Electrode optimization for efficient hydrogen production using an SO2-depolarized electrolysis cell
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Colón-Mercado, Héctor R. (ORCID:0000000192815976)↗
SEARCH · Engineering Papers
Results for “optimality”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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A GPU-based Approach for Path Planning Optimization via Travel Length Reduction
Typically, before constructing an object with an additive manufacturing system, the 3D object must be sent through a process called slicing. Slicing converts a 3D object commonly in the form of an STL file into a set of layers by horizontally intersecting a plane with the object at various heights. At each height, called a layer, multiple 2D polygons can be generated. Each polygon represents a boundary for solid geometry and is called an island. Each island is then comprised of multiple path types in an attempt to optimally fill the polygon. To move between each island and each islands’ paths, travels are inserted. Travels are simply motion by the system to move from one area of construction to another. Travels do not contribute to the construction of the object, and so, are considered wasted motion. In large-scale additive manufacturing, objects can be quite large and the distance between islands can be large as well. As a result, these travels can waste a significant amount of time. Ideally, travels would be as short as possible, however, computing global minimal travel paths is computationally expensive. To combat this problem, researchers at Oak Ridge National Lab developed a GPU-based approach to travel insertion based on a unique factoradic representation. This representation was then utilized by the GPU to solve the Traveling Salesman Problem (TSP). This algorithm was able to compute global minimal travel paths quickly resulting in faster object construction. A general investigation was also carried out to determine when a GPU vs CPU implementation would be beneficial.
Borish, Michael↗
Pareto Optimization of Oligomer Polarizability and Dipole Moment Using a Genetic Algorithm
High-performance electronic components are highly sought after in order to produce increasingly smaller and cheaper electronic devices. Drawing inspiration from inorganic dielectric materials, in which both polarizability and polarization contribute, organic materials can also maximize both. For a large set of small molecules drawn from PubChem, a Pareto-like front appears between the polarizability and dipole moment, indicating the presence of an apparent trade-off between these two properties. We tested this balance in π-conjugated materials by searching for novel conjugated hexamers with simultaneously large polar- izabilities and dipole moments with potential use for dielectric materials. Using a genetic algorithm (GA) screening technique in conjunction with an approximate density functional tight-binding method for property calculations, we were able to efficiently search chemical space for optimal hexamers. Given the scope of chemical space, using the GA technique saves considerable time and resources by speeding up molecular searches compared to a systematic search. Here, we also explored the underlying structure–function relationships, including sequence and monomer properties, that characterize large polarizability and dipole moment regimes.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Optimized Microwave-Based Synthesis of Thermally Stable Inverse Catalytic Core-shell Motifs for CO2 Hydrogenation
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99 GENERAL AND MISCELLANEOUS↗
Tuning the Solvation Structure in Aqueous Zinc Batteries to Maximize Zn-Ion Intercalation and Optimize Dendrite-Free Zinc Plating
Aqueous zinc batteries are recognized to suffer from H + /Zn 2+ coinsertion in the cathode, but few approaches have been reported to suppress deleterious H + intercalation. We realize this goal by tuning the solvation structure, using LiV 2 (PO 4 ) 3 (LVP) as a model cathode. Phase conversion of LVP induced by H + intercalation is observed in 4 m Zn(OTf) 2 , whereas dominant Zn 2+ insertion is confirmed in a ZnCl 2 water-in-salt electrolyte (WiSE). This disparity is ascribed to the complete absence of free water and a strong Zn 2+ –H 2 O interaction in the latter that interrupts the H 2 O hydrogen bonding network, thus suppressing H + intercalation. On the basis of this strategy, a novel PEG-based hybrid electrolyte is designed to replace the corrosive ZnCl2 WiSE. This system exhibits an optimized Zn 2+ solvation sheath with a similar low free water content, showing not only much better suppression of H + intercalation but also highly reversible Zn plating/stripping with a CE of ~99.7% over 150 cycles.
25 ENERGY STORAGE↗
Optimized CRISPR Interference System for Investigating Pseudomonas alloputida Genes Involved in Rhizosphere Microbiome Assembly
Pseudomonas alloputida KT2440 (formerly P. putida) has become both a well-known chassis organism for synthetic biology and a model organism for rhizosphere colonization. Here, we describe a CRISPR interference (CRISPRi) system in KT2440 for exploring microbe–microbe interactions in the rhizosphere and for use in industrial systems. Our CRISPRi system features three different promoter systems (XylS/P m , LacI/P lac , and AraC/P BAD ) and a dCas9 codon-optimized for Pseudomonads, all located on a mini-Tn7-based transposon that inserts into a neutral site in the genome. It also includes a suite of pSEVA-derived sgRNA expression vectors, where the expression is driven by synthetic promoters varying in strength. We compare the three promoter systems in terms of how well they can precisely modulate gene expression, and we discuss the impact of environmental factors, such as media choice, on the success of CRISPRi. We demonstrate that CRISPRi is functional in bacteria colonizing the rhizosphere, with repression of essential genes leading to a 10–100-fold reduction in P. alloputida cells per root. Finally, we show that CRISPRi can be used to modulate microbe–microbe interactions. When the gene pvdH is repressed and P. alloputida is unable to produce pyoverdine, it loses its ability to inhibit other microbes in vitro. Furthermore, our design is amendable for future CRISPRi-seq studies and in multispecies microbial communities, with the different promoter systems providing a means to control the level of gene expression in many different environments.
Bacteria↗
Splitting Mono- and Di-Branched Alkane Isomers by a Robust Aluminum-Based Metal-Organic Framework Material with Optimal Pore Dimensions
The separation of alkanes with different degrees of branching, particularly mono- and dibranched isomers, represents a challenging yet important industrial process for the production of premium gasoline blending components with high octane number. We report here the separation of linear/monobranched and dibranched alkanes through complete molecular sieving by a robust aluminum-based MOF material, Al-bttotb (H 3 bttotb = 4,4',4"-(benzene-1,3,5-triyltris(oxy))tribenzoicacid). Single- and multicomponent adsorption experiments reveal that the material adsorbs linear and monobranched alkanes, but fully excludes their dibranched isomers. Adsorption sites of alkanes within the MOF channels have been identified by single-crystal X-ray diffraction studies, and the adsorption mechanism was explored through computational calculations and modeling. The highly selective adsorption of the MOF should be attributed to its optimal pore dimensions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Optimal stomatal behaviour around the world
Stomatal conductance (g s ) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of g s in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of g s that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed g s obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model 1 and the leaf and wood economics spectrum 2,3 . We also demonstrate a global relationship with climate. In conclusion, these findings provide a robust theoretical framework for understanding and predicting the behaviour of g s across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.
54 ENVIRONMENTAL SCIENCES↗
Optimal renormalization of multiscale systems
While model order reduction is a promising approach in dealing with multi-scale time-dependent systems that are too large or too expensive to simulate for long times, the resulting reduced order models can suffer from instabilities. We have recently developed a time-dependent renormalization approach to stabilize such reduced models. In the current work, we extend this framework by introducing a parameter that controls the time-decay of the memory of such models and optimally selecting this parameter based on limited fully resolved simulations. First, we demonstrate our framework on the inviscid Burgers equation whose solution develops a finite-time singularity. Our renormalized reduced order models are stable and accurate for long times while using for their calibration only data from a full order simulation before the occurrence of the singularity. Furthermore, we apply this framework to the 3D Euler equations of incompressible fluid flow, where the problem of finite-time singularity formation is still open and where brute force simulation is only feasible for short times. Our approach allows us to obtain for the first time a perturbatively renormalizable model which is stable for long times and includes all the complex effects present in the 3D Euler dynamics. We find that, in each application, the renormalization coefficients display algebraic decay with increasing resolution, and that the parameter which controls the time-decay of the memory is problem-dependent.
Price, Jacob↗
Excited meson radiative transitions from lattice QCD using variationally optimized operators
Not Available
Shultz, Christian J.↗
Towards Efficient Alternating Current Optimal Power Flow Analysis on Graphical Processing Units
We present a solution of sparse ACOPF analysis on GPU. In particular, we discuss the performance bottlenecks and detail our efforts to accelerate the linear solver, a core component of ACOPF that dominates the computational time. ACOPF solutions of two large-scale systems, synthetic Northeast (25,000 buses) and Eastern (70,000 buses) \cite{birchfield2017tamu-cases} on GPU show promising speed-up compared to CPU based solution using a state-of-the-art solver. To our knowledge, this is the first result demonstrating acceleration of sparse ACOPF on GPUs.
Power grid analysis, GPU↗
Optimization of Transition Edge Sensor Arrays for Cosmic Microwave Background Observations With the South Pole Telescope
In this paper, we describe the optimization of transition-edge-sensor (TES) detector arrays for the third-generation camera for the South PoleTelescope. The camera, which contains similar to 16 000 detectors, will make high-angular-resolution maps of the temperature and polarization of the cosmic microwave background. Our key results are scatter in the transition temperature of Ti/Au TESs is reduced by fabricating the TESs on a thin Ti(5 nm)/Au(5 nm) buffer layer and the thermal conductivity of the legs that support our detector islands is dominated by the SiOx dielectric in the microstrip transmission lines that run along the legs.
Ding, Junjia↗
Test of CP invariance in vector-boson fusion production of the Higgs boson using the Optimal Observable method in the ditau decay channel with the ATLAS detector
N/A
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Optimizing Energy For Delivery Drones - A Comprehensive Tool Set For Drone Energy Calculation And Drone Fleet Optimization
This tool is intended to be deployed for potential customers to compare the energy profiles across various drone types/classes. The primary factors considered were design of the drone, the weight of the drone, the weight of the payload, and how the drone is flown. It has energy comparison metrics like "Drone (A) vs Drone (B) ", "Drone vs Ground Vehicle", "Drone Energy from delivery via landing versus hovering". It also includes the ability to determine the number of drones and batteries needed to optimally deliver goods from a chosen location to a set of destinations.
Mendadhala, Rohit [Idaho National Laboratory (INL)↗
Information transfer as a framework for optimized phase imaging
In order to efficiently image a non-absorbing sample (a phase object), dedicated phase contrast optics are required. Typically, these optics are designed with the assumption that the sample is weakly scattering, implying a linear relation between a sample’s phase and its transmission function. In the strongly scattering, nonlinear case, the standard optics are ineffective, and the transfer functions used to characterize them are uninformative. We use the Fisher information (FI) to assess the efficiency of various phase imaging schemes and to calculate an information transfer function (ITF). We show that a generalized version of Zernike phase contrast is efficient given sufficient prior knowledge of the sample. We show that with no prior knowledge, a random sensing measurement yields a significant fraction of the available information. Finally, we introduce a generalized approach to common path interferometry that can be optimized to prioritize sensitivity to particular sample features. Each of these measurements can be performed using Fourier lenses and phase masks.
Koppell, Stewart↗
Transport Studies Enabling Efficiency Optimization of Cost-Competitive Fuel Cell Stacks (aka AURORA: Areal Use and Reactant Optimization at Rated Amperage)
Hydrogen fuel cells are recognized as one of the most viable solutions for mobility in the 21st century; however, there are technical challenges that must be addressed before the technology can become available for mass production. One of the most demanding aspects is the costs of present-day fuel cells which are prohibitively high for the majority of envisioned markets. The fuel cell community recognizes two major drivers to an effective cost reduction: (1) decreasing the noble metals content, and (2) increasing the power density in order to reduce the number of cells needed to achieve a specified power level. To date, the majority of development work aimed at increasing the value metric (i.e. W/mg-Pt) has focused on the reduction of precious metal loadings, and this important work continues. Efforts to increase power density have been limited by two main factors: (1) performance limitations associated with mass transport barriers, and (2) the historical prioritization of efficiency over cost. This program is driven by commercialization imperatives, and challenges both of these factors. The premise of this Program, supported by proprietary cost modeling by Nuvera, is that DOE 2015 cost targets can be met by simultaneously exceeding DOE 2015 targets for Platinum loadings (using materials with less than 0.2 mg-Pt/cm 2 ) and MEA power density (operating at higher than 1.0 Watt/cm 2 ). The approach of this program is to combine Nuvera’s stack technology, which has demonstrated the ability to operate stably at high current densities (> 1.5 A/cm 2 ), with low Platinum loading MEAs developed by Johnson Matthey in order to maximize Pt specific power density and reduce stack cost. A predictive performance model developed by PSU/UTK is central to the program allowing the team to study the physics and optimize materials/conditions specific to low Pt loading electrodes and ultra-high current density and operation.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗