Low Cost, High-Throughput, Dense-Fiber Channel Optical Interrogator Based On Photonic Integrated Circuits (PIC) Microchip Technology.
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With the advances in next generation sequencing technologies, the number of sequenced genomes is growing exponentially, resulting in a technology bottleneck for the translation of sequence information into usable hypotheses about the function of each gene. We have proposed leveraging our leadership high-performance computing (HPC) resources to help break this annotation bottleneck. Here we design an HPC-based framework to infer gene function from gene sequence by incorporating information about protein structure and interactions predicted by deep learning approaches. Accurate functional prediction and gene annotation using computational methods will facilitate breakthroughs in the genomic sciences essential to understanding and harnessing life processes in bacteria, fungi and plants. The development and applications of the state-of-the-art deep neural networks to protein structural modeling, interaction prediction, sequence comparison, and quality assessment of protein structural models will be made possible by leadership computational resources. These HPC-enabled bioinformatics and molecular modeling tools will provide powerful insights into molecular functions of genes.
Primary project achievements include using selective pressures (O 2 , light, temperature) and developing culturing regimes for the diatom Nitzschia inconspicua str. hildebrandi to attain enrichments with an ~90% increase in areal biomass productivity relative to the parental strain under pond-mimicking conditions with high O 2 stress in laboratory bioreactors. The resulting strain (GAI-337) was tested further for dilution time, culture density, CO 2 supplementation, pH, temperature, and dissolved O 2 concentration under outdoor pond-mimicking conditions to improve areal productivities. These experiments yielded an optimum harvest and dilution time just after sunset, ~0.45 g AFDW L -1 initial culture density for maximal productivities, no requirement for CO 2 supplementation or pH control, maximal performance under a diel temperature curve going from 24 °C at night to 36 °C during the day, and benefits from some O 2 removal from the culture by bubbling with air. Using pond-mimicking laboratory bioreactors, N. inconspicua GAI-337 achieved ~42 g AFDW m -2 d -1 . Nutrient limitation experiments resulted in a biomass composition that equated to ~160 Gallons of Gasoline Equivalent energy per ton AFDW, highlighting the potential of GAI-337 as a promising renewable fuel feedstock strain. Genome resequencing has revealed genome alterations potentially contributing to the improved growth of GAI-337 in the laboratory. Based on the comparative analyses of the GAI-337 and GAI-229 (reference) strains, we identified 144 single nucleotide substitutions that resulted in amino acid change, 7 single nucleotide substitutions that resulted in protein truncation; 5 deletions; and 1 frameshift mutation. From the mutations that potentially affect expression of functionally annotated genes, particular interest was noted for an interferon-induced 6-16 family protein that may be involved in the host immune response against microbe invasion; the chaperone protein DnaK, which may function to protect the folding of proteins within the cell; and SPRY domain protein that is found in many eukaryotic proteins important in cell signaling pathways. Transcriptome analysis revealed over 1000 genes with increased transcript levels. Many of these and many of the genes with mutations are not yet functionally annotated and an increased bioinformatics effort is necessary to more completely analyze the Nitzschia inconspicua genome. Adaptive laboratory evolution (ALE) was performed for over 300 days using consecutive 0.5°C temperature increases in a constant temperature incubator to attain greater thermal tolerance in Nitzschia inconspicua. The adapted strain was able to grow at a constant temperature of 37.5°C; whereas this constant temperature was lethal to the parental control, which had an upper temperature boundary of 35.5°C prior to adaptive evolution. Several high-temperature clonal isolates were obtained from the evolved population following ALE, and increased temperature tolerance was observed in clonal adapted cultures. The final temperature adaptation was maintained through cryopreservation and was observed in multiple clonal isolates, including multiple clonal isolates with significantly increased cell size, indicating the potential occurrence of a sexual cycle during the clonal isolation process. A survey of Nannochloropsis strains was conducted for tolerances to high pH and high bicarbonate media. Nannochloropsis granulata showed promising growth in diel bioreactors and was successfully grown at the GAI Kauai farm site in long-term growth campaigns. Co-culturing using Nitzschia inconspicua, Nannochloropsis and a cyanobacterium were assembled in the laboratory to determine if productivity synergies could be attained. Although all strains grew well in the laboratory high-bicarbonate media individually, the cyanobacterium quickly outgrew the other strains in the laboratory consortium pushing the co-culture away from a diverse (and potentially synergistic assemblage) phototroph culture towards a monoculture dominated by the cyanobacterium. Several outdoor growth campaigns were conducted, with productivities ranging between 10-20 g/m 2 /d of biomass. The best performing strain in the laboratory (GAI-337) did not outperform reference strains at the Kauai farm under the conditions used. Addition growth campaigns are necessary under conditions that result in higher biomass (>20 g/m 2 /d) and that attain higher O 2 levels are likely necessary. Initial data indicate that the thermally adapted strain did slightly better than the control strain at higher temperatures; however, additional campaigns are necessary to establish statistical significance. In summary, Nitzschia inconspicua is able to attain exemplary biomass and lipid yields in the laboratory bioreactors. Strain evolution to both O 2 and temperature resulted in targeted strain improvements. Additional outdoor campaigns are necessary to determine if laboratory improvements translate to the field.
We present an approach for quantitatively predicting the temperature-dependent single-component adsorption behavior of linear alkanes in silica and Na-exchanged cationic zeolites using machine learning (ML) models trained from extensive molecular simulations based on force fields with coupled cluster accuracy. A high-performing classification model was developed to distinguish between instances with negligible and non-negligible adsorption. Subsequently, two ML models were trained to predict the single-component adsorption loading and the heat of adsorption at any pressure at 300 K for any zeolite topology and silicon-to-aluminum ratio. The ML models were trained on International Zeolite Association (IZA) zeolites, and their transferability to hypothetical zeolites was successfully validated. We then expand the power of these predictions to adsorbed mixtures at arbitrary temperatures by integrating them with the Clausius–Clapeyron equation and ideal adsorbed solution theory (IAST). This approach was validated and then applied to a temperature swing adsorption separation process to demonstrate its practical utility. We demonstrate how predictions from this ML-enabled approach can allow the selection of high-performing materials that are then validated using detailed molecular simulations based on quantitatively accurate force fields.
ULTIMATE is a leading-edge DOE program to develop ultrahigh temperature materials for gas turbine use in the aviation and power generation industries. This team, headquartered at West Virginia University and including collaborators from the National Energy Technology Laboratory and Advanced Manufacturing LLC, has developed a new class of ultra-high temperature Refractory Complex Concentrated Alloys-based Composites (RCCC) for high temperature applications such as combustion turbines used in the aerospace and energy industries. The RCCC consist of Refractory Complex Concentrated Alloys (RCCA) mixed with particles of Refractory High Entropy Carbides, to increase RCCA strength to withstand extreme conditions. These new materials optimize the balance among strength, creep (deformation), density, and stability at 1300 °C (2372 °F), while maintaining ductility once the alloy cools to room temperature. The research team has developed advanced manufacturing processes using the pulsed electric current and laser 3D printing to produce test coupons of these materials.
Modifications on RNAs play major roles in their stability, translation, and enzymatic activity. Despite its importance, the current techniques are insufficient to study the structure and function of RNA modifications. Indeed, the National Academies of Science, Engineering and Medicine indicate that developing new tools and further study the function of RNA modifications is strategically a high priority for advancing science in the coming years (https://www.nationalacademies.org/our-work/toward-sequencing-and-mapping-of-rna-modifications). RNA modifications occur in all domains of life controlling processes such as RNA turnover, translation regulation, cellular defenses and bioproduction. Our preliminary data indicated that the insulin mRNA might get ADP-ribosylated by the ADP-ribosyltransferase PARP12. RNA ADP-ribosylation has been described in Escherichia coli. Combined to the fact that ADP-ribosyltransferase (PARP) genes are conserved throughout evolution we hypothesize that this modification might play essential roles in cells. Therefore, we proposed to develop sequencing techniques and in vitro enzymatic assays to identify and validate ADP-ribosylation motifs and sites. Here we report the development of RNA-seq and qPCR assays to identify ADP-ribosylated RNAs, in addition to a nicotinamide adenosine dinucleotide (NAD – ADP-ribosylation donor) consumption assay and an enzyme-linked immunosorbent assay (ELISA) to measure ADP-ribosyltransferase activity. Testing these assays with the insulin mRNA confirmed that this transcript is ADP-ribosylated. These assays will not only enable studying the function of ADP-ribosylation but can be easily adapted for studying other RNA modifications. This will open opportunities to study RNA modifications in different model systems from bacteria to viruses to plants, bringing insights into their cellular functions and the possibility of targeting them for biotechnological applications.
Palo Alto Research Center (PARC) and its partners will explore a targeted molten metal as a catalyst in a methane pyrolysis mist reactor to convert natural gas into hydrogen and solid carbon at a low cost without carbon dioxide emissions. The technology could augment or replace current H 2 production methods, while simultaneously sequestering carbon in high value materials.
Photometric imaging of ionospheric/magnetospheric O II emission at 83.4 nm is a primary objective for mapping the distribution of O(+) ions. However, instrumental sensitivity has been a major barrier to realizing this goal. We report an instrumental design employing a low focal ratio three-mirror camera where the reflecting surfaces act as both narrowband reflection filters at 83.4 nm and as a high quality imaging system. The design includes coatings with reflectances that are relatively insensitive to the angle of incidence of light. The peak reflectance per mirror is more than 60 percent at 83.4 nm with the average reflectance for out-of-band wavelengths of less than 5 percent. The net reflective transmission for the three mirrors is greater than 20 percent with 6.8 nm bandwidth and 0.01 percent maximum transmittance for out-of-band wavelengths. The transmittance at 30.4 nm is 0.03 percent at 58.4 nm 0.05 percent, and at 121.6 nm 0.004 percent. When used with an open microchannel plate detector, contamination by H Ly-alpha is essentially eliminated. With this spectral purity and effective elimination of major contributors to background contamination noise, a signal-to-noise ratio (excluding detector noise) of 10 is achievable for a 0.01 R signal in 8.8 seconds for the full 6 deg field-of-view.
Advancement of microalgae for use as biofuel feedstock depends on bioprospecting novel strains and then applying classical strain improvement techniques to enhance desirable traits. Here we successfully demonstrate this approach using two novel strains of green algae, identified as Desmodesmus armatus and Chlorella vulgaris, to improve biomass and lipid yields. UV irradiation was utilized to generate random mutations and the resulting populations were analyzed via flow cytometry to quantify lipid fluorescence while enriching for high lipid variants using fluorescence activated cell sorting. Secondary screening was performed via in situ fluorescence staining to identify the single highest lipid producing mutants from each strain. This approach produced a Desmodesmus armatus mutant that exhibited both increased biomass productivity and higher lipid content, which doubled lipid yield from the culture. The resulting Chlorella vulgaris mutant exhibited an increase in growth only, resulting in a 33% increase in lipid yield.
Abstract Background Pyrolysis-molecular beam mass spectrometry (py-MBMS) analysis of a pedigree of Populus trichocarpa was performed to study the phenotypic plasticity and heritability of lignin content and lignin monomer composition. Instrumental and microspatial environmental variability were observed in the spectral features and corrected to reveal underlying genetic variance of biomass composition. Results Lignin-derived ions (including m/z 124, 154, 168, 194, 210 and others) were highly impacted by microspatial environmental variation which demonstrates phenotypic plasticity of lignin composition in Populus trichocarpa biomass. Broad-sense heritability of lignin composition after correcting for microspatial and instrumental variation was determined to be H 2 = 0.56 based on py-MBMS ions known to derive from lignin. Heritability of lignin monomeric syringyl/guaiacyl ratio ( S / G ) was H 2 = 0.81. Broad-sense heritability was also high (up to H 2 = 0.79) for ions derived from other components of the biomass including phenolics (e.g., salicylates) and C5 sugars (e.g., xylose). Lignin and phenolic ion abundances were primarily driven by maternal effects, and paternal effects were either similar or stronger for the most heritable carbohydrate-derived ions. Conclusions We have shown that many biopolymer-derived ions from py-MBMS show substantial phenotypic plasticity in response to microenvironmental variation in plantations. Nevertheless, broad-sense heritability for biomass composition can be quite high after correcting for spatial environmental variation. This work outlines the importance in accounting for instrumental and microspatial environmental variation in biomass composition data for applications in heritability measurements and genomic selection for breeding poplar for renewable fuels and materials.
Abstract Halide perovskites show ubiquitous presences in growing fields at both fundamental and applied levels. Discovery, investigation, and application of innovative perovskites are heavily dependent on the synthetic methodology in terms of time-/yield-/effort-/energy- efficiency. Conventional wet chemistry method provides the easiness for growing thin film samples, but represents as an inefficient way for bulk crystal synthesis. To overcome these, here we report a universal solid state-based route for synthesizing high-quality perovskites, by means of simultaneously applying both electric and mechanical stress fields during the synthesis, i.e., the electrical and mechanical field-assisted sintering technique. We employ various perovskite compositions and arbitrary geometric designs for demonstration in this report, and establish such synthetic route with uniqueness of ultrahigh yield, fast processing and solvent-free nature, along with bulk products of exceptional quality approaching to single crystals. We exemplify the applications of the as-synthesized perovskites in photodetection and thermoelectric as well as other potentials to open extra chapters for future technical development.
Revealing the contributions of genes to plant phenotype is frequently challenging because loss-of-function effects may be subtle or masked by varying degrees of genetic redundancy. Such effects can potentially be detected by measuring plant fitness, which reflects the cumulative effects of genetic changes over the lifetime of a plant. However, fitness is challenging to measure accurately, particularly in species with high fecundity and relatively small propagule sizes such as Arabidopsis thaliana. An image segmentation-based method using the software ImageJ and an object detection-based method using the Faster Region-based Convolutional Neural Network (R-CNN) algorithm were used for measuring two Arabidopsis fitness traits: seed and fruit counts. The segmentation-based method was error-prone (correlation between true and predicted seed counts, r 2 = 0.849) because seeds touching each other were undercounted. By contrast, the object detection-based algorithm yielded near perfect seed counts (r 2 = 0.9996) and highly accurate fruit counts (r 2 = 0.980). Comparing seed counts for wild-type and 12 mutant lines revealed fitness effects for three genes; fruit counts revealed the same effects for two genes. Our study provides analysis pipelines and models to facilitate the investigation of Arabidopsis fitness traits and demonstrates the importance of examining fitness traits when studying gene functions.
This final technical report presents a comprehensive analysis of a novel plasma-based in-line manufacturing process for large-area, LLZO-separator-based, solid-state lithium-ion batteries, demonstrating both technical feasibility and economic advantages over conventional vacuum deposition methods. The technical validation shows that spray-deposition with plasma curing achieves comparable electrode and separator quality to vacuum techniques while enabling continuous processing of components and industrially relevant film areas. Critical material interfaces maintain low porosity and high ionic conductivities, which confirm the process's ability to overcome the primary limitation of conventional methods - the trade-off between deposition quality and economically-viable production scale.
We have developed manufacturable approaches to form single, vertically aligned carbon nanotubes, where the tubes are centered precisely, and placed within a few hundred nm of 1-1.5 micron deep trenches. These wafer-scale approaches were enabled by chemically amplified resists and inductively coupled Cryo-etchers to form the 3D nanoscale architectures. The tube growth was performed using dc plasmaenhanced chemical vapor deposition (PECVD), and the materials used for the pre-fabricated 3D architectures were chemically and structurally compatible with the high temperature (700 C) PECVD synthesis of our tubes, in an ammonia and acetylene ambient. The TEM analysis of our tubes revealed graphitic basal planes inclined to the central or fiber axis, with cone angles up to 30 deg. for the particular growth conditions used. In addition, bending tests performed using a custom nanoindentor, suggest that the tubes are well adhered to the Si substrate. Tube characteristics were also engineered to some extent, by adjusting growth parameters, such as Ni catalyst thickness, pressure and plasma power during growth.
In the Run 3 upgrade of ATLAS experiment, the FELIX (Front-End LInk eXchange) system has been prepared as the interface between front-end electronics and common Data Acquisition (DAQ) systems. Based on a PCIe card hosted in commodity server, FELIX's flexibilty makes it has also been adopted by other experiments, such as the Single-Phase ProtoDUNE (Prototype for the Deep Underground Neutrino Experiment), sPHENIX and CBM experiments. The same PCIe based architecture is proposed for use in the ATLAS HL-LHC (High Luminosity Large Hadron Collider) upgrade and the DUNE experiment. To this end, the next generation of FELIX I/O card FLX-801 has been developed. It supports 25+ Gbps high speed fiber optical links and 16-lane Gen4 PCIe interface. There is an on-card DDR4 module to buffer event data for DUNE experiment. This paper reports on the test results for the demonstrator of this next generation card, with which main functions have been successfully evaluated.
Thermal energy management in metal-organic frameworks (MOFs) is an important, yet often neglected, challenge for many adsorption-based applications such as gas storage and separations. Despite its importance, there is insufficient understanding of the structure-property relationships governing thermal transport in MOFs. To provide a data-driven perspective into these relationships, here we perform large-scale computational screening of thermal conductivity k in MOFs, leveraging classical molecular dynamics simulations and 10,194 hypothetical MOFs created using the ToBaCCo 3.0 code. We found that high thermal conductivity in MOFs is favored by high densities (> 1.0 g cm -3 ), small pores (< 10 Å), and four-connected metal nodes. We also found that 36 MOFs exhibit ultra-low thermal conductivity (< 0.02 W m -1 K -1 ), which is primarily due to having extremely large pores (~65 Å). Furthermore, we discovered six hypothetical MOFs with very high thermal conductivity (>10 Wm -1 K -1 ), the structures of which we describe in additional detail.
Nuclear resonance time domain interferometry (NR-TDI) is used to study the slow dynamics of liquids (that do not require Mössbauer isotopes) at atomic and molecular length scales. Here the TDI method of using a stationary two-line magnetized 57 Fe foil as a source and a stationary single-line stainless steel foil analyzer is employed. The new technique of adding an annular slit in front of a single silicon avalanche photodiode detector enables a wide range of momentum transfers (1 to 100 nm -1 by varying the distance between the annular slits and sample) with a high count rate of up to 160 Hz with a Δ q resolution of ±1.7 nm -1 at q = 14 nm -1 . The sensitivity of this method in determining relaxation times is quantified and discussed. The Kohlrausch–Williams–Watts (KWW) model was used to extract relaxation times for glycerol. These relaxation times give insight into the dynamics of the electron density fluctuations of glycerol as a function of temperature and momentum transfers.
Standard x-ray systems for crystallography rely on massive generators coupled with optics that guide X-ray beams onto the crystal sample. Optics for single-crystal diffractometry include total reflection mirrors, polycapillary optics or graded multilayer monochromators. The benefit of using polycapillary optic is that it can collect x-rays over tile greatest solid angle, and thus most efficiently, utilize the greatest portion of X-rays emitted from the Source, The x-ray generator has to have a small anode spot, and thus its size and power requirements can be substantially reduced We present the design and results from the first high flux x-ray system for crystallography that combine's a microfocus X-ray generator (40microns FWHM Spot size at a power of 45 W) and a collimating, polycapillary optic. Diffraction data collected from small test crystals with cell dimensions up to 160A (lysozyme and thaumatin) are of high quality. For example, diffraction data collected from a lysozyme crystal at RT yielded R=5.0% for data extending to 1.70A. We compare these results with measurements taken from standard crystallographic systems. Our current microfocus X-ray diffraction system is attractive for supporting crystal growth research in the standard crystallography laboratory as well as in remote, automated crystal growth laboratory. Its small volume, light-weight, and low power requirements are sufficient to have it installed in unique environments, i.e.. on-board International Space Station.