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At least 649 records · Page 36

1,8-Dihydroxy Naphthalene—A New Building Block for the Self-Assembly with Boronic Acids and 4,4′-Bipyridine to Stable Host–Guest Complexes with Aromatic Hydrocarbons

The new Lewis acid–base adducts of general formula X(nad)B←NC5H4-C5H4N→B(nad)X [nad = 1,8-O2C10H6, X = C6H5 (2c), 3,4,5-F3-C6H2 (2d)] were synthesized in high yields via reactions of 1,8-dihydroxy naphthalene [nadH2] and 4,4′-bipyridine with the aryl boronic acids C6H5B(OH)2 and 3,4,5-F3-C6H2B(OH)2, respectively, and structurally characterized by multi-nuclear NMR spectroscopy and SCXRD. Self-assembled H-shaped Lewis acid–base adduct 2d proved to be effective in forming thermally stable host–guest complexes, 2d × solvent, with aromatic hydrocarbon solvents such as benzene, toluene, mesitylene, aniline, and m-, p-, and o-xylene. Crystallographic analysis of these solvent adducts revealed host–guest interactions to primarily occur via π···π contacts between the 4,4′-bipyridyl linker and the aromatic solvents, resulting in the formation of 1:1 and 1:2 host–guest complexes. Thermogravimetric analysis of the isolated complexes 2d × solvent revealed their high thermal stability with peak temperatures associated with the loss of solvent ranging from 122 to 147 °C. 2d, when self-assembled in an equimolar mixture of m-, p-, and o-xylene (1:1:1), preferentially binds to o-xylene. Collectively, these results demonstrate the ability of 1,8-dihydroxy naphthalene to serve as an effective building block in the selective self-assembly to supramolecular aggregates through dative covalent N→B bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded-aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consist of 80- channel detector plane histograms that accumulate photon counts over periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey data set between 14 and 195 keV. Survey data comprise >90% of all BAT data by volume and allow for the tracking of long-term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey data set has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis Python package, a wrapper for HEASoftpy, which provides a modern, opensource pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources, including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the Python code and exemplify its usefulness and accuracy by analyzing survey data of the Crab Nebula, NGC 2992, and a previously uncataloged MAXI transient. The BatAnalysis package allows for ~18 yr of BAT survey data to be used in a systematic way to study a large variety of astrophysical sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded-aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consist of 80-channel detector plane histograms that accumulate photon counts over periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey data set between 14 and 195 keV. Survey data comprise >90% of all BAT data by volume and allow for the tracking of long-term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey data set has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis Python package, a wrapper for HEASoftpy, which provides a modern, open-source pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources, including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the Python code and exemplify its usefulness and accuracy by analyzing survey data of the Crab Nebula, NGC 2992, and a previously uncataloged MAXI transient. The BatAnalysis package allows for ~18 yr of BAT survey data to be used in a systematic way to study a large variety of astrophysical sources.

79 ASTRONOMY AND ASTROPHYSICS↗

Statistical and sensitivity analysis of failing rods in EPR LBLOCA

A statistical fuel failure analysis procedure has been developed, and is now applied in full scale to a large break loss-of-coolant accident (LBLOCA) scenario in EPR-type nuclear power plant. The goal is to statistically determine the number of failing fuel rods. It is also important to bring out the underlying causes for rod failures, and therefore a sensitivity analysis procedure for the preceding complex calculation chain is outlined and adopted. In order to produce a statistically reliable estimation on the number of failing rods, a large number of simulations are required. In the analysis, single rods are simulated with the coupled fuel performance - thermal hydraulics code FRAPTRAN-GENFLO. The statistically varied factors are divided into global and local by their range of influence. Transient thermal hydraulic and power history boundary conditions and model parameters are global and affect all the rods. Fuel rod manufacturing parameters and other rod position related factors are local and are related to a certain rod. The number of global scenarios is 59 as dictated by the Wilks' formula, and 1000 randomly sampled rods are simulated in each scenario. The thermal hydraulic and transient power boundary conditions for the fuel performance code are calculated with a statistical version of the system code APROS. The steady-state irradiation histories are simulated with FRAPCON, and the steady-state power histories used as boundary conditions for FRAPCON are obtained from SIMULATE calculations. Thus, a multistage calculation chain is required to consolidate the procedure. As an outcome, in the worst global scenario, 1.4% of the simulated rods failed. It can be concluded that the Finnish safety regulations, i.e. max. 10% of the rods allowed to fail, are met. In order to find out which input parameters have significance to the outcome of the analysis, a sensitivity analysis is done. At the moment, only the worst global scenario is considered but later on it is possible to include also the sensitivities of the global factors. Due to complexity of the existing data, first the relevant input parameters for the sensitivity analysis have to be specified. Data visualization with a cobweb graph is used for the screening. Then, selected sensitivity measures are calculated between the chosen input and output parameters. The sensitivity indices calculated are the Borgonovo's delta measure, the first order Sobol sensitivity index, and squared Pearson correlation coefficients. The first mentioned is a novelty in this context. As an outcome, the most relevant parameters with respect to the cladding integrity were determined to be the decay heat power during the transient, the thermal hydraulic conditions in the rod's location in the reactor, and the steady-state irradiation history of the rod as represented in this analysis by the rod burnup. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Temporal Summary Images: An Approach to Narrative Visualization via Interactive Annotation Generation and Placement

Visualization is a powerful technique for analysis and communication of complex, multidimensional, and time-varying data. However, it can be difficult to manually synthesize a coherent narrative in a chart or graph due to the quantity of visualized attributes, a variety of salient features, and the awareness required to interpret points of interest (POIs). We present Temporal Summary Images (TSIs) as an approach for both exploring this data and creating stories from it. As a visualization, a TSI is composed of three common components: (1) a temporal layout, (2) comic strip-style data snapshots, and (3) textual annotations. To augment user analysis and exploration, we have developed a number of interactive techniques that recommend relevant data features and design choices, including an automatic annotations workflow. As the analysis and visual design processes converge, the resultant image becomes appropriate for data storytelling. For validation, we use a prototype implementation for TSIs to conduct two case studies with large-scale, scientific simulation datasets.

97 MATHEMATICS AND COMPUTING↗

Reinterpreting π-stacking

The nature of π–π interactions has long been debated. The term “π-stacking” is considered by some to be a misnomer, in part because overlapping π-electron densities are thought to incur steric repulsion, and the physical origins of the widely-encountered “slip-stacked” motif have variously been attributed to either sterics or electrostatics, in competition with dispersion. Here, we use quantum-mechanical energy decomposition analysis to investigate π–π interactions in supramolecular complexes of polycyclic aromatic hydrocarbons, ranging in size up to realistic models of graphene, and for comparison we perform the same analysis on stacked complexes of polycyclic saturated hydrocarbons, which are cyclohexane-based analogues of graphane. Our results help to explain the short-range structure of liquid hydrocarbons that is inferred from neutron scattering, trends in melting-point data, the interlayer separation of graphene sheets, and finally band gaps and observation of molecular plasmons in graphene nanoribbons. Analysis of intermolecular forces demonstrates that aromatic π–π interactions constitute a unique and fundamentally quantum-mechanical form of non-bonded interaction. Not only do stacked π–π architectures enhance dispersion, but quadrupolar electrostatic interactions that may be repulsive at long range are rendered attractive at the intermolecular distances that characterize π-stacking, as a result of charge penetration effects. The planar geometries of aromatic sp 2 carbon networks lead to attractive interactions that are “served up on a molecular pizza peel”, and adoption of slip-stacked geometries minimizes steric (rather than electrostatic) repulsion. The slip-stacked motif therefore emerges not as a defect induced by electrostatic repulsion but rather as a natural outcome of a conformational landscape that is dominated by van der Waals interactions (dispersion plus Pauli repulsion), and is therefore fundamentally quantum-mechanical in its origins. This reinterpretation of the forces responsible for π-stacking has important implications for the manner in which non-bonded interactions are modeled using classical force fields, and for rationalizing the prevalence of the slip-stacked π–π motif in protein crystal structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fluid dynamic simulation and analysis of water-cooling systems for the Electron-Ion Collider

The Electron-Ion Collider is the newest large-scale project at Brookhaven National Laboratory. The collider’s purpose is to provide further advancements in the knowledge of the universe’s origin by accelerating particles near the speed of light. Our project for this 3.8 km ring was to create a thermal hydraulic steady-state simulation design of the water-cooling system to be cost-effective and energy efficient, as envisioned by Charlie Foltz, the EIC Infrastructure Division Director. The system would include a supply and return header, which cools several thousand components of the ring. The water would then be returned and cooled down using a system of cooling towers and plate and frame heat exchangers. Due to the size of the system and the complexity of the network analysis, a fluid dynamic simulation software, AFT Fathom, was used. Since previous methods of maintaining systems relied on building upon smaller real-life models and implementing empirical data, this flow model was unique and first of a kind in the domain of accelerator design, construction and operation. Therefore, our hydraulic team piloted a new method to perform network analysis on a large scale cooling system. We successfully created several test scenarios for system behavior in a shorter time compared to the method of performing hand calculations. Cooling specifications for heat rejection, pressure drop, flow rate, and pipe sizing were changed based on the individual systems of the vacuum, radio frequency (RF), magnet and power supply, and cryogenics sections. Finally, we used DOE guidelines to perform life-cycle cost analysis with net present value and carbon saving analysis on the systems where pipe size could be optimized.

43 PARTICLE ACCELERATORS↗

A Solid of Revolution Time Study using COG11.1 and MCNP6.1

The performance of two continuous energy Monte Carlo transport codes, COG11.1 and MCNP6.1, has been compared for the {sup 239}Pu Jezebel Benchmark using cross sections based on the ENDF/B-VII.1 evaluated nuclear data library. The purpose of this study is to determine the length of time it takes each code to complete a series of criticality calculations, using two different methods to model a solid of revolution. A solid of revolution is essential in many fields of engineering and mathematics, and has been a standard feature in computer-aided design and manufacturing since the 1970's. In the field of criticality safety, a solid of revolution can be used to reproduce and simplify complex engineering drawings and systems that would otherwise require excessive use of geometric primitives and computational resources to achieve a comparable level of fidelity. There are two basic methods to model a solid of revolution: Method 1 (COG) specifies a set of x-y pairs or polar coordinates and rotate the curve about the x-axis. Method 2 (COG and MCNP) creates a set of end-to-end conical frustums and/or cylinders. Method 1 is only available in COG and can be implemented using one surface and sector specification. Method 2 can be implemented in both COG and MCNP. This time study was initially conceived as a result of criticality safety analysis performed for a complex system with a high degree of rotational symmetry. Each COG input deck typically took 1-2 days to run in serial mode. COG input decks were then converted to MCNP format and run on the same computer cluster. Instead of expected 1-2 day runtimes, it took MCNP6.1 more than one week to complete each run. Since MCNP typically runs faster than many codes, these lengthy runtimes were considered unusual. This study attempts to investigate the runtime discrepancy between the two codes. The methods and benchmark in this time study were selected to provide a consistent, generalized approach to modeling an arbitrary solid of revolution. While there are many different ways to model the {sup 239}Pu Jezebel Benchmark, the focus of this study is on investigating the practical difference between the two basic methods to model a surface of revolution. Throughout this study, the only code that maintains reasonably low runtimes is COG11.1 (Method 1). Based on the observed performance of each code and method, it is likely that the divergent runtimes are the result of tracking particles across planes that lie between conical frustums, as opposed to defining the object boundary as a single surface. Slight fluctuations in graphed results were also observed, due to random sampling and CPU loading. This was confirmed by re-running input decks and comparing average runtimes to a preliminary curve fit. From the perspective of a criticality safety analyst, the results of this study are expected to contribute towards understanding one of the practical trade-offs between codes and methods as they apply to real-world analysis. Ultimately, it's about choosing the right tool for the job.

97 MATHEMATICS AND COMPUTING↗

A Transductive Graph Neural Network learning for Grid Resilience Analysis

Power grids are critical infrastructures that require robust resilience analysis to ensure reliable and uninterrupted electricity supply. Traditional simulation-based methods for grid resilience analysis suffer from computational complexity and limited ability to capture the full spectrum of potential disruptions. This paper presents a novel approach to enhance grid resilience by leveraging transductive graph neural network (GNN) learning to identify critical nodes and links. By leveraging the graph structure and system features, GNNs effectively learn resilience metrics and accurately identify critical nodes based on actual grid operational behavior. The efficacy of the proposed approach is demonstrated through case studies on node criticality scoring and critical node/line identification in cascading outage scenarios. The results highlight the advantages of learning-based methods over traditional simulation-based approaches and their potential to revolutionize grid resilience analysis. The contributions of this paper include a graph-based scalable approach for fast cascading analysis, an inductive formulation for training GNN models, and a transfer learning-based approach to scale the model to largescale power systems.

grid resilience, graph neural networks, transducti↗

Discovery of FoTO1 and Taxol genes enables biosynthesis of baccatin III

Abstract Plants make complex and potent therapeutic molecules 1,2 , but sourcing these molecules from natural producers or through chemical synthesis is difficult, which limits their use in the clinic. A prominent example is the anti-cancer therapeutic paclitaxel (sold under the brand name Taxol), which is derived from yew trees (Taxusspecies) 3 . Identifying the full paclitaxel biosynthetic pathway would enable heterologous production of the drug, but this has yet to be achieved despite half a century of research 4 . WithinTaxus’ large, enzyme-rich genome 5 , we suspected that the paclitaxel pathway would be difficult to resolve using conventional RNA-sequencing and co-expression analyses. Here, to improve the resolution of transcriptional analysis for pathway identification, we developed a strategy we term multiplexed perturbation × single nuclei (mpXsn) to transcriptionally profile cell states spanning tissues, cell types, developmental stages and elicitation conditions. Our data show that paclitaxel biosynthetic genes segregate into distinct expression modules that suggest consecutive subpathways. These modules resolved seven new genes, allowing a de novo 17-gene biosynthesis and isolation of baccatin III, the industrial precursor to Taxol, inNicotiana benthamianaleaves, at levels comparable with the natural abundance inTaxusneedles. Notably, we found that a nuclear transport factor 2 (NTF2)-like protein, FoTO1, is crucial for promoting the formation of the desired product during the first oxidation, resolving a long-standing bottleneck in paclitaxel pathway reconstitution. Together with a new β-phenylalanine-CoA ligase, the eight genes discovered here enable the de novo biosynthesis of 3’-N-debenzoyl-2’-deoxypaclitaxel. More broadly, we establish a generalizable approach to efficiently scale the power of co-expression analysis to match the complexity of large, uncharacterized genomes, facilitating the discovery of high-value gene sets.

Science & Technology - Other Topics↗

Structure-Based Exciton Hamiltonian and Dynamics for the Reconstituted Wild-type CP29 Protein Antenna Complex of the Photosystem II

Here we provide an analysis of the pigment composition of reconstituted wild type CP29 complexes. The obtained stoichiometry of 9 ± 0.6 Chls a and 3 ± 0.6 Chls b per complex, with some possible heterogeneity in the carotenoid binding, is in agreement with 9 Chls a and 3.5 Chls b revealed by the modeling of low-temperature optical spectra. We find that ~50% of Chl b614 is lost during the reconstitution/purification procedure, while Chls a are almost fully retained. The excitonic structure and the nature of the low-energy (low-E) state(s) are addressed via simulations (using Redfield theory) of 5 K absorption and fluorescence/nonresonant hole-burned (NRHB) spectra obtained at different excitation/burning conditions. We show that, depending on laser excitation frequency, reconstituted complexes display two (independent) low-E states (i.e., the A and B traps) with different NRHB and emission spectra. The red-shifted state A near 682.4 nm is assigned to a minor (~10%) subpopulation (Sub. II) that most likely originates from an imperfect local folding occurring during protein reconstitution. Its lowest energy state A (localized on Chl a604) is easily burned with λ B = 488.0 nm and has a red-shifted florescence origin band near 683.7 nm that is not observed in native (isolated) complexes. Prolonged burning by 488.0 nm light reveals a second low-E trap at 680.2 nm (state B) with a fluorescence origin-band ~681 nm which is also observed when using a direct lowfluence excitation near 650 nm. The latter state is mostly delocalized over the a611, a612, a615 Chl trimer, and corresponds to the lowest energy state of the major (~90%) subpopulation (Sub. I) which exhibits a lower hole-burning quantum yield. Thus, we suggest that major Sub. I correspond to the native folding of CP29, whereas the red-shift of the Chl a604 site energy observed in the minor Sub. II occurs only in reconstituted complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterization of genetic variability of Venezuelan equine encephalitis viruses

Venezuelan equine encephalitis virus (VEEV) is a mosquito-borne alphavirus that has caused large outbreaks of severe illness in both horses and humans. New approaches are needed to rapidly infer the origin of a newly discovered VEEV strain, estimate its equine amplification and resultant epidemic potential, and predict human virulence phenotype. We performed whole genome single nucleotide polymorphism (SNP) analysis of all available VEE antigenic complex genomes, verified that a SNP-based phylogeny accurately captured the features of a phylogenetic tree based on multiple sequence alignment, and developed a high resolution genome-wide SNP microarray. We used the microarray to analyze a broad panel of VEEV isolates, found excellent concordance between array- and sequence-based SNP calls, genotyped unsequenced isolates, and placed them on a phylogeny with sequenced genomes. The microarray successfully genotyped VEEV directly from tissue samples of an infected mouse, bypassing the need for viral isolation, culture and genomic sequencing. Lastly, we identified genomic variants associated with serotypes and host species, revealing a complex relationship between genotype and phenotype.

59 BASIC BIOLOGICAL SCIENCES↗

Data mining for better material synthesis: The case of pulsed laser deposition of complex oxides

The pursuit of more advanced electronics, and finding solutions to energy needs often hinges upon the discovery and optimization of new functional materials. However, the discovery rate of these materials is alarmingly low. Much of the information that could drive this rate higher is scattered across tens of thousands of papers in the extant literature published over several decades but is not in an indexed form, and cannot be used in entirety without substantial effort. Many of these limitations can be circumvented if the experimentalist has access to systematized collections of prior experimental procedures and results. Here, we investigate the property-processing relationship during growth of oxide films by pulsed laser deposition. To do so, we develop an enabling software tool to (1) mine the literature of relevant papers for synthesis parameters and functional properties of previously studied materials, (2) enhance the accuracy of this mining through crowd sourcing approaches, (3) create a searchable repository that will be a community-wide resource enabling material scientists to leverage this information, and (4) provide through the Jupyter notebook platform, simple machine-learning-based analysis to learn the complex interactions between growth parameters and functional properties. Here, the results allow visualization of growth windows, trends and outliers, which can serve as a template for analyzing the distribution of growth conditions, provide starting points for related compounds and act as a feedback for first-principles calculations. Such tools will comprise an integral part of the materials design schema in the coming decade.

36 MATERIALS SCIENCE↗

A Guide to Nonaqueous Electrochemistry of f-Element Complexes

Electrochemistry is a powerful tool for assessing and understanding the redox chemistry of molecular complexes. Cyclic voltammetry enables the f-element community to study molecules in unusually high or low oxidation states, which potentially pose important broad-scope questions of electronic structure. In the pursuit of boundary-pushing compounds, reactive air- and moisture-sensitive species are often encountered, which can be challenging to characterize, especially when they are chemically incompatible with certain solvents, electrolytes, or electrodes or when their potentials lie outside of common electrochemical windows. Nonaqueous solvents and pseudo reference electrodes complicate many of the standard practices in acquiring high-quality and reproducible electrochemical data. This guide presents a detailed discussion of selecting appropriate cell conditions and referencing and addresses metrics for evaluating electrochemical and chemical reversibility. These methodological approaches have been extended to best practices for the electrochemical analysis of radioactive transuranic complexes.

Electrodes↗

Corrosion Inhibition Study of Mg-Nd-Y High Strength Magnesium Alloy Using Organic Inhibitor

A study on corrosion inhibition mechanism has been performed on rare earth containing WE43 magnesium alloy in 3.5 wt.% NaCl containing 8-hydroxyquinoline (HQ). After an initial increase in corrosion rate due to the formation of sparingly soluble MgQ{sub 2} complex, it was found to decrease owing to inhibition effect of the complex. Scanning electrochemical microscopic analysis showed a decrease in corrosion currents and enhanced resistance to pitting corrosion was observed for WE43 samples in the presence of HQ after an exposure of 48 h. With time, the MgQ{sub 2} thus generated formed a protective layer on the Mg alloy surface to prevent further corrosion. The corrosion rate of WE43 samples decreased by ~ 50% in HQ containing medium after a constant exposure of 28 days (from ~ 0.22 mg/cm{sup 2} day in no HQ to ~ 0.11 mg/cm{sup 2} day in HQ). For the WE43 samples in the presence of HQ, formation of MgO and MgQ{sub 2} was detected by x-ray photoelectron spectroscopy and x-ray diffraction. Shallower and smaller pits appeared on the magnesium alloy with HQ in the solution as compared to deeper and larger pits on the samples with no HQ in the solution. The significance of metal-complexing organic agent, hydroxyquinoline, in initial acceleration and subsequent prevention of Mg corrosion via protective MgQ{sub 2} complex layer formation is demonstrated.

36 MATERIALS SCIENCE↗

Understanding the Electronic Structure of 4d Metal Complexes: From Molecular Spinors to L-Edge Spectra of a di-Ru Catalyst

L{sub 2,3}-edge X-ray absorption spectroscopy (XAS) has demonstrated unique capabilities for the analysis of the electronic structure of di-Ru complexes such as the blue dimer cis,cis-[Ru{sub 2}{sup III}O(H{sub 2}O){sub 2}(bpy){sub 4}]{sup 4+} water oxidation catalyst. Spectra of the blue dimer and the monomeric [Ru(NH{sub 3}){sub 6}]{sup 3+} model complex show considerably different splitting of the Ru L{sub 2,3} absorption edge, which reflects changes in the relative energies of the Ru 4d orbitals caused by hybridization with a bridging ligand and spin-orbit coupling effects. To aid the interpretation of spectroscopic data, we developed a new approach, which computes L{sub 2,3}-edges XAS spectra as dipole transitions between molecular spinors of 4d transition metal complexes. This allows for careful inclusion of the spin-orbit coupling effects and the hybridization of the Ru 4d and ligand orbitals. The obtained theoretical Ru L{sub 2,3}-edge spectra are in close agreement with experiment. Critically, existing single-electron methods (FEFF, FDMNES) broadly used to simulate XAS could not reproduce the experimental Ru L-edge spectra for the [Ru(NH{sub 3}){sub 6}]{sup 3+} model complex nor for the blue dimer, while charge transfer multiplet (CTM) calculations were not applicable due to the complexity and low symmetry of the blue dimer water oxidation catalyst. We demonstrated that L-edge spectroscopy is informative for analysis of bridging metal complexes. The developed computational approach enhances L-edge spectroscopy as a tool for analysis of the electronic structures of complexes, materials, catalysts, and reactive intermediates with 4d transition metals.

Alperovich, Igor↗

An Observation-Driven Agent-Based Modeling and Analysis Framework for C. elegans Embryogenesis

With cutting-edge live microscopy and image analysis, biologists can now systematically track individual cells in complex tissues and quantify cellular behavior over extended time windows. Computational approaches that utilize the systematic and quantitative data are needed to understand how cells interact in vivo to give rise to the different cell types and 3D morphology of tissues. An agent-based, minimum descriptive modeling and analysis framework is presented in this paper to study C. elegans embryogenesis. The framework is designed to incorporate the large amounts of experimental observations on cellular behavior and reserve data structures/interfaces that allow regulatory mechanisms to be added as more insights are gained. Observed cellular behaviors are organized into lineage identity, timing and direction of cell division, and path of cell movement. The framework also includes global parameters such as the eggshell and a clock. Division and movement behaviors are driven by statistical models of the observations. Data structures/interfaces are reserved for gene list, cell-cell interaction, cell fate and landscape, and other global parameters until the descriptive model is replaced by a regulatory mechanism. This approach provides a framework to handle the ongoing experiments of single-cell analysis of complex tissues where mechanistic insights lag data collection and need to be validated on complex observations.

Science & Technology - Other Topics↗

Unraveling the discontinuous plastic flow of a Co-Cr-Fe-Ni-Mo multiprincipal-element alloy at deep cryogenic temperatures

We report an analysis of the discontinuous plastic flow of a multiprincipal-element alloy, Co 17.5 Cr 12.5 Fe 55 Ni 10 Mo 5 (atomic percent, at. %), in the temperature range of 0.5–4.2 K showing serrated deformation curves. Using the analytical techniques, we studied the statistics of the stress drops associated with the unstable plastic flow. The analysis showed that the complexity and heterogeneity of a discontinuous plastic flow were reduced when the temperature was lowered. This behavior was associated with the effects of dynamic recovery and adiabatic heating on the dislocation-density evolution.

36 MATERIALS SCIENCE↗