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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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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Synthesis, crystal structure, thermal analysis and dielectric properties of [(C{sub 4}H{sub 9}){sub 4}N]{sub 3}Bi{sub 2}Cl{sub 9} compound

A new organic–inorganic tri-tetrabutylammonium nonachlorobibismuthate(III) compound was prepared. It was found to crystallize in the monoclinic system (P2{sub 1}/n space group) with the following lattice parameters: a=11.32(2) Å, b=22.30(3) Å, c=28.53(2) Å and β=96.52(0)°. The [Bi{sub 2}Cl{sub 9}]{sup 3−} anions are surrounded by six [(C{sub 4}H{sub 9})N]{sup +} cations, forming an octahedral configuration. These octahedra are sharing corners in order to provide the tri-dimensional network cohesion. The differential scanning calorimetry reveals four order-disorder reversible phase transitions located at 214, 238, 434 and 477 K. The Raman and infrared spectra confirm the presence of both cationic [(C{sub 4}H{sub 9})N]{sup +} and anionic [Bi{sub 2}Cl{sub 9}]{sup 3−} parts. The dielectric parameters, real and imaginary dielectric permittivity (ε′ and ε″), and dielectric loss tangent (tg δ), were measured in the frequency range of 209 kHz–5 MHz at different temperatures. The variations of dielectric dispersion (ε') and dielectric absorption (ε″) with frequency show a distribution of relaxation times, which is probably related to the change in the dynamical state of the [(C{sub 4}H{sub 9}){sub 4}N]{sup +} cations and the [Bi{sub 2}Cl{sub 9}]{sup 3−} anions. - Graphical abstract: Projection of the atomic arrangement of the [(C{sub 4}H{sub 9}){sub 4}N]{sub 3}Bi{sub 2}Cl{sub 9} compound along the b axis. - Highlights: • The structure of the (TBA){sub 3}Bi{sub 2}Cl{sub 9} compound was solved and reported. • The cristal belongs to the monoclinic system with P2{sub 1}/n space group. • DSC discloses four order–disorder reversible phases transitions. • The temperature-dependent permittivity ε' and ε″ has been investigated.

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

Empirically-calibrated H100 node power models for accurate AI training energy estimation

Accurately quantifying the energy use of artificial intelligence (AI) training is critical for infrastructure planning, carbon accounting, and sustainable data center operation, but few studies have directly measured the power consumption of production workloads on contemporary hardware. By combining empirical measurements from Brookhaven National Laboratory during AI training on 8-graphics-processing-unit H100 systems with open-source benchmarking data, we develop statistical models relating computational intensity to node-level power consumption. We measure the gap between manufacturer-rated thermal design power (TDP) and actual power demand during AI training. Our analysis reveals that even computationally intensive workloads operate at only 76% of the 10.2 kW TDP rating. Our architecture-specific model, calibrated to floating-point operations, predicts energy consumption with 11.4% mean absolute percentage error, significantly outperforming TDP-based approaches (27%–37% error). We identified distinct power signatures between transformer and convolutional neural network architectures, with transformers showing characteristic fluctuations that may impact grid stability. These results provide a measurement-grounded basis for improving AI training energy estimates, enabling more reliable infrastructure sizing, cost projections, and environmental impact assessments.

Newkirk, Alex C↗
DOE OSTI2020

Deep Learning-Based Queue-Aware Eco-Approach and Departure System for Plug-In Hybrid Electric Buses at Signalized Intersections: A Simulation Study

Eco-Approach and Departure (EAD) has been considered as a promising eco-driving strategy for vehicles traveling in an urban environment, where information such as signal phase and timing (SPaT) and geometric intersection description is well utilized to guide vehicles passing through intersections in the most energy-efficient manner. Previous studies formulated the optimal trajectory planning problem as finding the shortest path on a graphical model. While this method is effective in terms of energy saving, its computation efficiency can be further enhanced by adopting machine learning techniques. In this paper, we propose an innovative deep learning-based queue-aware eco-approach and departure (DLQ-EAD) system for a plug-in hybrid electric bus (PHEB), which is able to provide an online optimal trajectory for the vehicle considering both the downstream traffic condition (i.e. traffic lights, queues) and the vehicle powertrain efficiency. Based on optimal solutions obtained from the graph-based trajectory planning algorithm (GTPA), a deep neural network (DNN) is developed to learn the optimal vehicle speed for the next time step given its current state. It is demonstrated that the trained DNN can provide energy-efficient trajectories with high computational efficiency and high flexibility adopting to dynamic changes in the surrounding environment. To address the impact of downstream traffic, a queue prediction model is further developed using data from radars and connected vehicles (CVs), as well as signal timing data from SPaT messages. A comprehensive simulation study in the microscopic traffic modeling software PTV VISSIM shows that the proposed DLQ-EAD can achieve 18.7%-24.0% energy efficiency improvements for a single PHEB on various traffic congestion levels. The proposed queue prediction model can be of practical significance even at low penetration rates of CVs. Specifically, additional energy savings of 2.0%-8.2% can be further achieved with 20% vehicles in the network.

Ye, Fei↗
DOE OSTI2016

A Nonrelational Data Warehouse for the Analysis of Field and Laboratory Data From Multiple Heterogeneous Photovoltaic Test Sites

A nonrelational, distributed computing, data warehouse, and analytics environment (Energy-CRADLE) was developed for the analysis of field and laboratory data from multiple heterogeneous photovoltaic (PV) test sites. This data informatics and analytics infrastructure was designed to process diverse formats of PV performance data and climatic telemetry time-series data collected from a PV outdoor test network, i.e., the Solar Durability and Lifetime Extension global SunFarm network, as well as point-in-time laboratory spectral and image measurements of PV material samples. Using Hadoop/HBase for the distributed data warehouse, Energy-CRADLE does not have a predefined data table schema, which enables ingestion of data in diverse and changing formats. For easy data ingestion and data retrieval, Energy-CRADLE utilizes Hadoop streaming to enable Python MapReduce and provides a graphical user interface, i.e., py-CRADLE. By developing the Hadoop distributed computing platform and the HBase NoSQL database schema for solar energy, Energy-CRADLE exemplifies an integrated, scalable, secure, and user-friendly data informatics and analytics system for PV researchers. Furthermore, an example of Energy-CRADLE enabled scalable, data-driven, analytics is presented, where machine learning is used for anomaly detection across 2.2 million real-world current-voltage (I–V) curves of PV modules in three distinct Koppen–Geiger climatic zones.

14 SOLAR ENERGY↗
DOE OSTI2012

Decision support systems and methods for complex networks

Methods and systems for automated decision support in analyzing operation data from a complex network. Embodiments of the present invention utilize these algorithms and techniques not only to characterize the past and present condition of a complex network, but also to predict future conditions to help operators anticipate deteriorating and/or problem situations. In particular, embodiments of the present invention characterize network conditions from operation data using a state estimator. Contingency scenarios can then be generated based on those network conditions. For at least a portion of all of the contingency scenarios, risk indices are determined that describe the potential impact of each of those scenarios. Contingency scenarios with risk indices are presented visually as graphical representations in the context of a visual representation of the complex network. Analysis of the historical risk indices based on the graphical representations can then provide trends that allow for prediction of future network conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Parallel replica dynamics method for bistable stochastic reaction networks: Simulation and sensitivity analysis

Stochastic reaction networks that exhibit bistable behavior are common in systems biology, materials science, and catalysis. Sampling of stationary distributions is crucial for understanding and characterizing the long-time dynamics of bistable stochastic dynamical systems. However, simulations are often hindered by the insufficient sampling of rare transitions between the two metastable regions. In this paper, we apply the parallel replica method for a continuous time Markov chain in order to improve sampling of the stationary distribution in bistable stochastic reaction networks. The proposed method uses parallel computing to accelerate the sampling of rare transitions. Furthermore, it can be combined with the path-space information bounds for parametric sensitivity analysis. With the proposed methodology, we study three bistable biological networks: the Schlögl model, the genetic switch network, and the enzymatic futile cycle network. We demonstrate the algorithmic speedup achieved in these numerical benchmarks. More significant acceleration is expected when multi-core or graphics processing unit computer architectures and programming tools such as CUDA are employed

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

IMG-ABC: new features for bacterial secondary metabolism analysis and targeted biosynthetic gene cluster discovery in thousands of microbial genomes

Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic gene clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

A new strontium antimonate{sup III} Sr{sub 5}Sb{sub 22}O{sub 38}: Synthesis, crystal structure and characterizations

A new strontium antimonate{sup III}, Sr{sub 5}Sb{sub 22}O{sub 38}, has been hydrothermally synthesized and structurally characterized by single crystal X-ray diffraction. It crystallizes in the P2{sub 1}/n space group of the monoclinic system with a=11.739(9) Å, b=12.014(10) Å, c=16.412(13) Å, β=91.460(8)°, V=2314.0(3) Å{sup 3}. The crystal structure is built of seven trigonal–pyramidal SbO{sub 3} and four sphenoid SbO{sub 4} polyhedra which are connected through sharing corner-oxygen atoms to form the complex three-dimensional {sub ∞}{sup 3}[Sb{sub 22}O{sub 38}]{sup 10−} anionic network with two different intersectant tunnels along the [111-bar ] and [11-bar 1-bar ] directions accommodating the electric charge balanced Sr{sup 2+} cations. First-principles electronic structure calculations based on the density functional theory (DFT) and the UV–vis diffuse reflectance spectroscopy measurements both indicate that the compound belongs to a direct band insulator with an optical gap value of 3.3 eV. - Graphical abstract: The 2D Sb–O slabs are stacked through sharing oxygen atoms to form the 3D network structure of the new strontium antimonate{sup III} Sr{sub 5}Sb{sub 22}O{sub 38}. - Highlights: • A new strontium antimonate{sup III}, Sr{sub 5}Sb{sub 22}O{sub 38}, has been hydrothermally synthesized. • The single crystal structure was determined by X-ray diffraction. • The powder XRD and UV–vis absorption spectroscopy were studied. • Theoretical studies interpret the relationships between optical absorption and crystal structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Novel alkaline earth copper germanates with ferro and antiferromagnetic S=1/2 chains

Two new alkaline earth copper(II) germanates were hydrothermally synthesized: CaCuGeO{sub 4}{center_dot}H{sub 2}O (1) and BaCu{sub 2}Ge{sub 3}O{sub 9}{center_dot}H{sub 2}O (2), and their structures determined by single crystal X-ray diffraction. Compound (1) crystallizes in space group P2{sub 1}/c with a=5.1320(2) Angstrom-Sign , b=16.1637(5) Angstrom-Sign , c=5.4818(2) Angstrom-Sign , {beta}=102.609(2) Degree-Sign , V=443.76(3) Angstrom-Sign {sup 3} and Z=4. This copper germanate contains layers of composition [CuGeO{sub 4}]{sub {infinity}}{sup 2-} comprising CuO{sub 4} square planes and GeO{sub 4} tetrahedra with calcium and water molecules in the inter-layer space. Compound (2) crystallizes in the Cmcm space group with a=5.5593(3) Angstrom-Sign , b=10.8606(9) Angstrom-Sign , c=13.5409(8) Angstrom-Sign , V=817.56(9) Angstrom-Sign {sup 3} and Z=4. This structure contains GeO{sub 6} and CuO{sub 6} octahedra as well as GeO{sub 4} tetrahedra, forming a three-dimensional network of interconnecting six-membered ring channels. The magnetic susceptibility for both samples can be interpreted as S=1/2 chains, in agreement with the copper topology observed in the crystal structure. The susceptibility of (1) exhibits a Bonner-Fisher type behavior, resulting from antiferromagnetic intra-chain interactions without three-dimensional ordering down to 5 K-the lowest measured temperature. This observation, together with the absence of super-exchange paths between the copper chains, make this system particularly promising for the study of low dimensional magnetism. The magnetic properties of (2) show a very weak ferromagnetic near-neighbor interaction along the chain. In this compound a peak the {chi}T plot seems to indicate the onset of interchain antiferromagentic correlations. However, no ordering temperature is detected in the susceptibility data. - Graphical abstract: Copper chains present in CaCuGeO{sub 4}{center_dot}H{sub 2}O and BaCu{sub 2}Ge{sub 3}O{sub 9}{center_dot}H{sub 2}O, two novel copper germanates synthesized hydrothermally, showing antiferromagnetic and ferromagnetic intra-chain interactions respectively. Highlights: Black-Right-Pointing-Pointer The structure of two new chain containing copper germinates is reported. Black-Right-Pointing-Pointer The calcium compound CaCuGeO{sub 4}{center_dot}H{sub 2}O contains corner sharing square planes. Black-Right-Pointing-Pointer The barium compound BaCu{sub 2}Ge{sub 3}O{sub 9}, displays edge sharing octahedra. Black-Right-Pointing-Pointer Susceptibility data show that the Ca compound is a one-dimensional antiferromagnet while Ba is a weak ferromagnet.

36 MATERIALS SCIENCE↗
DOE OSTI2012

A novel structure and photochromism of heteropolyoxometalates dispersed in polymer networks

Nanocomposites based on Keggin structure tungstophosphate acid (PWA) with 'branch-like' nanometer well dispersed in poly(acrylamide-co-vinylamine) (PAM-co-PVAm) were fabricated. The microstructure and photochromic properties were studied via Fourier transform infrared spectroscopy (FT-IR), scanning electron microscope (SEM), transmission electron microscope (TEM), ultraviolet-visible spectra (UV-vis) and electron resonance spectra (ESR). FT-IR results showed that the Keggin geometry of polyoxometalates was still preserved inside the composites and hydrogen bonding and salt formation were built between PWA and polymer matrix. SEM and TEM images showed that PWA nanoparticles were finely dispersed in polymer matrix with 'branch-like' shape. Under UV irradiation, the film was reduced photochemically to yield a glaucous species. After UV light turned off, the color of film became green. Two photo-reduction processes (one was between acylamino and heteropoly acid, another was between amidocyanogen and heteropoly acid) occurred at the same time in PWA/PAM-co-PVAm system, which resulted in the formation of heteropolygreen. - Graphical abstract: Two absorption bands appeared after UV irradiated. In bleaching process, the peaks at 620-820 nm disappeared and those at 420 nm still presented. Due to synergies happened between heteropolyacid and PAM-co-PVAm, heteropolygreen was formed. Highlights: Black-Right-Pointing-Pointer 'Branch-like' composites were fabricated by dispersed PWA into PAM-co-PVAm system. Black-Right-Pointing-Pointer Two photo-reduction processes occurred simultaneously in PWA/PAM-co-PVAm system. Black-Right-Pointing-Pointer Heteropolygreen was formed by synergies of hydrogen bonding and salt formation.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Complex long-range magnetic ordering in the Mn-bearing dugganite Pb{sub 3}TeMn{sub 3}P{sub 2}O{sub 14}

Spin liquids, multiferroics, and doubly-chiral helical structures are just some of the exotic magnetic states found in the langasite compounds. A subclass of the langasite group, the Te{sup 6+}-containing dugganites, has also shown exotic magnetism including magnetoelectric coupling, coexisting complex long-ranged ordered structures, and low-field induced magnetic transitions. Here, we present the first detailed structural study of Pb{sub 3}TeMn{sub 3}P{sub 2}O{sub 14} as well as the first neutron scattering measurements. This material undergoes long-range magnetic ordering, similar to the multiferroic Ba{sub 3}NbFe{sub 3}Si{sub 2}O{sub 14}, at T{sub N}=6.6 K, which is consistent with previous magnetization measurements. However unlike any other langasite or dugganite studied to date, we present evidence of a large, pseudohexagonal incommensurate supercell that alters the nuclear and magnetic structures away from the langasite ideal. - Graphical abstract: Two geometrically frustrated cationic substructures of the langasites and dugganites have profound effects on the magnetism of these compounds. In Pb{sub 3}TeMn{sub 3}P{sub 2}O{sub 14}, Mn{sup 2+} (S=5/2) isolated trinuclear units are shown in yellow, while the red distorted kagomé network is nonmagnetic. (For interpretation of the references to color the reader is referred to the web version of this article.) Highlights: • Polycrystalline Pb{sub 3}TeMn{sub 3}P{sub 2}O{sub 14} was prepared. • Found evidence of a large, pseudohexagonal supercell that is incommensurate with the subcell. • Long-range antiferromagnetic ordering is observed below T{sub N}=6.6 K similar to Ba{sub 3}NbFe{sub 3}Si{sub 2}O{sub 14}. • Broken symmetry probably causes magnetic peak splitting in this system.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Synthesis, crystal structure and properties of [(dien){sub 2}Mn]Ge{sub 2}S{sub 4} with mixed-valent Ge centers

One new manganese thiogermanate, [(dien){sub 2}Mn]Ge{sub 2}S{sub 4} (dien=diethylenetriamine), was prepared under mild solvothermal conditions and structurally and spectroscopically characterized. The title compound crystallizes in the orthorhombic system, chiral space group P2{sub 1}2{sub 1}2{sub 1} (no. 19) with a=9.113(4) Å, b=12.475(5) Å, c=17.077(7) Å, V=1941.5(15) Å{sup 3} and Z=4. Its structure features a three-dimensional (3D) network composed of a one-dimensional (1D) [Ge{sub 2}S{sub 4}]{sup 2−} anionic chain and a [(dien){sub 2}Mn]{sup 2+} complex interconnected via various hydrogen bonds. The most interesting structural feature of the compound is the presence of two different oxidation states of germanium centers in the 1D [Ge{sub 2}S{sub 4}]{sup 2−} chain, which is also supported by the result of X-ray photoelectron spectroscopy measurement. The optical property of the title compound has also been studied by UV–vis spectra. - Graphical abstract: One new thiogermanate, [(dien){sub 2}Mn]Ge{sub 2}S{sub 4}, contains a one-dimensional [Ge{sub 2}S{sub 4}]{sup 2−} anionic chain with two different oxidation states of germanium centers. Display Omitted - Highlights: • One new manganese thiogermanate [(dien){sub 2}Mn]Ge{sub 2}S{sub 4} was prepared. • The compound features 1D [Ge{sub 2}S{sub 4}]{sup 2−} chain composed of [Ge{sup II}S{sub 4}] and [Ge{sup IV}S{sub 4}] tetrahedra. • The first example of inorganic–organic hybrid thiogermanates with mixed valent Ge centers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

WHONDRS-GUI: a web application for global survey of surface water metabolites

Background The Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) is a consortium that aims to understand complex hydrologic, biogeochemical, and microbial connections within river corridors experiencing perturbations such as dam operations, floods, and droughts. For one ongoing WHONDRS sampling campaign, surface water metabolite and microbiome samples are collected through a global survey to generate knowledge across diverse river corridors. Metabolomics analysis and a suite of geochemical analyses have been performed for collected samples through the Environmental Molecular Sciences Laboratory (EMSL). The obtained knowledge and data package inform mechanistic and data-driven models to enhance predictions of outcomes of hydrologic perturbations and watershed function, one of the most critical components in model-data integration. To support efforts of the multi-domain integration and make the ever-growing data package more accessible for researchers across the world, a Shiny/R Graphical User Interface (GUI) called WHONDRS-GUI was created. Results The web application can be run on any modern web browser without any programming or operational system requirements, thus providing an open, well-structured, discoverable dataset for WHONDRS. Together with a context-aware dynamic user interface, the WHONDRS-GUI has functionality for searching, compiling, integrating, visualizing and exporting different data types that can easily be used by the community. The web application and data package are available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1484811 , which enables users to simultaneously obtain access to the data and code and to subsequently run the web app locally. The WHONDRS-GUI is also available for online use at Shiny Server ( https://xmlin.shinyapps.io/whondrs/ ).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Harnessing distributed GPU computing for generalizable graph convolutional networks in power grid reliability assessments

Although machine learning (ML) has emerged as a powerful tool for rapidly assessing grid contingencies, prior studies have largely considered a static grid topology in their analyses. This limits their application, since they need to be re-trained for every new topology. Here, this paper explores the development of generalizable graph convolutional network (GCN) models by pre-training them across a range of grid topologies and contingency types. We found that a GCN model with auto-regressive moving average (ARMA) layers with a line graph representation of the grid offered the best predictive performance in predicting voltage magnitudes (VM) and voltage angles (VA). We introduced the concept of phantom nodes to consider disparate grid topologies with a varying number of nodes and lines. For pre-training the GCN ARMA model across a variety of topologies, distributed graphics processing unit (GPU) computing afforded us significant training scalability. The predictive performance of this model on grid topologies that were part of the training data is substantially better than the direct current (DC) approximation. Although direct application of the pre-trained model to topologies that are not part of the grid is not particularly satisfactory, fine-tuning with small amounts of data from a specific topology of interest significantly improves predictive performance. In general, this paper highlights the feasibility of training large-scale GNN models to assess the reliability of power grids by considering a wide variety of grid topologies and contingency types. With the advent of foundational models in ML and the exponential increase in GPU computing clusters, generalizable ML models will significantly enhance how utilities manage power systems and make decisions in real-time or near-real-time.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Cd(II) complexes with different nuclearity and dimensionality based on 3-hydrazino-4-amino-1,2,4-triazole

A series of zero- to two-dimensional Cd(II) coordination compounds have been synthesized by the reaction of Cd(II) salts and 3-hydrazino-4-amino-1,2,4-triazole di-hydrochloride (HATr·2HCl). [CdCl{sub 2}(HATr){sub 2}] (1) and [Cd{sub 2}Cl{sub 4}(HATr){sub 2}(H{sub 2}O){sub 2}] (2) have discrete mononuclear and binuclear structures, respectively. [Cd(HATr){sub 2}(ClO{sub 4}){sub 2}]{sub n} (3) presents polymeric 1-D chain and [Cd{sub 2}(NO{sub 3}){sub 2}Cl{sub 2}(HATr){sub 2}]{sub n} (4) shows 2-D frameworks. All Cd(II) ions exhibit distorted octahedral configurations in 1–3, whilst both hexa and heptacoordinated Cd(II) are formed in 4. The HATr ligands adopt chelating coordinated mode in 1, while tri-dentate bridging–chelating mode in 2–4. The chloride ion is a mono-coordinated ligand in 1 and 2, but it bridges two adjacent metal ions in 4. Furthermore, thermal behaviors have been investigated and the results reveal that all complexes have good thermal stability. The impact sensitivity test indicates that complex 3 is sensitive to impact stimuli. - Graphical abstract: Four Cd(II) complexes based on 3-hydrazino-4-amino-1,2,4-triazole ligands exhibit diverse structures from mononuclear to 2D networks. - Highlights: • Cd(II) complexes containing 3-hydrazino-4-amino-1,2,4-triazole ligands. • Mononuclear, binuclear, 1-D and 2-D structures. • Good thermal stability. • Thermal decomposition kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Optimum Aggregation and Control of Spatially Distributed Flexible Resources in Smart Grid

This paper presents an algorithm to optimally aggregate spatially distributed flexible resources at strategic microgrid/smart-grid locations. The aggregation reduces a distribution network having thousands of nodes to an equivalent network with a few aggregated nodes, thereby enabling distribution system operators (DSOs) to make faster operational decisions. Moreover, the aggregation enables flexibility from small distributed flexible resources to be traded to different power and energy markets. A hierarchical control architecture comprising a combination of centralized and decentralized control approaches is proposed to practically deploy the aggregated flexibility. The proposed method serves as a great operational tool for DSOs to decide the exact amount of required flexibilities from different network section(s) for solving grid constraint violations. The effectiveness of the proposed method is demonstrated through simulation of three operational scenarios in a real low voltage distribution system having high penetrations of electric vehicles and heat pumps. Finally, the simulation results demonstrated that the aggregation helps DSOs not only in taking faster operational decisions, but also in effectively utilizing the available flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Data Acquisition with GPUs: The DAQ for the Muon $g$-$2$ Experiment at Fermilab

Graphical Processing Units (GPUs) have recently become a valuable computing tool for the acquisition of data at high rates and for a relatively low cost. The devices work by parallelizing the code into thousands of threads, each executing a simple process, such as identifying pulses from a waveform digitizer. The CUDA programming library can be used to effectively write code to parallelize such tasks on Nvidia GPUs, providing a significant upgrade in performance over CPU based acquisition systems. The muon $g$-$2$ experiment at Fermilab is heavily relying on GPUs to process its data. The data acquisition system for this experiment must have the ability to create deadtime-free records from 700 $\mu$s muon spills at a raw data rate 18 GB per second. Data will be collected using 1296 channels of $\mu$TCA-based 800 MSPS, 12 bit waveform digitizers and processed in a layered array of networked commodity processors with 24 GPUs working in parallel to perform a fast recording of the muon decays during the spill. The described data acquisition system is currently being constructed, and will be fully operational before the start of the experiment in 2017.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Efficient Aho-Corasick String Matching on Emerging Multicore Architectures

String matching algorithms are critical to several scientific fields. Beside text processing and databases, emerging applications such as DNA protein sequence analysis, data mining, information security software, antivirus, ma- chine learning, all exploit string matching algorithms [3]. All these applica- tions usually process large quantity of textual data, require high performance and/or predictable execution times. Among all the string matching algorithms, one of the most studied, especially for text processing and security applica- tions, is the Aho-Corasick algorithm. 1 2 Book title goes here Aho-Corasick is an exact, multi-pattern string matching algorithm which performs the search in a time linearly proportional to the length of the input text independently from pattern set size. However, depending on the imple- mentation, when the number of patterns increase, the memory occupation may raise drastically. In turn, this can lead to significant variability in the performance, due to the memory access times and the caching effects. This is a significant concern for many mission critical applications and modern high performance architectures. For example, security applications such as Network Intrusion Detection Systems (NIDS), must be able to scan network traffic against very large dictionaries in real time. Modern Ethernet links reach up to 10 Gbps, and malicious threats are already well over 1 million, and expo- nentially growing [28]. When performing the search, a NIDS should not slow down the network, or let network packets pass unchecked. Nevertheless, on the current state-of-the-art cache based processors, there may be a large per- formance variability when dealing with big dictionaries and inputs that have different frequencies of matching patterns. In particular, when few patterns are matched and they are all in the cache, the procedure is fast. Instead, when they are not in the cache, often because many patterns are matched and the caches are continuously thrashed, they should be retrieved from the system memory and the procedure is slowed down by the increased latency. Efficient implementations of string matching algorithms have been the fo- cus of several works, targeting Field Programmable Gate Arrays [4, 25, 15, 5], highly multi-threaded solutions like the Cray XMT [34], multicore proces- sors [19] or heterogeneous processors like the Cell Broadband Engine [35, 22]. Recently, several researchers have also started to investigate the use Graphic Processing Units (GPUs) for string matching algorithms in security applica- tions [20, 10, 32, 33]. Most of these approaches mainly focus on reaching high peak performance, or try to optimize the memory occupation, rather than looking at performance stability. However, hardware solutions supports only small dictionary sizes due to lack of memory and are difficult to customize, while platforms such as the Cell/B.E. are very complex to program.

Tumeo, Antonino↗