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At least 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Case Study of LLVM-Based Analysis for Optimizing SIMD Code Generation

This paper presents a methodology for using LLVM-based tools to tune the DCA++ (dynamical cluster approximation) application that targets the new ARM A64FX processor. The goal is to describe the changes required for the new architecture and generate efficient single instruction/multiple data (SIMD) instructions that target the new Scalable Vector Extension instruction set. During manual tuning, the authors used the LLVM tools to improve code parallelization by using OpenMP SIMD, refactored the code and applied transformation that enabled SIMD optimizations, and ensured that the correct libraries were used to achieve optimal performance. By applying these code changes, code speed was increased by 1.98× and 78 GFlops were achieved on the A64FX processor. The authors aim to automatize parts of the efforts in the OpenMP Advisor tool, which is built on top of existing and newly introduced LLVM tooling.

Huber, Joseph↗
DOE OSTI2014

Tunable water desalination across Graphene Oxide Framework membranes

The performance of graphene oxide framework (GOF) membranes for water desalination is assessed using classical molecular dynamics (MD) simulations. The coupling between water permeability and salt rejection GOF membranes is studied as a function of linker concentration n, thickness h and applied pressure DP. The simulations reveal that water permeability in GOF-(n,h) membranes can be tuned from 5 (n = 32 and h = 6.5 nm) to 400 L/cm2/day/MPa (n = 64 and h = 2.5 nm) and follows the law Cnh an . For a given pore size (n = 16 or 32), water permeability of GOF membranes increases when the pore spacing decreases, whereas for a given pore spacing (n = 32 or 64), water permeability increases by up to two orders of magnitude when the pore size increases. Furthermore, for linker concentrations n 32, the high water permeability corresponds to a 100% salt rejection, elevating this type of GOF membrane as an ideal candidate for water desalination. Compared to experimental performance of reverse osmosis membranes, our calculations suggest that under the same conditions of applied pressure and characteristics of membranes (DP 10 MPa and h 100 nm), one can expect a perfect salt rejection coupled to a water permeability two orders of magnitude higher than existing technologies, i.e., from a few cL/cm2/day/MPa to a few L/cm2/day/MPa.

Nicolai, Adrien↗
DOE OSTI2024

Interpretable Machine Learning Models for Practical Antimonate Electrocatalyst Performance

Computationally predicting the performance of catalysts under reaction conditions is a challenging task due to the complexity of catalytic surfaces and their evolution in situ, different reaction paths, and the presence of solid-liquid interfaces in the case of electrochemistry. We demonstrate here how relatively simple machine learning models can be found that enable prediction of experimentally observed onset potentials. Inputs to our model are comprised of data from the oxygen reduction reaction on non-precious transition-metal antimony oxide nanoparticulate catalysts with a combination of experimental conditions and computationally affordable bulk atomic and electronic structural descriptors from density functional theory simulations. From human-interpretable genetic programming models, we identify key experimental descriptors and key supplemental bulk electronic and atomic structural descriptors that govern trends in onset potentials for these oxides and deduce how these descriptors should be tuned to increase onset potentials. Here, we finally validate these machine learning predictions by experimentally confirming that scandium as a dopant in nickel antimony oxide leads to a desired onset potential increase. Macroscopic experimental factors are found to be crucially important descriptors to be considered for models of catalytic performance, highlighting the important role machine learning can play here even in the presence of small datasets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Rapid synthesis of phase-engineered tungsten carbide electrocatalysts via flash joule heating for high-current-density hydrogen evolution

Fabricating durable and high-performance electrocatalysts operating at high current densities for industrial acidic hydrogen evolution remains a daunting challenge. Tailoring the phase composition of electrocatalysts is a promising strategy to harness synergistic effects and improve charge transfer, thereby optimizing their performance. Here, this work presents a fast, green method based on flash joule heating (FJH) to synthesize phase-engineered tungsten carbide electrocatalysts for the acidic hydrogen evolution reaction (HER) at high current densities. Tungsten carbide electrodes with varying FJH treatment durations (3, 10, 30, and 60 s) are fabricated to fine-tune the mixture of tungsten monocarbide (WC) and tungsten semicarbide (W 2 C) phases. Results show that samples with a 30-s treatment (TC-3) exhibit an optimal balance between these phases, leading to a low overpotential of 180.97 and 387 mV at current densities of 10 mA/cm 2 and 4 A/cm 2 , respectively. TC-3 exhibits significantly lower charge transfer resistance compared to the other electrocatalysts, which can be attributed to its optimal phase ratio. Notably, the TC-3 electrocatalyst remains stable for over 9 days at 4 A/cm 2 due to their controlled phases and excellent corrosion-resistant properties. This work highlights a new method to fabricate cost-effective, high-performance tungsten carbide electrocatalysts with well-controlled phase compositions.

Acidic hydrogen evolution reaction↗
DOE OSTI2023

Combining multitask and transfer learning with deep Gaussian processes for autotuning-based performance engineering

We combine deep Gaussian processes (DGPs) with multitask and transfer learning for the performance modeling and optimization of HPC applications. Deep Gaussian processes merge the uncertainty quantification advantage of Gaussian processes (GPs) with the predictive power of deep learning. Multitask and transfer learning allow for improved learning efficiency when several similar tasks are to be learned simultaneously and when previous learned models are sought to help in the learning of new tasks, respectively. A comparison with state-of-the-art autotuners shows the advantage of our approach on two application problems. In this article, we combine DGPs with multitask and transfer learning to allow for both an improved tuning of an application parameters on problems of interest but also the prediction of parameters on any potential problem the application might encounter.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Importance of the tuning of band position in optimizing the electronic coupling and photocatalytic activity of nanocomposite

The electronic coupling and photocatalytic activity of Ag{sub 2}CO{sub 3}–TiO{sub 2} nanocomposite can be optimized by the fine-tuning of the band position of titanium oxide with nitrogen doping. The increase of the valence band energy of TiO{sub 2} by N-doping leads not only to the enhanced absorption of visible light but also to the promoted hole transfer from Ag{sub 2}CO{sub 3} to TiO{sub 2}, resulting in the efficient spatial separation of photogenerated electrons and holes. While the undoped Ag{sub 2}CO{sub 3}–TiO{sub 2} nanocomposite shows an inferior photocatalytic activity to the pure Ag{sub 2}CO{sub 3}, the photocatalyst performance of N-doped nanocomposite is better than those of Ag{sub 2}CO{sub 3} and undoped Ag{sub 2}CO{sub 3}–TiO{sub 2} nanocomposite. This observation underscores a significant enhancement of the photocatalytic activity of nanocomposite upon N-doping, a result of enhanced electronic coupling between the hybridized species. The present results clearly demonstrate the importance of the fine-tuning of band position in optimizing the photocatalytic activity of hybrid-type photocatalysts. - Highlights: • The band position of Ag{sub 2}CO{sub 3}–TiO{sub 2} can be effectively tailored by nitrogen doping. • The N-doping leads to the improvement of charge separation. • The N-doped Ag{sub 2}CO{sub 3}–TiO{sub 2} shows high photocatalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Tuning spin transport properties and molecular magnetoresistance through contact geometry

Molecular spintronics seeks to unite the advantages of using organic molecules as nanoelectronic components, with the benefits of using spin as an additional degree of freedom. For technological applications, an important quantity is the molecular magnetoresistance. In this work, we show that this parameter is very sensitive to the contact geometry. To demonstrate this, we perform ab initio calculations, combining the non-equilibrium Green's function method with density functional theory, on a dithienylethene molecule placed between spin-polarized nickel leads of varying geometries. We find that, in general, the magnetoresistance is significantly higher when the contact is made to sharp tips than to flat surfaces. Interestingly, this holds true for both resonant and tunneling conduction regimes, i.e., when the molecule is in its “closed” and “open” conformations, respectively. We find that changing the lead geometry can increase the magnetoresistance by up to a factor of ∼5. We also introduce a simple model that, despite requiring minimal computational time, can recapture our ab initio results for the behavior of magnetoresistance as a function of bias voltage. This model requires as its input only the density of states on the anchoring atoms, at zero bias voltage. We also find that the non-resonant conductance in the open conformation of the molecule is significantly impacted by the lead geometry. As a result, the ratio of the current in the closed and open conformations can also be tuned by varying the geometry of the leads, and increased by ∼400%.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Strain and localization effects in InGaAs(N) quantum wells: Tuning the magnetic response

We investigated effects of localization and strain on the optical and magneto-optical properties of diluted nitrogen III–V quantum wells theoretically and experimentally. High-resolution x-ray diffraction, photoluminescence (PL), and magneto-PL measurements under high magnetic fields up to 15 T were performed at low temperatures. Bir-Pikus Hamiltonian formalism was used to study the influence of strain, confinement, and localization effects. The circularly polarized magneto-PL was interpreted considering localization aspects in the valence band ground state. An anomalous behavior of the electron-hole pair magnetic shift was observed at low magnetic fields, ascribed to the increase in the exciton reduced mass due to the negative effective mass of the valence band ground state.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite

The analysis of connected data is an increasingly important application in high-performance computing. Such analyses can reveal fraudulent patterns in financial transactions, optimize telecommunications networks, predict information flow in social networks, etc. However, the landscape of graph analytics is highly diverse. Graph algorithms stress processor architectures differently, and no one graph can represent all topologies. Consequently, no single approach or framework is expected to be optimal for all graph analytics problems. To help make sense of this diverse landscape, we evaluated four approaches to graph analytics: GraphBLAS, Galois, BGL17, GraphIt; and compare them against hand-tuned implementations that take advantage of hardware features on our test platform. Graph- BLAS formulates graph analytics as sparse linear algebra. Galois provides syntactic constructs for data parallelism over irregular data structures. BGL17 is a generic C++ template library for implementing graph algorithms. GraphIt provides a domain- specific language to describe and optimize graph algorithms. We use the GAP Benchmark Suite to establish baseline performance and guide the side-by-side evaluation of each framework. GAP consists of 30 tests: six graph analytics algorithms (breadth- first search, single-source shortest path, PageRank, betweenness centrality, connected components, and triangle counting) run on five graphs, each with different topological characteristics (e.g., high diameter, skewed degree distribution, high average degree). High-performance reference implementations are included for each benchmark algorithm. Because a graph can be loaded into memory a number of ways (e.g., flat file on disk, compressed sparse format, data frames, retrieved from SQL or NoSQL databases), our evaluation focused on computational performance rather than I/O. Our results show the relative strengths of each framework.

Graph algorithms, Benchmarking, shared-memory prog↗
DOE OSTI2016

Tuning back contact property via artificial interface dipoles in Si/organic hybrid solar cells

Back contact property plays a key role in the charge collection efficiency of c-Si/poly(3,4-ethylthiophene):poly(styrenesulfonate) hybrid solar cells (Si-HSCs), as an alternative for the high-efficiency and low-cost photovoltaic devices. In this letter, we utilize the water soluble poly (ethylene oxide) (PEO) to modify the Al/Si interface to be an Ohmic contact via interface dipole tuning, decreasing the work function of the Al film. This Ohmic contact improves the electron collection efficiency of the rear electrode, increasing the short circuit current density (J{sub sc}). Furthermore, the interface dipoles make the band bending downward to increase the total barrier height of built-in electric field of the solar cell, enhancing the open circuit voltage (V{sub oc}). The PEO solar cell exhibits an excellent performance, 12.29% power conversion efficiency, a 25.28% increase from the reference solar cell without a PEO interlayer. The simple and water soluble method as a promising alternative is used to develop the interfacial contact quality of the rear electrode for the high photovoltaic performance of Si-HSCs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Conflicting Roles of Coordination Number on Catalytic Performance of Single-Atom Pt Catalysts

Tailoring the coordination number (CN) of metal atoms has been increasingly recognized as one of the strategies to enhance the catalytic performance of single-atom catalysts (SACs). We here present the single-atom Pt loaded onto a semiconductor SiC substrate (Pt 1 /SiC) with a high loading of up to 9.6 wt % and a precise control of its CN from 3 to 5. The CN tuning was enabled by binding organic linkers on the substrate surface and retaining the metal-linker bonds after photoreduction and mild thermal treatment from 80 to 160 °C. At a higher temperature, Pt became coordinated with additional oxygen atoms from the surface Si–OH groups and organic linkers. This resulted in the increase of the CN from 3 for Pt 1 treated at 80 °C to 5 at 160 °C. The Pt 1 /SiCs with varying CNs effectively broke C–Br bonds in the model brominated compounds through both thermocatalysis using H 2 and photocatalysis using H + as the source for strongly reducing atomic hydrogen (H atom ). The thermocatalytic debromination kinetics increased with the decreasing CN. However, photocatalytic debromination kinetics were independent of the CN, contradictory to the prevalent understanding in literature. Furthermore, we attribute the differential CN effects on these two catalytic schemes to the differences in the pathways for the formation of H atom as well as the rate-limiting step of the overall reaction pathways. Our study presents a unique and important example as to how the performance of SACs and the role of CN can significantly vary depending on the catalytic schemes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

History Matching and Prediction of a Polymer Flood Pilot in Heavy Oil Reservoir on Alaska North Slope

The first-ever polymer flood pilot to enhance heavy oil recovery on Alaska North Slope is ongoing. After more than 3 years of polymer injection, significant benefit has been observed from the decrease in water cut from 65% to less than 15% in the project producers. The primary objective of this study is to develop a robust history-matched reservoir simulation model capable of predicting future polymer flood performance. In this work, the reservoir simulation model has been developed based on the geological model and available reservoir and fluid data. In particular, four high transmissibility strips were introduced to connect the injector-producer well pairs, simulating short-circuiting flow behavior that can be explained by viscous fingering and reproducing the water cut history. The strip transmissibilities were manually tuned to improve the history matching results during the waterflooding and polymer flooding periods, respectively. It has been found that higher strip transmissibilities match the sharp water cut increase very well in the waterflooding period. Then the strip transmissibilities need to be reduced with time to match the significant water cut reduction. The viscous fingering effect in the reservoir during waterflooding and the restoration of injection conformance during polymer flooding have been effectively represented. Based on the validated simulation model, numerical simulation tests have been conducted to investigate the oil recovery performance under different development strategies, with consideration for sensitivity to polymer parameter uncertainties. The oil recovery factor with polymer flooding can reach about 39% in 30 years, twice as much as forecasted with continued waterflooding. Besides, the updated reservoir model has been successfully employed to forecast polymer utilization, a valuable parameter to evaluate the pilot test’s economic efficiency. All the investigated development strategies indicate polymer utilization lower than 3.5 lbs/bbl in 30 years, which is less than that of the same polymer used in a polymer pilot in Argentina.

Wang, Xindan↗
DOE OSTI2021

Open-Loop Control of Adjustable Tuned Mass Dampers for Floating Wind Turbine Platforms: Preprint

Floating offshore wind turbines have several advantages over their land-based counterparts, including access to stronger, more consistent winds and proximity to population centers. However, increased costs from the platform have been a challenge inhibiting their widespread adoption. New damping technologies with tunable target frequencies and damping ratios promise a greater degree of control over platform motions, allowing hulls to be designed smaller and reducing the overall cost of the turbines. In this work, a control strategy is proposed for these adjustable tuned mass dampers (TMDs). A frequency-domain model of the system is developed, from which response amplitude operators (RAOs) for the platform's rigid-body modes can be obtained for different natural frequencies and damping ratios of the dampers. Using these RAOs, and JONSWAP spectrums of operational and extreme sea states, the performance of the various damper settings are compared by evaluating the standard deviation of a rigid-body motion of interest (platform pitch or heave). By finding the optimal damper setting for a range of representative design load cases (DLCs), a lookup function is made to return the damper target frequency given the peak period of the sea state. To determine the current sea state, we propose a simple estimator that uses wave measurements (e.g., from a measurement buoy) to determine the peak period and significant wave height. The significant wave height is determined using the statistics of the past 100 seconds of wave elevation information and the peak period is computed using a frequency locked loop. Initial results show that we can use these estimated values to control the TMD natural frequency with an open loop controller. The controlled system is tested in a range of environmental conditions determined by the International Electrotechnical Commission design load cases (DLCs), which include normal and extreme wind and wave models. In these tests, we compare the performance of 4 cases: (1) no TMD, (2) a constant TMD based on the worst case DLC, (3) a controlled TMD based on known wind and wave environments, and (4) a real-time controlled TMD using estimated wind and wave environments. The effect of hull-based TMD control is also compared to changes in traditional wind turbine control via blade pitch.

control↗
DOE OSTI2025

Dual aggregation steering in bulk-heterojunction via solvent engineering toward efficient and stable binary organic solar cells

In high-performance organic solar cells (OSCs), efficient charge transport hinges on a well-optimized morphology of the photoactive layer, which depends critically on controlled aggregation and favorable interactions between donor and acceptor materials. In this work, we introduce a cascade solvent system comprising high-boiling-point ethylbenzene (EB) and low-boiling-point chloroform (CF) to finely tune the aggregation behavior of the D18 donor and L8-BO acceptor. The incorporation of EB not only promotes the H-aggregation of D18 and the J-aggregation of L8-BO but also facilitates the formation of ideal nanoscale phase separation, thereby suppressing bimolecular recombination. As a result, devices processed with the EB/CF solvent blend achieve a best power conversion efficiency (PCE) of 19.6 % and enhanced operational stability, outperforming those fabricated with pure CF (17.1 %). In conclusion, this study offers a reliable and effective strategy for optimizing donor and acceptor aggregation, providing a viable pathway toward higher-performance OSCs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Stabilizing dynamic subsea power cables using Bi-stable nonlinear energy sinks

This study investigates vibration mitigation of dynamic subsea cables through passive bi-stable nonlinear energy sinks (B-NESs). These devices suppress vibration energy in a broadband way, and can be regarded as extensions of classical linear tuned mass dampers (TMDs) which are narrowband devices. Through the open-source MoorDyn library, we simulated the vibrations of a vertical subsea cable equipped with a set of B-NESs. Multi-objective optimization was performed to detect the B-NES parameters for optimal mitigation of the cable vibrations. Advanced signal processing verified the efficacy of the optimized B-NESs not only to rapidly absorb and locally dissipate vibration energy, but also to nonlinearly scatter vibration energy from low to high frequencies within the cable itself. This last feature is especially beneficial for vibration mitigation of the undersea cable, as at higher frequencies the cable vibrations exhibit drastically reduced amplitudes and are more effectively dissipated by inherent structural damping and hydrodynamic radiation damping. This contrasts with traditional TMDs which can mitigate vibration only at a single frequency. Furthermore, our robustness study confirms the B-NES's effectiveness under even varying environmental conditions. Overall, the B-NES's capacity for broadband vibration mitigation renders it a promising retrofit solution for improving the performance and operational safety of dynamic power cables in offshore wind farms and other marine applications.

17 WIND ENERGY↗
DOE OSTI2019

Numerical analysis and wave tank validation on the optimal design of a two-body wave energy converter

To improve the performance of a ‘point absorber’ type wave energy converter (WEC), an additional submerged body can be deployed. The submerged body can be used to increase the equivalent excitation force on the WEC, as well as provide resonance tuning. This paper presents numerical analysis and experimental validation of a two-body point absorber type WEC using a mechanical motion rectifier (MMR) based power takeoff. The two-body point absorber consists of a floating buoy connected to a neutrally buoyant submerged body via the power-takeoff. The mechanical motion rectifier and a ball screw translate the relative heave motion of the two bodies into unidirectional rotation, which in turn spins a generator. Frequency domain analysis suggests there is an optimal submerged body mass for maximum WEC power absorption. Regular wave simulations in the time domain are compared to the results obtained in the frequency domain. While the time domain and frequency domain results predict the same optimal mass ratio, time domain analysis provides a more complex and accurate power result. To validate the time domain model, experimental wave tank testing is conducted using a 1:30 scale model WEC. The experiment shows the two-body WEC can produce twice the amount of power as the single-body WEC with same floating buoy and can be further increased by PTO design and power electronics optimization. Furthermore, wave tank testing shows the two-body WEC has a capture width ratio up to 58% at 59 kW/m and 51% at 36 kW/m.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Conventional High-Temperature Superconductivity in Metallic, Covalently Bonded, Binary-Guest C–B Clathrates

Inspired by the synthesis of XB 3 C 3 (X = Sr, La) compounds in the bipartite sodalite clathrate structure, density functional theory (DFT) calculations are performed on members of this family containing up to two different metal atoms. A DFT chemical pressure analysis on systems with X = Mg, Ca, Sr, Ba reveals that the size of the metal cation, which can be tuned to stabilize the B–C framework, is key for their ambient-pressure dynamic stability. High-throughput density functional theory calculations on 105 Pm$\bar{3}$ symmetry XYB 6 C 6 binary-guest compounds (where X, Y are electropositive metal atoms) find 22 that are dynamically stable at 1 atm, expanding the number of potentially synthesizable phases by 19 (18 metals and 1 insulator). Here, the density of states at the Fermi level and superconducting critical temperature, T c , can be tuned by changing the average oxidation state of the metal atoms, with T c being highest for an average valence of +1.5. KPbB 6 C 6 , with an ambient-pressure Eliashberg T c of 88 K, is predicted to possess the highest T c among the studied Pm$\bar{3}$n XB 3 C 3 or Pm$\bar{3}$XYB 6 C 6 phases, and calculations suggest it may be synthesized using high-pressure high-temperature techniques and then quenched to ambient conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Thermodynamically Guided Synthesis of Mixed-Linker Zr-MOFs with Enhanced Tunability

Guided by thermodynamics, we have synthesized two mixed-linker zirconium-based metal–organic frameworks (Zr-MOFs), namely, PCN-133 and PCN-134. Both of them possess a layer-pillar structure, in which the connection between Zr 6 clusters and primary BTB linkers form a (3,6)-connected kdg layer that is further extended into 3D frameworks by auxiliary DCDPS/TCPP linkers (BTB = benzene tribenzoate, DCDPS = 4,4'-dicarboxydiphenyl sulfone, TCPP = tetrakis(4-carboxyphenyl)porphyrin). PCN-134 demonstrates high porosity (N 2 uptake of 717 cm 3 ·g –1 and BET surface area of 1946 cm 2 ·g –1 ) and excellent chemical stability in aqueous solutions with pH values ranging from 0 to 13. More importantly, PCN-134 tolerates the partial absence of auxiliary linkers leading to structural defects during the assembly process while preserving its framework integrity. Furthermore, the defect density can be systematically controlled by tuning the occupancy of the auxiliary linker, which in turn affects the MOF properties. For instance, the dichromate uptake of PCN-134 is tuned by adjusting the BTB/TCPP ratios, which gives rise to an efficient dichromate absorbent when the TCPP molar ratio in linkers is set as 22%. Additionally, the photocatalytic reduction of Cr(VI) in aqueous solution was also performed by PCN-134–22%TCPP which exhibits excellent catalytic activity. This work not only opens up a new synthetic route toward mixed-linker MOFs, but also provides tunable control of MOF defects and, in turn, the properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗