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At least 343 records · Page 19

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DOE OSTI2025

Grey-Box System Identification of Grid-Forming Inverters

This paper demonstrates the use of grey-box system identification methods for simplifying and understanding the nonlinear power dynamics of grid-forming inverters (GFMs). The power and frequency outputs of complex high-order GFM models are fed into system identification software in order to fit them to a predetermined LTI system and learn system parameters such as (synthetic) inertia and droop constants. The same process is then run for a high-order synchronous generator model, and the outputs are fit to the same set of LTI equations. Simulation of a network of GFM inverters with diverse control architecture is also performed for the same process. The intent is threefold: first, to demonstrate the appropriateness of unified LTI models for describing the power and frequency dynamics of individual resources and connected networks, in order to facilitate analysis of larger heterogeneous networked systems; second, to discover the relationship between internal control parameters of GFMs and their externally observed values; and third, to validate that grey-box data-driven system identification techniques can be a valuable tool to discover the values of important parameters in the absence of explicit vendor models.

analytical models↗

DOE OSTI2020

Impedance-Based Prediction of SSR-Generated Harmonics in Doubly-Fed Induction Generators

Doubly-fed induction generators (DFIGs) are prone to subsynchronous resonance (SSR) with series-compensated transmission lines and experiencing SSR-generated harmonics of wide-ranging magnitudes. This paper presents a large-signal impedance-based approach for the prediction of the magnitude of SSR-generated harmonics in DFIGs. Note that the large-signal impedance of a network shows variation in its impedance response with the magnitude of perturbation at its terminals. It is discovered in this paper that the impedance of a series-compen- sated transmission line starts changing with the magnitude of SSR because of the metal-oxide varistor-based protection of series capacitors in the line. The changing line impedance halts the growth of the SSR beyond a certain point, where the DFIG forms a limit-cycle mode and emits harmonics at the SSR frequency. The discovered role of the protection of series capacitors in SSR not only enables the prediction of SSR-generated harmonics but also can be used for the timely detection of an SSR event to avoid system disruption and sudden loss of bulk generation. The large- signal impedance-based prediction of SSR-generated harmonics in DFIG-based wind and hydro generators is demonstrated using numerical simulations of a 2.5-MVA, 690-V DFIG supplying to a series-compensated transmission line.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Parameter Reduction of Composite Load Model Using Active Subspace Method

Over the past decades, the increasing penetration of distributed energy resources (DERs) has dramatically changed the power load composition in the distribution networks. The traditional static and dynamic load models can hardly capture the dynamic behavior of modern loads especially for fault-induced delayed voltage recovery (FIDVR) events. Thus, a more comprehensive composite load model with combination of static load, different types of induction motors, single-phase A/C motor, electronic load and DERs has been proposed by Western Electricity Coordinating Council (WECC). However, due to the large number of parameters and model complexity, the WECC composite load model (WECC CMLD) raises new challenges to power system studies. To overcome these challenges, in this paper, a cutting-edge parameter reduction (PR) approach for WECC CMLD based on active subspace method (ASM) is proposed. Firstly, the WECC CMLD is parameterized in a discrete-time manner for the application of the proposed method. Then, parameter sensitivities are calculated by discovering the active subspace, which is a lower-dimensional linear subspace of the parameter space of WECC CMLD in which the dynamic response is most sensitive. The interdependency among parameters can be taken into consideration by our approach. Finally, the numerical experiments validate the effectiveness and advantages of the proposed approach for WECC CMLD model.

active subspace↗

DOE OSTI2021

Beyond Visual Analytics: Human-Machine Teaming for AI-Driven Data Sensemaking

"Detect the expected, discover the unexpected" was the founding principle of the field of visual analytics. This mantra implies that human stakeholders, like a domain expert or data analyst, could leverage visual analytics techniques to seek answers to known unknowns and discover unknown unknowns in the course of the data sensemaking process. We argue that in the era of AI-driven automation, we need to recalibrate the roles of humans and machines (e.g., a machine learning model) as teammates. We posit that by realizing human-machine teams as a stakeholder unit, we can better achieve the best of both worlds: automation transparency and human reasoning efficacy. However, this also increases the burden on analysts and domain experts towards performing more cognitively demanding tasks than what they are used to. In this paper, we reflect on the complementary roles in a human-machine team through the lens of cognitive psychology and map them to existing and emerging research in the visual analytics community. We discuss open questions and challenges around the nature of human agency and analyze the shared responsibilities in human-machine teams.

Sensemaking, human-machine teaming, agency, artifi↗

DOE OSTI2023

RecJ3/4-aRNase J form a Ubl-associated nuclease complex functioning in survival against DNA damage in Haloferax volcanii

Nucleases are strictly regulated and often localized in the cell to avoid the uncontrolled degradation of DNA and RNA. Here, a new type of nuclease complex, composed of RecJ3, RecJ4, and aRNase J, was identified through its ATP-dependent association with the ubiquitin-like SAMP1 and AAA-ATPase Cdc48a. The complex was discovered in Haloferax volcanii , an archaeon lacking an RNA exosome. Genetic analysis revealed aRNase J to be essential and RecJ3, RecJ4, and Cdc48a to function in the recovery from DNA damage including genotoxic agents that generate double-strand breaks. The RecJ3:RecJ4:aRNase J complex (isolated in 2:2:1 stoichiometry) functioned primarily as a 3′−5′ exonuclease in hydrolyzing RNA and ssDNA, with the mechanism non-processive for ssDNA. aRNase J could also be purified as a homodimer that catalyzed endoribonuclease activity and, thus, was not restricted to the 5′−3′ exonuclease activity typical of aRNase J homologs. Moreover, RecJ3 and RecJ4 could be purified as a 560-kDa subcomplex in equimolar subunit ratio with nuclease activities mirroring the full RecJ3/4-aRNase J complex. These findings prompted reconstitution assays that suggested RecJ3/4 could suppress, alter, and/or outcompete the nuclease activities of aRNase J. Based on the phenotypic results, this control mechanism of aRNase J by RecJ3/4 is not necessary for cell growth but instead appears important for DNA repair. IMPORTANCE Nucleases are critical for various cellular processes including DNA replication and repair. Here, a dynamic type of nuclease complex is newly identifiedidentifiedidentifiedin the archaeon Haloferax volcanii , which is missing the canonical RNA exosome. The complex, composed of RecJ3, RecJ4, and aRNase J, functions primarily as a 3′−5′ exonuclease and was discovered through its ATP-dependent association with the ubiquitin-like SAMP1 and Cdc48a. aRNase J alone forms a homodimer that has endonuclease function and, thus, is not restricted to 5′−3′ exonuclease activity typical of other aRNase J enzymes. RecJ3/4 appears to suppress, alter, and/or outcompete the nuclease activities of aRNase J. While aRNase J is essential for growth, RecJ3/4, Cdc48a, and SAMPs are important for recovery against DNA damage. These biological distinctions may correlate with the regulated nuclease activity of aRNase J in the RecJ3/4-aRNaseJ complex.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Two novel Patescibacteria: Phycocordibacter aenigmaticus gen. nov. sp. nov. and Minusculum obligatum gen. nov. sp. nov., both associated with microalgae optimized for carbon dioxide sequestration from flue gas

The functional roles of bacterial symbionts associated with microalgae remain understudied despite the importance of microalgae in biotechnology and environmental microbiology. 16S rRNA gene sequencing was conducted to analyze bacterial communities associated with two microalgae optimized for growth with flue gas containing 5%–10% CO 2 . Two dominant bacteria with no taxonomic classification beyond the class level (Paceibacteria) were discovered repeatedly in the most productive algal cultures. Long-read metagenomic sequencing was conducted to yield high-quality metagenomes, from which two novel species were discovered under the Seqcode (seqco.de/r:ywe1blo2), Phycocordibacter aenigmaticus gen. nov. sp. nov. and Minusculum obligatum gen. nov. sp. nov. The genus Phycocordibacter gen. nov. was proposed as the nomenclatural type of the family Phycocordibacteraceae fam. nov. and the order Phycocordibacterales ord. nov. Both bacteria possessed features typical of Patescibacteria such as reduced genomes (<800 kbp), lack of complete glycolysis and tricarboxylic acid (TCA) cycle pathways, and inability to synthesize amino acids. Instead, they rely on the reductive pentose phosphate pathway (Calvin cycle) for essential biosynthesis and redox balance. P. aenigmaticus may also rely on elemental sulfur oxidation (sdo), partial nitrite reduction (nirK), and sulfur-related amino acid metabolism (SAMe → SAH). Both bacteria were found in high relative abundance in cultures of Tetradesmus obliquus HTB1 (freshwater) and Nannochloropsis oceanica IMET1 (marine), suggesting a tight association with microalgae in various environments. The absence of full metabolic pathways for energy production suggests extreme metabolic limitations and obligate symbiosis, most likely with other bacteria associated with the microalgae.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Catabolism of β-5 linked aromatics by Novosphingobium aromaticivorans

ABSTRACT Aromatic compounds are an important source of commodity chemicals traditionally produced from fossil fuels. Aromatics derived from plant lignin can potentially be converted into commodity chemicals through depolymerization followed by microbial funneling of monomers and low molecular weight oligomers. This study investigates the catabolism of the β-5 linked aromatic dimer dehydrodiconiferyl alcohol (DC-A) by the bacterium Novosphingobium aromaticivorans . We used genome-wide screens to identify candidate genes involved in DC-A catabolism. Subsequent in vivo and in vitro analyses of these candidate genes elucidated a catabolic pathway composed of four required gene products and several partially redundant dehydrogenases that convert DC-A to aromatic monomers that can be funneled into the central aromatic metabolic pathway of N. aromaticivorans . Specifically, a newly identified γ-formaldehyde lyase, PcfL, opens the phenylcoumaran ring to form a stilbene and formaldehyde. A lignostilbene dioxygenase, LsdD, then cleaves the stilbene to generate the aromatic monomers vanillin and 5-formylferulate (5-FF). We also showed that the aldehyde dehydrogenase FerD oxidizes 5-FF before it is decarboxylated by LigW, yielding ferulic acid. We found that some enzymes involved in the β-5 catabolism pathway can act on multiple substrates and that some steps in the pathway can be mediated by multiple enzymes, providing new insights into the robust flexibility of aromatic catabolism in N. aromaticivorans . A comparative genomic analysis predicted that the newly discovered β-5 aromatic catabolic pathway is common within the order Sphingomonadales. IMPORTANCE In the transition to a circular bioeconomy, the plant polymer lignin holds promise as a renewable source of industrially important aromatic chemicals. However, since lignin contains aromatic subunits joined by various chemical linkages, producing single chemical products from this polymer can be challenging. One strategy to overcome this challenge is using microbes to funnel a mixture of lignin-derived aromatics into target chemical products. This approach requires strategies to cleave the major inter-unit linkages of lignin to release monomers for funneling into valuable products. In this study, we report newly discovered aspects of a pathway by which the Novosphingobium aromaticivorans DSM12444 catabolizes aromatics joined by the second most common inter-unit linkage in lignin, the β-5 linkage. This work advances our knowledge of aromatic catabolic pathways, laying the groundwork for future metabolic engineering of this and other microbes for optimized conversion of lignin into products.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Disrupting the ArcA Regulatory Network Amplifies the Fitness Cost of Tetracycline Resistance in Escherichia coli

There is an urgent need for strategies to discover secondary drugs to prevent or disrupt antimicrobial resistance (AMR), which is causing >700,000 deaths annually. Here, we demonstrate that tetracycline-resistant (Tet R ) Escherichia coli undergoes global transcriptional and metabolic remodeling, including downregulation of tricarboxylic acid cycle and disruption of redox homeostasis, to support consumption of the proton motive force for tetracycline efflux. Using a pooled genome-wide library of single-gene deletion strains, at least 308 genes, including four transcriptional regulators identified by our network analysis, were confirmed as essential for restoring the fitness of Tet R E. coli during treatment with tetracycline. Targeted knockout of ArcA, identified by network analysis as a master regulator of this new compensatory physiological state, significantly compromised fitness of Tet R E. coli during tetracycline treatment. A drug, sertraline, which generated a similar metabolome profile as the arcA knockout strain, also resensitized Tet R E. coli to tetracycline. We discovered that the potentiating effect of sertraline was eliminated upon knocking out arcA, demonstrating that the mechanism of potential synergy was through action of sertraline on the tetracycline-induced ArcA network in the Tet R strain. Our findings demonstrate that therapies that target mechanistic drivers of compensatory physiological states could resensitize AMR pathogens to lost antibiotics.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Efficacy of using a dynamic length representation vs. a fixed-length for neuroarchitecture search

Deep learning neuroarchitecture and hyperparameter search are important in finding the best configuration that maximizes learned model accuracy. However, the number of types of layers, their associated hyperparameters, and the myriad of ways to connect layers poses a significant computational challenge in discovering ideal model configurations. Here, we assess two different approaches for neuroarchitecture search for a LeNet style neural network, one that uses a fixed-length approach where there is a preset number of possible layers that can be toggled on or off via mutation, and a variable-length approach where layers can be freely added or removed via special mutation operators. We found that the variable-length implementation trained better models while discovering unusual layer configurations worth further exploration.

Coletti, Mark↗

DOE OSTI2020

Dynamic Construction, Perception, and Remodeling of Plant Cell Walls

Plant cell walls are dynamic structures that are synthesized by plants to provide durable coverings for the delicate cells they encase. They are made of polysaccharides, proteins, and other biomolecules and have evolved to withstand large amounts of physical force and to resist external attack by herbivores and pathogens but can in many cases expand, contract, and undergo controlled degradation and reconstruction to facilitate developmental transitions and regulate plant physiology and reproduction. Recent advances in genetics, microscopy, biochemistry, structural biology, and physical characterization methods have revealed a diverse set of mechanisms by which plant cells dynamically monitor and regulate the composition and architecture of their cell walls, but much remains to be discovered about how the nanoscale assembly of these remarkable structures underpins the majestic forms and vital ecological functions achieved by plants.

biofuels (including algae and biomass), bio-inspir↗

DOE OSTI2022

In-Operando XRD Study of the Effects of Water Vapor on Phase Formation in LSM/YSZ SOFC Cathodes

Here, in-operando XRD was conducted on anode supported SOFC button cells with LSM-YSZ cathodes operated at varying cathode air compositions under constant current conditions for over 1000 h. 1-hour XRD scans were continuously collected throughout the entire operation duration. By taking the sum of measured intensities from all of the collected patterns, the resulting cumulative XRD count times allowed the identification of minor phases present at concentrations as low as <0.1 wt%. In dry air with no contaminants, the cathode exhibited improving power output during the first couple of hundred hours, followed by stable operation. The effect of 3% H 2 O + 12% CO 2 on the LSM-YSZ cathode was very similar to the effect of 3% H 2 O alone, exhibiting performance degradation. Increasing contaminants in the cathode air were found to decrease the performance of the cells. In-operando XRD discovered an increase in MnO concentration and decrease in La 2 O 3 . A gradual expansion of the LSM lattice resulting from loss of Sr or O was discovered in the LSM/YSZ cathodes tested in humid cathode air. The inverse relationship between the unit cell volume and operating voltage suggests a possible correlation between Sr segregation and performance degradation in the LSM/YSZ cathodes.

25 ENERGY STORAGE↗

DOE OSTI2022

Electron Temperature Gradient Driven Transport Model for Tokamak Plasmas

A new model for electron temperature gradient (ETG) modes is developed as a component of the Multi-Mode anomalous transport module [T. Rafiq \textit{et al.,} Phys Plasmas \textbf{20}, 032506 (2013)] to predict a time dependent electron temperature profile in conventional and low aspect ratio tokamaks. This model is based on two-fluid equations that govern the dynamics of low-frequency short- and long-wavelength electromagnetic toroidal ETG driven drift modes. A low collisionality NSTX discharge is used to scan the plasma parameter dependence on the ETG real frequency, growth rate, and electron thermal diffusivity. Electron thermal transport is discovered in the deep core region where modes are more electromagnetic in nature. Several previously reported gyrokinetic trends are reproduced, including the dependencies of density gradients, magnetic shear, $\beta$ and gradient of $\beta$ $(\betap)$, collisionality, safety factor, and toroidicity, where $\beta$ is the ratio of plasma pressure to the magnetic pressure. The electron heat diffusivity associated with the ETG mode is discovered to be on a scale consistent with the experimental diffusivity determined by power balance analysis.

ETG↗

DOE OSTI2021

Mapping the combustion modes of a dual-fuel compression ignition engine

Compression-ignition (CI) engines can produce higher thermal efficiency (TE) and thus lower carbon dioxide (CO 2 ) emissions than spark-ignition (SI) engines. Unfortunately, the overall fuel economy of CI engine vehicles is limited by their emissions of nitrogen oxides (NO x ) and soot, which must be mitigated with costly, resource- and energy-intensive aftertreatment. NO x and soot could also be mitigated by adding premixed gasoline to complement the conventional, non-premixed direct injection (DI) of diesel fuel in CI engines. Several such “dual-fuel” combustion modes have been introduced in recent years, but these modes are usually studied individually at discrete conditions. This paper introduces a mapping system for dual-fuel CI modes that links together several previously studied modes across a continuous two-dimensional diagram. This system includes the conventional diesel combustion (CDC) and conventional dual-fuel (CDF) modes; the well-explored advanced combustion modes of HCCI, RCCI, PCCI, and PPCI; and a previously discovered but relatively unexplored combustion mode that is herein titled “Piston-split Dual-Fuel Combustion” or PDFC. Tests show that dual-fuel CI engines can simultaneously increase TE and lower NO x and/or soot emissions at high loads through the use of Partial HCCI (PHCCI). At low loads, PHCCI is not possible, but either PDFC or RCCI can be used to further improve NO x and/or soot emissions, albeit at slightly lower TE. These results lead to a “partial dual-fuel” multi-mode strategy of PHCCI at high loads and CDC at low loads, linked together by PDFC. Drive cycle simulations show that this strategy, when tuned to balance NO x and soot reductions, can reduce engine-out CO 2 emissions by about 1% while reducing NO x and soot by about 20% each with respect to CDC. This increases emissions of unburnt hydrocarbons (UHC), still in a treatable range (2.0 g/kWh) but five times as high as CDC, requiring changes in aftertreatment strategy.

Engineering↗

DOE OSTI2020

Comparative RNA-Seq transcriptome analyses reveal dynamic time-dependent effects of 56 Fe, 16 O, and 28 Si irradiation on the induction of murine hepatocellular carcinoma

One of the health risks posed to astronauts during deep space flights is exposure to high charge, high-energy (HZE) ions (Z > 13), which can lead to the induction of hepatocellular carcinoma (HCC). However, little is known on the molecular mechanisms of HZE irradiation-induced HCC. We performed comparative RNA-Seq transcriptomic analyses to assess the carcinogenic effects of 600 MeV/n 56 Fe (0.2 Gy), 1 GeV/n 16 O (0.2 Gy), and 350 MeV/n 28 Si (0.2 Gy) ions in a mouse model for irradiation-induced HCC. C3H/HeNCrl mice were subjected to total body irradiation to simulate space environment HZE-irradiation, and liver tissues were extracted at five different time points post-irradiation to investigate the time-dependent carcinogenic response at the transcriptomic level. Our data demonstrated a clear difference in the biological effects of these HZE ions, particularly immunological, such as Acute Phase Response Signaling, B Cell Receptor Signaling, IL-8 Signaling, and ROS Production in Macrophages. Also seen in this study were novel unannotated transcripts that were significantly affected by HZE. To investigate the biological functions of these novel transcripts, we used a machine learning technique known as self-organizing maps (SOMs) to characterize the transcriptome expression profiles of 60 samples (45 HZE-irradiated, 15 non-irradiated control) from liver tissues. A handful of localized modules in the maps emerged as groups of co-regulated and co-expressed transcripts. The functional context of these modules was discovered using overrepresentation analysis. We found that these spots typically contained enriched populations of transcripts related to specific immunological molecular processes (e.g., Acute Phase Response Signaling, B Cell Receptor Signaling, IL-3 Signaling), and RNA Transcription/Expression. A large number of transcripts were found differentially expressed post-HZE irradiation. These results provide valuable information for uncovering the differences in molecular mechanisms underlying HZE specific induced HCC carcinogenesis. Additionally, a handful of novel differentially expressed unannotated transcripts were discovered for each HZE ion. Taken together, these findings may provide a better understanding of biological mechanisms underlying risks for HCC after HZE irradiation and may also have important implications for the discovery of potential countermeasures against and identification of biomarkers for HZE-induced HCC.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Data for Metabolic Engineering of Nonmodel Yeast Issatchenkia orientalis SD108 for 5-Aminolevulinic Acid Production

Biological production of 5‐aminolevulinic acid (5‐ALA) has received growing attentionover theyears.However, thereis the tradeoff between 5‐ALA biosynthesis and cell growth because the fermentation broth will become acidic due to the production of 5‐ALA. To address this limitation, we engineered an acid‐tolerant yeast, Issatchenkia orientalis SD108, for 5‐ALA production. We first discovered that the cell growth rate of I. orientalis SD108 was boosted by 5‐ALA and its endogenous ALA synthetase (ALAS) showed higher activity than those homologs from other yeasts. The titer of 5‐ALA was improved from 28mg/L to 120‐, 150‐, and 300mg/L, by optimizing plasmid design, overexpressing a transporter, and increasing gene copy number, respectively. After redirecting the metabolic flux using the pyruvate decarboxylase (PDC) knockout strain (SD108ΔPDC) and culturing with urea, we increased the titer of 5‐ALA to 510mg/L, a 13‐fold enhancement, proving the importance of the newly identified IoALAS with higher activity and the strategic selection of nitrogen sources for knockout strains. This study demonstrates the acid‐tolerant I. orientalis SD108ΔPDC has a high potential for 5‐ALA production at a large scale in the future.

Bioproducts↗

DOE OSTI2026

Data for High Yield Production of 3-Hydroxypropionic Acid Using Issatchenkia orientalis

Biomanufacturing provides a more sustainable alternative to fossil-based chemical manufacturing. 3-Hydroxypropionic acid (3HP) is a top Department of Energy value-added chemical and precursor to bioplastics, yet cost-effective microbial production remains elusive. Here, we establish the acid-tolerant yeast Issatchenkia orientalis as a robust host for low-pH 3HP biosynthesis. Genome-scale modeling identifies the β-alanine pathway as optimal, offering the highest theoretical yield and lowest oxygen requirement. Thermodynamic analysis confirms its favorability under acidic conditions. Using sequence similarity network analysis, we discover highly active aspartate 1-decarboxylase (PAND), β-alanine-pyruvate aminotransferase (BAPAT), and 3HP dehydrogenase (YDFG), which significantly improve the pathway efficiency. Next, to further elevate the production, pathway optimization through multi-copy PAND integration, byproduct elimination (knockouts of pyruvate decarboxylase and glycerol-3-phosphate dehydrogenase), and reinforcement of aspartate flux by overexpression of pyruvate carboxylase and aspartate amino transferase improves the titer to 29 g/L in shake flasks. Fed-batch fermentation at pH 4 with low-cost corn steep liquor medium further increases the production to 92 g/L with 0.7 g/g yield and 0.55 g/L/h productivity. Techno-economic analysis indicates that such performance could potentially enable a financially viable process for sustainable acrylic acid production. This work establishes I. orientalis as a next-generation platform for cost-effective 3HP production and paves the way toward industrial commercialization.

Bioproducts↗

DOE OSTI2023

Computationally-driven discovery of second harmonic generation in EuBa 3 (B 3 O 6 ) 3 through inversion symmetry breaking

Nonlinear optical (NLO) crystals with superior properties are significant for advancing laser technologies and applications. Introducing rare earth metals to borates is a promising and effective way to modify the electronic structure of a crystal to improve its optical properties in the visible and ultraviolet range. In this work, we computationally discover inversion symmetry breaking in EuBa 3 (B 3 O 6 ) 3 , which was previously identified as centric, and demonstrate noncentrosymmetry via synthesizing single crystals for the first time by the floating zone method. We determine the correct space group to be P 6¯. The material has a large direct bandgap of 5.56 eV and is transparent down to 250 nm. The complete anisotropic linear and nonlinear optical properties were also investigated with a d 11 of ∼0.52 pm/V for optical second harmonic generation. Further, it is Type I and Type II phase matchable. This work suggests that rare earth metal borates are an excellent crystal family for exploring future deep ultraviolet (DUV) NLO crystals. It also highlights how first principles computations combined with experiments can be used to identify noncentrosymmetric materials that have been wrongly assigned to be centrosymmetric.

He, Jingyang (ORCID:0000000238863659)↗

DOE OSTI2023

Leveraging Application Data Constraints to Optimize Database-Backed Web Applications

Exploiting the relationships among data is a classical query optimization technique. As persistent data is increasingly being created and maintained programmatically, prior work that infers data relationships from data statistics misses an important opportunity. We present Coco, the first tool that identifies data relationships by analyzing database-backed applications. Once identified, Coco leverages the constraints to optimize the application's physical design and query execution. Instead of developing a fixed set of predefined rewriting rules, Coco employs an enumerate-test-verify technique to automatically exploit the discovered data constraints to improve query execution. Each resulting rewrite is provably equivalent to the original query. Using 14 real-world web applications, our experiments show that Coco can discover numerous data constraints from code analysis and improve real-world application performance significantly.

Computer Science↗