Structural analyses of NudT16-ADP-ribose complexes direct rational design of mutants with improved processing of poly(ADP-ribosyl)ated proteins
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Synchrotron characterization techniques provide some of the most powerful tools for the study of film structure and chemistry. The brilliance and tunability of the Advanced Photon Source allow access to scattering and spectroscopic techniques unavailable with in-house laboratory setups and provide the opportunity to probe various atomic layer deposition (ALD) processes in situ starting at the very first deposition cycle. Here, we present the design and implementation of a portable ALD instrument which possesses a modular reactor scheme that enables simple experimental switchover between various beamlines and characterization techniques. As first examples, we present in situ results for (1) X-ray surface scattering and reflectivity measurements of epitaxial ZnO ALD on sapphire, (2) grazing-incidence small angle scattering of MnO nucleation on silicon, and (3) grazing-incidence X-ray absorption spectroscopy of nucleation-regime Er{sub 2}O{sub 3} ALD on amorphous ALD alumina and single crystalline sapphire.
The synthesis and experimental/theoretical characterization of a new series of electron-transporting copolymers based on the naphthalene bis(4,8-diamino-1,5-dicarboxyl)amide (NBA) building block are reported. Comonomers are designed to test the emergent effects of manipulating backbone torsional characteristics, and density functional theory (DFT) analysis reveals the key role of backbone conformation in optimizing electronic delocalization and transport. The NBA copolymer conformational and electronic properties are characterized using a broad array of molecular/macromolecular, thermal, optical, electrochemical, and charge transport techniques. All NBA copolymers exhibit strongly aggregated morphologies with significant nanoscale order. Copolymer charge transport properties are investigated in thin-film transistors and exhibit excellent electron mobilities ranging from 0.4 to 4.5 cm(2) V-1 s(-1). Importantly, the electron transport efficiency correlates with the film mesoscale order, which emerges from comonomer-dependent backbone planarity and extension. These results illuminate the key NBA building block structure-morphology-bulk property design relationships essential for processable, electronics-applicable high-performance polymeric semiconductors.
Nuclear fission is the splitting of a heavy nucleus into two or more fragments, a process that releases a substantial amount of energy. It is ubiquitous in modern applications, critical for national security, energy generation and reactor safeguards. Fission also plays an important role in understanding the astrophysical formation of elements in the universe. Eighty years after the discovery of the fission process, its theoretical understanding from first principles remains a great challenge. In this paper, we present promising new approaches to make more accurate predictions of fission observables.
The US Department of Energy’s (DOE’s) Advanced Manufacturing Office held the virtual workshop entitled “Thermal Process Intensification: Transforming the Way Industry Uses Thermal Process Energy” in November and December 2020. The workshop brought together participants from universities/laboratories, industries, equipment manufacturers, technology vendors, nongovernmental organizations, and subject-matter experts to discuss transformative technologies and strategies to substantially improve the performance (e.g., energy productivity, thermal efficiency, reduced greenhouse gas [GHG] emissions, reduced number of process steps) of thermal processing systems in the industrial sector. The US industrial sector accounts for 32% of the nation’s primary energy use (including feedstocks), and refining, chemicals, pulp and paper, iron and steel, and food products represent the top energy-consuming sectors. Thermal processing or process heating represents the largest energy use category; it accounts for 63% of all energy use in manufacturing. Additionally, thermal processing is the largest contributor of carbon dioxide (CO2) generation, resulting from combustion of fuels and process related chemical reactions, such as in the case of cement and lime production. The challenge of achieving net-zero industrial GHG emissions is colossal considering the established industrial base that depends mainly on carbon-based processes and energy sources; the time frame and cost to replace carbon-based energy sources and feedstocks; and the long-term outlook for development with large-scale adaptation of alternative non carbon–based technologies. The goals of the DOE Advanced Manufacturing Office Thermal Process Intensification Workshop were as follows: (1) Identify R&D gaps and opportunities to facilitate transformative improvement in industrial thermal processes beyond current technologies and allow for entirely new methods for processing materials; (2) Gain insight into new and innovative approaches to thermally intensify processes, reduce heat demand, harness waste heat, and use fuels and hydrocarbon feedstocks more efficiently; (3) Identify the R&D pathways to thermal process intensification (TPI) with the highest potential for impact and adoption by the industrial sector; (4) Define areas of research, development, and demonstration (RD&D) activities to accelerate development and application of emerging and transformative technologies to intensify thermal processes in industry. The scope and focus of the workshop were defined to meet these goals. Based on the available data for energy use and GHG emissions, the industries that collectively use more than 80% of the total process heating energy consumption were selected as primary focus areas. The chosen industries were combined into the following four groups based on similarities in their thermal processes: high-temperature metal processing (iron and steel industry, alumina-aluminum industry); high-temperature nonmetal and mineral processing (cement and glass industry); medium- to low-temperature thermal processing (food processing and pulp and paper industry as part of forest products sector); and hydrocarbon processing (petroleum refining and chemical industry). Furthermore, all potential TPI technologies associated with the processes defined were considered as part of the workshop. Different types of TPI technologies possible in industrial in the document.
Process-based models have been widely used for hydrologic modeling, and it is a common practice to use sensitivity analysis methods for excluding non-influential hydrologic processes from further investigation and/or model improvement. This study develops a new method called multi-model absolute difference-based sensitivity (MMADS) analysis method to screen non-influential system processes and parameters. MMADS is conceptually similar to the Morris method for addressing parametric uncertainty, but has a unique feature to address both process model uncertainty (i.e., a process may be represented by multiple process models) and process model parameter uncertainty (i.e., parameters associated with a process model are random). MMADS first evaluates absolute differences of a quantity of interest (i.e., a system model output) by varying process models and/or process model parameter values, and then calculates the mean and variance of the differences for investigating process influence. The mean measures overall influence of the process on the quantity of interest, and the variance estimates influence of nonlinear effects of the process and/or its interactions with other processes. MMADS is an extension of the Morris method from a parameter space to a joint parameter-model space for explicitly addressing both process model uncertainty and model parameter uncertainty. The performance of MMADS is evaluated by using two numerical experiments. One experiment is based on Sobol’s G*-function with ten product elements, and has analytical solutions of the MMADS mean and variance of absolute differences. The other experiment is for groundwater flow modeling which considers three processes (i.e., recharge, geology, and snowmelt) that interact with each other. Finally, results indicate that MMADS is computationally efficient and can identify non-influential processes of complex hydrological systems.
Productivity and Sustainability Improvement Planning (PSIP) is a lightweight, iterative workflow that allows software development teams to identify development bottlenecks and track progress to overcome them. In this paper, we present an overview of PSIP and how it compares to other software process improvement (SPI) methodologies, and provide two case studies that describe how the use of PSIP led to successful improvements in team effectiveness and efficiency.
Momentary cessation refers to an inverter control mode. When the inverter terminal voltage falls below (or exceeds) a certain level, the inverter ceases to output any current, but attempts to maintain (or quickly regain) phase-locked loop synchronization to allow for quick reinjection of current when the voltage recovers to a certain point. This paper presents a photovoltaic (PV) momentary cessation model developed in PSS/E. Simulations are presented for a high voltage transmission line fault contingency in the Hawaiian island of Oahu power system on a validated PSS/E model, modified to include a custom distributed PV inverter model, and different near-future distributed PV penetration levels. Simulations for the island power system include different penetration levels of PV, and different recovery times (ramp rates and delays) after momentary cessation. The results indicate that during low voltage events, such as faults, momentary cessation can produce severe under frequency events, causing significant load shed and shortly thereafter, in some cases, over frequency events that cause generation to trip offline. The problem is exacerbated with higher penetration levels of PV. If momentary cessation is used (as is typically the case for distribution-connected resources), the recovery process after momentary cessation should be carefully considered to minimize impacts to bulk power system stability.
Context. The astrophysical origin of the rapid neutron-capture process (r-process), responsible for producing roughly half of the elements heavier than iron, remains uncertain. Detailed chemical signatures from the oldest, most metal-poor stars, which act as fossil records of the earliest nucleosynthesis events, can be used to identify the dominant r-process sites. Aims. We present a homogeneous chemical abundance analysis of ten r-process element-enhanced stars. These old and metal-poor stars are strongly enriched in r-process elements with minimal contamination from other nucleosynthetic sources. By focusing on this chemically pure sample, we aim to investigate intrinsic variations in the r-process abundance patterns and explore their implications for the nature and potential diversity of r-process sites. Methods. We performed a detailed chemical abundance analysis of high-resolution, high-signal-to-noise spectra. For each star, we inspected over 1400 individual absorption lines using a combination of equivalent width measurements and spectral synthesis. The analysis was conducted under the assumption of 1D local thermodynamic equilibrium and employing the MOOG radiative transfer code. Results. We derived abundances for 54 chemical species, including 29 neutron-capture (n-capture) elements, covering the full mass range of the r-process abundance pattern. A kinematic analysis reveals that stars likely originated from ten kinematically distinct systems. Based on this assumption, we used the sample to probe the maximum variation expected from ten independent r-process nucleosynthesis events and computed the intrinsic dispersion of each element relative to Zr and Eu for the light and heavy r-process elements, respectively. This exercise resulted in a remarkably low cosmic scatter across the ten r-process sites enriching these stars; for the rare earth and third peak elements, for example, we find σ [La/Eu] = 0.08 and σ [Os/Eu] = 0.11 dex, while the scatter between light and heavy elements, σ [Zr/Eu] , is slightly higher at 0.18 dex. Conclusions. The elemental abundance patterns across the ten independent r-process sites show remarkably small cosmic dispersions. This minimal dispersion suggests a high degree of uniformity in r-process yields across diverse astrophysical environments.
Use of corn fractionation techniques in dry grind process increases the number of coproducts, enhances their quality and value, generates feedstock for cellulosic ethanol production and potentially increases profitability of the dry grind process. The aim of this study is to develop process simulation models for eight different wet and dry corn fractionation techniques recovering germ, pericarp fiber and/or endosperm fiber, and evaluate their techno-economic feasibility at the commercial scale. Ethanol yields for plants processing 1113.11 MT corn/day were 37.2 to 40 million gal for wet fractionation and 37.3 to 31.3 million gal for dry fractionation, compared to 40.2 million gal for conventional dry grind process. Capital costs were higher for wet fractionation processes ($92.85 to $97.38 million) in comparison to conventional ($83.95 million) and dry fractionation ($83.35 to $84.91 million) processes. Due to high value of coproducts, ethanol production costs in most fractionation processes ($1.29 to $1.35/gal) were lower than conventional ($1.36/gal) process. Internal rate of return for most of the wet (6.88 to 8.58%) and dry fractionation (6.45 to 7.04%) processes was higher than the conventional (6.39%) process. Wet fractionation process designed for germ and pericarp fiber recovery was most profitable among the processes.
Commercial electrical conductor wires are currently produced from aluminum alloys by multi-step deformation processing involving rolling and drawing. These processes typically require 10 to 20 steps of deformation, since the plastic strain or reduction that can be imposed in a single step is limited by material workability and process mechanics. Here, we demonstrate a fundamentally different, single-step approach to produce flat wire aluminum products using machining-based deformation that also ensures adequate material workability in the formed product. Two process routes are proposed: (1) chip formation by free-machining (FM), with a post-machining, light drawing reduction (<20%) to achieve desired finish and (2) constrained chip formation by large strain extrusion machining (LSEM). Using commercially pure aluminum conductor alloys (Al 1100 and EC1350) as representative material systems, we demonstrate key features of the machining-based processing, including (a) single-step processing to achieve flat wire geometries, (b) surface finish (Ra = 0.2 to 1.0 μm) comparable to that of commercial wire products made by drawing/rolling, (c) deformation control independent of wire size, and (d) hardness increases of 50–150% over that of annealed wires, while retaining high electrical conductivity (>56% IACS). Here, the wire microstructure, which can also be varied via the large-strain deformation parameters, is correlated with mechanical and electrical properties. Implications for commercial manufacture of flat wire products are discussed.
Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.
Belowground microbial communities strongly influence ecosystem function such that predicting function may rely on understanding ecological processes that assemble communities. Uncertainty remains, however, in what governs the relative contributions of different ecological processes. To help fill this knowledge gap we test the general hypothesis that both initial state and degree of change in environmental conditions govern the relative contributions of different ecological assembly processes. To do so we leveraged regional-scale nutrient and organic matter addition experiments and used soil organic matter (SOM) as a proxy of integrated soil environmental conditions. Consistent with our hypothesis, we found that both the initial amount of SOM and the degree of change in SOM—in response to nutrient addition—influenced the relative contributions of different ecological assembly processes. These influences were most clearly observed at the regional scale, suggesting potential scale dependence. More specifically, nutrient additions homogenized bacterial community composition due to enhanced influences of homogenizing dispersal when SOM content was initially high. In contrast, nutrient additions led to divergence in community composition due to variable selection when initial SOM was low and/or when SOM increased significantly in response to nutrient additions. Our findings indicate important connections among initial conditions, degree of change in environmental variables, and microbial community assembly processes that may influence ecosystem processes. These conceptual inferences highlight a need to strengthen connections between ecological theory and biogeochemical modeling.
The sustainability and economic feasibility of modern biorefinery depend on the efficient processing of both carbohydrate and lignin fractions for value-added products. By mimicking the biomass degradation process in white-rote fungi, a tailored two-step fractionation process was developed to maximize the sugar release from switchgrass biomass and to optimize the lignin processability for bioconversion. Biomimicking biomass processing using Formic Acid: Fenton: Organosolv (F 2 O) and achieved high processability for both carbohydrate and lignin. Specifically, switchgrass pretreated by the F 2 O process had 99.6% of the theoretical yield for glucose release. The fractionated lignin was also readily processable by fermentation via Rhodococcus opacus PD630 with a lipid yield of 1.16 g/L. Scanning electron microscope analysis confirmed the fragmentation of switchgrass fiber and the cell wall deconstruction by the F 2 O process. 2D-HSQC NMR further revealed the cleavage of aryl ether linkages (β-O-4) in lignin components. These results revealed the mechanisms for efficient sugar release and lignin bioconversion. The F 2 O process demonstrated effective mimicking of natural biomass utilization system and paved a new path for improving the lignin and carbohydrate processability in next generation lignocellulosic biorefinery.
Solvent-free manufacturing of battery components is a promising alternative to traditional slurry processing for reducing the cost and environmental impact. In this work, we used twin-screw melt extrusion to fabricate a polymer-based high voltage composite cathode. The melt-processed cathode is dense (near zero porosity) and thick (65 μm) and has high active material loading (80 wt %). The active particles are distributed uniformly throughout the melt-processed cathode, unlike the traditional slurry-cast cathode, which exhibits inhomogeneous particle distribution. In the melt-processed cathode, polymer and carbon form separate phases, whereas in the slurry-cast cathode they blend into a single phase. Due to these structural differences, the melt-processed cathode shows smooth charge–discharge profiles, while the slurry-cast cathode shows noisy charging and soft-shorting behavior. In conclusion, this work highlights that twin-screw extrusion as a scalable, solvent-free manufacturing method is advantageous in producing uniform cathodes, which mitigates anode instability.
The primary astrophysical source of the rare-earth elements is the rapid neutron capture process ( r process). The rare-earth peak that is seen in the solar r -process residuals has been proposed to originate as a pile-up of nuclei during the end of the r process. We introduce a new method utilizing Monte Carlo studies of nuclear masses in the rare-earth region, that includes self-consistently adjusting β -decay rates and neutron capture rates, to find the mass surfaces necessary for the formation of the rare-earth peak. We demonstrate our method with two types of astrophysical scenario, one corresponding to conditions typical of hot winds from core-collapse supernovae and stellar-mass accretion disks, and one corresponding to conditions typical of the ejection of the material from the tidal tails of neutron star mergers. In each type of astrophysical condition, this method successfully locates a region of enhanced stability in the mass surface that is responsible for the rare-earth peak. For each scenario, we find that the change in the mass surface has qualitatively different features, thus future measurements can shed light on the type of environment in which the r process occurred.