implementing Class III habitats from an architectural perspective. NASA panelists and the moderator will also provide an overview of partnership opportunities and avenues for further engagement to advance habitation systems for the SpaceCom audience. NASA is currently developing notional concepts for a lunar surface habitat and Mars transit habitat, which will be discussed during this panel session and used as examples. These concepts represent options for habitation system design and are a point of departure. They do not represent a final plan or formal recommendation on the part of the agency. Based on the most recent analysis cycle, NASA’s lunar surface habitat (SH) concept nominally supports two crew members for 30 days, with the capacity to support four crew during a surge period where crew will swap between the SH and another surface asset, such as a pressurized rover. This example design has a metallic airlock for ingress/egress and the upper portion is an inflatable material system which serves as the habitation module. The notional interior of the habitat is a three-deck layout/configuration which supports all crew mission functions, including exercise, stowage, extravehicular activity (EVA), sleep, hygiene waste collection, maintenance and repair, and meal preparation. Under analysis assumptions for habitation, the Mars Transit Habitat (TH) concept would support four crew on an up to 1,200 day Mars mission. One option for the concept is to initially dock Transit Habitat at Gateway, where it can be used to increase the duration of crew stays in cislunar space and perform shakedown and analog missions prior to a Mars departure. One challenge in longer duration missions which involve both surface exploration and transit is understanding crew adaptation when transitioning between partial gravity and microgravity environments. TH at Gateway offers an opportunity to study this transition and in doing so reduce risks associated with future Mars exploration. Like lunar SH, the most recent analysis cycle concept of a Mars TH is a hybrid structure design, with a metallic section supporting EVAs, axial/radial docking, and Safe Haven capabilities, and an inflatable softgoods structure for the primary habitation function. Interior layouts to optimize crew usability and livability are currently under trade. The panel will include presentation material, but also seeks to engage the audience in a highly interactive conversation regarding the potential role for habitation in future exploration initiatives. Potential topics for discussion include the influence of the crew experience on habitation systems design and livability/usability considerations, the benefits of space habitation development in terrestrial applications, and challenges and opportunities in “feeding forward” lunar surface habitation systems development to Mars exploration.

space habitats↗

Optimization of the moderators in the STS preliminary design

This report details the results for an optimization of the dimensions of the moderators in the preliminary design of the Spallation Neutron Source Second Target Station (STS). This study uses the optimization algorithms of Dakota and an unstructured mesh model for the moderators in MCNP. More details on the unstructured mesh model and the automated mesh generation can be found in [3]. Parallel to this effort, the same moderator geometries have been optimized using a constructive solid geometry (CSG) MCNP model. More details on this model and its results can be found in [4]. Three optimal designs are selected for each moderator: one that is optimized for maximum peak brightness, one for maximum time-integrated brightness, and one for a combination of peak and time-integrated brightness. The backbone of the optimization work flow is provided by Dakota. For each set of design parameters requested by Dakota, a new solid geometry is automatically built in Creo and SpaceClaim, and subsequently exported to Attila4MC to generate an unstructured mesh geometry for MCNP. After the MCNP calculation is finished, the objective function (e.g., brightness metric) is returned to Dakota. After the new design has been evaluated, a result-file is written, and Dakota proposes the next set of design parameters to be evaluated. The loop continues until a specified convergence criterion has been met. The design parameters of the cylindrical (upper) moderator include the hydrogen radius, the premoderator thickness (top, bottom, radial), the beryllium radius and the horizontal position of the moderator. The crucial design choice is the hydrogen radius. A radius of 62 mm is shown to provide the maximum time-integrated brightness. The maximum peak brightness occurs with a radius of 40 mm. A combined (middle) design, which balances peak and time-integrated brightnesses, is obtained with a hydrogen radius of 50 mm. The premoderator thicknesses and the beryllium radius are slightly larger in the design optimized for time-integrated brightness than in the design optimized for peak brightness. The sensitivity to these two parameters is relatively small close to the optimal configurations. The hydrogen vessel and vacuum vessel wall thicknesses are dependent on the radius of the liquid hydrogen due to structural integrity requirements. The increased wall thicknesses for larger vessels significantly penalize the time-integrated brightness, with the maximum obtainable value reduced by more than 10% relative to earlier studies which used fixed vessel wall thicknesses. The impact of the variable wall thicknesses is much less for the peak brightness and combined brightness designs. The design parameters of the tube (lower) moderator selected for the optimization are the tube length, the annular premoderator thickness, the beryllium radius and the horizontal position of the moderator. The tube length is the crucial parameter and is chosen large (210 mm) and small (125 mm) in the designs optimized for time-integrated and peak brightness respectively. A combined optimal design has a tube length of 170 mm. The premoderator thickness and the beryllium radius are chosen larger in the design optimized for time-integrated brightness.

42 ENGINEERING↗

On the cogent formulation of an elastomeric silicone ink material for direct ink write ( DIW ) 3D printing

Abstract Adhesives and sealants show fine rheology with good physical and mechanical properties as viscous pastes, a possible starting point for developing direct ink writing (DIW) 3D printing ink. However, many commercial adhesives and sealants take days or weeks to cure fully. DIW 3D‐printed parts made directly from these sealants are not designed for a scalable manufacturing process and high‐volume production. Moreover, most of these adhesives and sealants have volume shrinkage during cure. A systematic understanding of formulation methods and design principles for an elastomeric silicone DIW ink can overcome these issues. This study presents the cogent formulation development of a 3D printable thermoset elastomer silicone that gels and cures isotropically in minutes, reducing cycle time for rapid ink development with no shrinkage during cure. More specifically, we outline the principles of raw material selection of a formulation to achieve excellent rheology, printability, synchronized working, and gel time fitting requirements closer to scalable manufacturing. The reaction kinetics and their corresponding 3D‐printed structural properties are also described. Interest in future work is toward a rational DIW 3D printing ink material development protocol and use of machine learning (ML). Highlights Formulation method flexibility and design principle of DIW ink. Raw material selection principle to achieve optimal rheology for DIW printing. Ink gel kinetics for large‐scale DIW manufacturing. Hydrosilylation conversion over time at different ambient temperatures. Structural properties of DIW 3D printed parts.

36 MATERIALS SCIENCE↗

OPTICON: Pro-Matlab software for large order controlled structure design

A software package for large order controlled structure design is described and demonstrated. The primary program, called OPTICAN, uses both Pro-Matlab M-file routines and selected compiled FORTRAN routines linked into the Pro-Matlab structure. The program accepts structural model information in the form of state-space matrices and performs three basic design functions on the model: (1) open loop analyses; (2) closed loop reduced order controller synthesis; and (3) closed loop stability and performance assessment. The current controller synthesis methods which were implemented in this software are based on the Generalized Linear Quadratic Gaussian theory of Bernstein. In particular, a reduced order Optimal Projection synthesis algorithm based on a homotopy solution method was successfully applied to an experimental truss structure using a 58-state dynamic model. These results are presented and discussed. Current plans to expand the practical size of the design model to several hundred states and the intention to interface Pro-Matlab to a supercomputing environment are discussed.

Peterson, Lee D.↗

Multidisciplinary Multiobjective Optimal Design for Turbomachinery Using Evolutionary Algorithm

This report summarizes Dr. Lian s efforts toward developing a robust and efficient tool for multidisciplinary and multi-objective optimal design for turbomachinery using evolutionary algorithms. This work consisted of two stages. The first stage (from July 2003 to June 2004) Dr. Lian focused on building essential capabilities required for the project. More specifically, Dr. Lian worked on two subjects: an enhanced genetic algorithm (GA) and an integrated optimization system with a GA and a surrogate model. The second stage (from July 2004 to February 2005) Dr. Lian formulated aerodynamic optimization and structural optimization into a multi-objective optimization problem and performed multidisciplinary and multi-objective optimizations on a transonic compressor blade based on the proposed model. Dr. Lian s numerical results showed that the proposed approach can effectively reduce the blade weight and increase the stage pressure ratio in an efficient manner. In addition, the new design was structurally safer than the original design. Five conference papers and three journal papers were published on this topic by Dr. Lian.

Source record↗

Composite panel development at JPL

Parametric computer studies can be use in a cost effective manner to determine optimized composite mirror panel designs. An InterDisciplinary computer Model (IDM) was created to aid in the development of high precision reflector panels for LDR. The materials properties, thermal responses, structural geometries, and radio/optical precision are synergistically analyzed for specific panel designs. Promising panels designs are fabricated and tested so that comparison with panel test results can be used to verify performance prediction models and accommodate design refinement. The iterative approach of computer design and model refinement with performance testing and materials optimization has shown good results for LDR panels.

Mcelroy, Paul↗

Optimal Design and Techno-Economic Analysis of 3D-Printed, Intensified Packings for Absorbers and Strippers in Solvent-Based CO 2 Capture

A potential technology for the CO 2 absorption process is utilizing intensified structured packing with embedded cooling/heating channels for continuous heat exchange, which can overcome limitations of discrete methods, such as discrete intercooling and centralized reboilers, to aid in reducing energy consumption and decreasing costs. This work investigates the modeling of intensified packing (IP) for the stripper tower, extending on previous work for the absorber, which distributes heat internally within the column, improving the thermodynamics for the solvent regeneration process. The model includes submodels for steam turbine extraction to produce steam at various qualities as well as a surrogate model for calculating steam enthalpy. A cost model for a plant-scale absorption capture process was developed, allowing for the design of the plant to be optimized, subject to minimizing capture cost using two different power plant flue gas sources. In this optimization, the placement of IP in both towers is optimized to balance the trade-off between enhanced heat transfer and reduced mass transfer volume. For natural gas combined cycle flue gas, the standard process configuration had a minimum cost of $\$$65.40/tonne CO 2 , and considering IP, the minimum capture cost is reduced to $\$$62.73/tonne, with utilization in the stripper column, which reduces yearly costs by up to $\$$2.67 MM/yr. Cooling the absorber through IP, or intercoolers, was only found to be beneficial at higher capture rates, with IP in both towers having a cost of capture of $\$$68.08/tonne at 99.9% capture, a reduction of $\$$12.64/tonne when using only intercoolers at the same capture rate. When capturing from pulverized-coal power plants, the minimum cost of capture when using IP in both towers is $\$$44.18/tonne (at 97% capture), while the standard configuration with and without intercoolers was $\$$45.69 and $\$$47.22 per tonne, respectively. This results in a reduction in yearly costs of $\$$16.98 MM/yr from the base-case configuration. At this higher CO 2 concentration, cooling in the absorber from the IP becomes extremely beneficial, reducing energy consumption by up to 6%.

20 FOSSIL-FUELED POWER PLANTS↗

Modified independent modal space control method for active control of flexible systems

A modified independent modal space control (MIMSC) method is developed for designing active vibration control systems for large flexible structures. The method accounts for the interaction between the controlled and residual modes. It incorporates also optimal placement procedures for selecting the optimal locations of the actuators in the structure in order to minimize the structural vibrations as well as the actuation energy. The MIMSC method relies on an important feature which is based on time sharing of a small number of actuators, in the modal space, to control effectively a large number of modes. Numerical examples are presented to illustrate the application of the method to generic flexible systems. The results obtained suggest the potential of the devised method in designing efficient active control systems for large flexible structures.

Baz, A.↗

Modified independent modal space control method for active control of flexible systems

A modified independent modal space control (MIMSC) method is developed for designing active vibration control systems for large flexible structures. The method accounts for the interaction between the controlled and residual modes. It incorporates also optimal placement procedures for selecting the optimal locations of the actuators in the structure in order to minimize the structural vibrations as well as the actuation energy. The MIMSC method relies on an important feature which is based on time sharing of a small number of actuators, in the modal space, to control effectively a large number of modes. Numerical examples are presented to illustrate the application of the method to generic flexible systems. The results obtained suggest the potential of the devised method in designing efficient active control systems for large flexible structures.

Baz, A.↗

Modified independent modal space control method for active control of flexible systems

A modified independent modal space control (MIMSC) method is developed for designing active vibration control systems for large flexible structures. The method accounts for the interaction between the controlled and residual modes. It incorporates also optimal placement procedures for selecting the optimal locations of the actuators in the structure in order to minimize the structural vibrations as well as the actuation energy. The MIMSC method relies on an important feature which is based on time sharing of a small number of actuators, in the modal space, to control effectively a large number of modes. Numerical examples are presented to illustrate the application of the method to generic flexible systems. The results obtained suggest the potential of the devised method in designing efficient active control systems for large flexible structures.

Baz, A.↗

Design Optimization of Stiffened Panels with Postbuckling Constraints

The funding provided by the grant is used to complete the final stages of the development of a geometrically nonlinear analysis and design capability for the static response of compressively loaded prismatic plate structures. The analysis is based on the nonlinear finite strip method and is applicable for structures, such as stiffened panels or box columns, that can be modeled as assemblages of finite length plate strips. In an effort to reduce the computational cost of the nonlinear finite strip method, thus making it suitable for use in the design optimization environment, reduced basis techniques as described in various references by Noor are used in conjunction with the finite strip method. In addition, an efficient scheme for tracing the nonlinear equilibrium paths through highly nonlinear response curves was implemented. The new scheme, which is referred to as the normal flow algorithm, is based on homotopy methods, and is capable of negotiating highly nonlinear limit point instabilities with a reduced computational cost compared to the popular Ricks/Wempner and Chrisfield algorithms.

Guerdal, Zafer↗

Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows

Synthetic polymers are highly customizable with tailored structures and functionality, yet this versatility generates challenges in the design of advanced materials due to the size and complexity of the design space. Thus, exploration and optimization of polymer properties using combinatorial libraries has become increasingly common, which requires careful selection of synthetic strategies, characterization techniques, and rapid processing workflows to obtain fundamental principles from these large data sets. Herein, we provide guidelines for strategic design of macromolecule libraries and workflows to efficiently navigate these high-dimensional design spaces. We describe synthetic methods for multiple library sizes and structures as well as characterization methods to rapidly generate data sets, including tools that can be adapted from biological workflows. We further highlight relevant insights from statistics and machine learning to aid in data featurization, representation, and analysis. This Perspective acts as a “user guide” for researchers interested in leveraging high-throughput screening toward the design of multifunctional polymers and predictive modeling of structure–property relationships in soft materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Distinguishing photo-induced oxygen attack on alkyl chain versus conjugated backbone for alkylthienyl-benzodithiophene (BDTT)-based push–pull polymers

Synthetic design has enabled increasing power conversion efficiency advances in organic photovoltaics (OPV). One continuing knowledge gap is detailed understanding of single-material chemical (photo)stability. Many considerations are based on prior OPV-relevant donor homopolymer systems rather than the next-generation push–pull architectures. Generally, energetic offsets between the lowest occupied molecular orbital of the donor and molecular oxygen are assumed to dictate kinetics of photo-induced charge transfer to a super oxide radical. Herein we determine the ambient-induced photo-degradation pathways, presented as proposed site-specific arrow-pushing mechanisms, for five donor polymers all containing the same push unit – alkylthienyl-substituted-benzodithiophene (BDTT) – but with chemically distinct pull units. The donor-only polymer films were subject to controlled photobleaching in air as an accelerated degradation approach, coupled with simultaneous monitoring of absorptance. Sample subsets were periodically removed and analyzed with X-ray photoelectron spectroscopy, to evaluate near-surface chemical composition and oxygen additions to hetero reporter atoms on either the BDTT push unit or distinct pull unit (i.e., sulphur and nitrogen). Here, this methodology allows us to distinguish between different mechanisms of bond cleavage and formation. Overall, we find that neither polymer redox properties nor individual push or pull unit stability are sufficient to predict photo-oxidative degradation of these polymers. Rather, there is a greater dependence on the susceptibility of unique structural groups within a polymeric system. Alkyl chain oxygen addition is generally the first attack site and direct sulfur oxidation on the conjugated backbone occurs after saturation of the alkyl chain initiation sites. This work provides a standard that could be used to evaluate relative photo-oxidative (in)stability for new OPV materials quickly – prior to time-consuming device optimization – and demonstrates an effective methodology for correlating optical degradation with chemical structure alterations via spectroscopic signatures to guide synthetic design.

14 SOLAR ENERGY↗