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At least 1,027 records · Page 57

Metabolic engineering strategies for sesquiterpene production in microorganism

Sesquiterpenes are a large variety of terpene natural products, widely existing in plants, fungi, marine organisms, insects, and microbes. Value-added sesquiterpenes are extensively used in industries such as: food, drugs, fragrances, and fuels. With an increase in market demands and the price of sesquiterpenes, the biosynthesis of sesquiterpenes by microbial fermentation methods from renewable feedstocks is acquiring increasing attention. Synthetic biology provides robust tools of sesquiterpene production in microorganisms. This review presents a summary of metabolic engineering strategies on the hosts and pathway engineering for sesquiterpene production. Advances in synthetic biology provide new strategies on the creation of desired hosts for sesquiterpene production. Especially, metabolic engineering strategies for the production of sesquiterpenes such as: amorphadiene, farnesene, bisabolene, and caryophyllene are emphasized in: Escherichia coli , Saccharomyces cerevisiae , and other microorganisms. Herein, challenges and future perspectives of the bioprocess for translating sesquiterpene production into practical industrial work are also discussed.

59 BASIC BIOLOGICAL SCIENCES↗

Element differentiation with a Hartmann- based X-ray phase imaging system

Significant efforts are currently ongoing in X-ray imaging to provide multimodal imaging systems, targeting better sensitivity and specificity for both biomedical or non-destructive testing applications. Knowing the elemental composition of specific structures, such as breast microcalcifications in mammography, would help to differentiate malign and benign tumours. Standard X-ray Phase Contrast Imaging techniques provide only qualitative information on elements with similar absorption properties. However, their chemical composition can be determined from the measurement of the phase as it is directly related to the optical index of elemental materials. We will show new experimental results obtained with an X-ray phase imaging system based on a Hartmann mask. Early data treatment succeeded in retrieving both the real and imaginary parts of the refractive index. The system demonstrates the capability to discriminate materials based on elemental composition.

36 MATERIALS SCIENCE↗

Emission factors of industrial boilers burning biomass-derived fuels

Boilers are combustion devices that provide process heat and are integral to many industrial facilities. Historically, outside of the pulp and paper industry, most boilers burned fossil fuels, although interest in decarbonization has been leading to an increased use of renewable fuels in boilers. These boilers, including those in the biorefineries, are often large sources of air pollutant emissions, and the characterization of these emissions is critical to obtaining air permits and ensuring protection of the surrounding air quality. Several industrial boilers and new biorefineries allow utilization of biomass-derived fuels (e.g. wastewater sludge, lignin, etc.) produced during their operation as a fuel for the boiler to meet process energy needs. However, there is limited empirical data on emission factors for the burning of unconventional fuels, such as solid-gas mixtures containing biomass residues. To fill this gap, we carry out a comprehensive data survey, collecting information on emission factors for boilers burning either a single or a mixture of solid and gaseous biomass-derived fuels. We review multiple hard-to-obtain and unconventional data sources, such as air permit applications, stack test data, and industry-sponsored data collection efforts, to compile emission factors for biomass-derived fuels. We then compare this data with wood residue emission factors from the U.S. Environmental Protection Agency’s AP-42 emission factor database. Our results indicate that the emission factors for boilers burning unconventional fuels vary widely depending on the fuel composition, boiler type, and fuel characteristics. Overall, we find that median emission factors of selected biomass-derived fuels are typically lower than those of wood residue boilers in AP-42. The information collected herein could be useful to permitting agencies and industries utilizing boilers who may want to reduce the carbon impact of their facilities by combusting biomass-derived wastes for process energy needs, for more accurate emission estimation for permitting.

09 BIOMASS FUELS↗

On unifying randomized methods for inverse problems

This work unifies the analysis of various randomized methods for solving linear and nonlinear inverse problems with Gaussian priors by framing the problem in a stochastic optimization setting. By doing so, we show that many randomized methods are variants of a sample average approximation (SAA). More importantly, we are able to prove a single theoretical result that guarantees the asymptotic convergence for a variety of randomized methods. Additionally, viewing randomized methods as an SAA enables us to prove, for the first time, a single non-asymptotic error result that holds for randomized methods under consideration. Another important consequence of our unified framework is that it allows us to discover new randomization methods. Here, we present various numerical results for linear, nonlinear, algebraic, and PDE-constrained inverse problems that verify the theoretical convergence results and provide a discussion on the apparently different convergence rates and the behavior for various randomized methods.

42 ENGINEERING↗

An autoencoder compression approach for accelerating large-scale inverse problems

Abstract Partial differential equation (PDE)-constrained inverse problems are some of the most challenging and computationally demanding problems in computational science today. Fine meshes required to accurately compute the PDE solution introduce an enormous number of parameters and require large-scale computing resources such as more processors and more memory to solve such systems in a reasonable time. For inverse problems constrained by time-dependent PDEs, the adjoint method often employed to compute gradients and higher order derivatives efficiently requires solving a time-reversed, so-called adjoint PDE that depends on the forward PDE solution at each timestep. This necessitates the storage of a high-dimensional forward solution vector at every timestep. Such a procedure quickly exhausts the available memory resources. Several approaches that trade additional computation for reduced memory footprint have been proposed to mitigate the memory bottleneck, including checkpointing and compression strategies. In this work, we propose a close-to-ideal scalable compression approach using autoencoders to eliminate the need for checkpointing and substantial memory storage, thereby reducing the time-to-solution and memory requirements. We compare our approach with checkpointing and an off-the-shelf compression approach on an earth-scale ill-posed seismic inverse problem. The results verify the expected close-to-ideal speedup for the gradient and Hessian-vector product using the proposed autoencoder compression approach. To highlight the usefulness of the proposed approach, we combine the autoencoder compression with the data-informed active subspace (DIAS) prior showing how the DIAS method can be affordably extended to large-scale problems without the need for checkpointing and large memory.

Mathematics↗

Absolute nuclear charge radius by Na-like spectral line separation in high-Z elements

Abstract We describe a novel technique to determine absolute nuclear radii of high- Z nuclides. Utilizing accurate theoretical atomic structure calculations together with precise measurements of extreme ultraviolet transitions in highly charged ions this method allows for precise determinations of absolute nuclear charge radii based upon the well-known nuclear radii of their neighboring elements. This method can work for elements without stable isotopes, and its accuracy may be competitive with current methods (electron scattering and muonic x-ray spectroscopy).

Hosier, A. (ORCID:0000000328366605)↗

Topological background discrimination in the PandaX-III neutrinoless double beta decay experiment

The PandaX-III experiment plans to search for neutrinoless double beta decay (0ν ββ ) of 136 Xe in the China JinPing underground Laboratory (CJPL). The experiment will use a high pressure gaseous time projection chamber (TPC) to register both the energy and the electron track topology of an event. This article is devoted to demonstrate our particular detector setup capabilities for the identification of 0ν ββ and the consequent background reduction. As software tool we use REST, a framework developed for the reconstruction and simulation of TPC-based detector systems. We study the potential for background reduction by introducing appropriate parameters based on the properties of 0ν ββ events. We exploit for the first time not only the energy density of the electron track-ends, but also the electron scattering angles produced by an electron near the end of its trajectory. To implement this, we have added new algorithms for detector signal and track processing inside REST. Their assessment shows that background can be reduced by about 7 orders of magnitude while keeping 0ν ββ efficiency above 20% for the PandaX-III baseline readout scheme, a two-dimensional 3 mm pitch stripped readout. More generally, we use the potential of REST to handle 2D/3D data to assess the impact on signal-to-background significance at different detector granularities, and to validate the PandaX-III baseline choice. Finally, we demonstrate the additional potential to discriminate surface background events generated at the readout plane in the absence of to, by making use of event parameters related with the diffusion of electrons.

Majorana↗

Multi-physics modeling of grain growth during solidification in electron beam additive manufacturing of Inconel 718

While experimental work has shown promising results regarding control of additive manufacturing metal grain structure, the effects of processing parameters on the grain structure is difficult to understand and predict from experiment alone. To this end, a modeling framework is developed which sequentially couples a macro-scale, semi-analytic thermal model, and a meso-scale, cellular automata-based microstructure model. This framework is applied to electron beam additive manufacturing of Inconel 718 using a complex spot scan pattern. The model shows that, with the same scan pattern, variations in the spot time and electron-beam current produce thermal histories with significant spatial and temporal differences, which then produce complex solidification conditions from the interplay between molten pools in the same layer and subsequent layers, resulting in vastly different grain structures. Additionally, it is noted that the framework can significantly reduce the computational expenses for coupled thermal-metallurgical problems, and has the potential to be used for component level problems.

36 MATERIALS SCIENCE↗

Metallic and porous Ti nanorod arrays for visible-IR light absorption and dendrite-free stable lithium-metal batteries

It is still a challenging task to prepare highly porous nanorod arrays of metals formed on substrates for optical and energy storage applications. Herein, we demonstrate the design and synthesis of black color, metallic and highly porous Ti nanorod arrays as novel current collectors for dendrite-free and highly stable Li-metal anodes. The high porosity of metallic nanorod arrays provides numerous heterogeneous nucleation sites and huge contact area and large space for the accommodation of Li metal. The conductive metallic Ti nanorod arrays enhance electrode integration. Effectively, it eliminates formation Li dendrites and demonstrates superior cycling stability over 300 cycles. Additionally, the unique porous structures of the nanorod arrays can decrease the amplitude of forced vibration in narrow space leading to light absorption. Interestingly, the metal is black instead of metallic color. The black metallic nanorod arrays can absorb more than 96% of both visible and infra-red lights. Furthermore, this black color metallic porous nanorod arrays may find additional applications in aerospace, energy, biomedical, defence, and chemical industries.

25 ENERGY STORAGE↗

Hierarchical domain structures associated with oxygen octahedra tilting patterns in lead-free (Bi 1/2 Na 1/2 )TiO 3

Hierarchical domain structures associated with oxygen octahedra tilting patterns were observed in lead-free (Bi 1/2 Na 1/2 )TiO 3 ceramics using aberration-corrected high-resolution transmission electron microscopy (HRTEM). Three types of domains are induced by distinct mechanisms: the 'orientation-domain' is induced at micrometer scale formed by different tilting orientations of the oxygen octahedra, the 'meso-chemical-domain' occurs at a few tens of nanometer scale by chemical composition variation on the A-site in the ABO 3 perovskite structure, and the 'nano-cluster-region' runs across several unit-cells with apparent A-site cation segregation with oxygen vacancies clustering around Na cations. Based on HRTEM amplitude contrast imaging (ACI), the correlation between the oxygen octahedral tilting pattern and compositional non-stoichiometry was established. The role of the hierarchical domain structure associated with the tilting patterns of the oxygen octahedra on the ferroelectric behavior of (Bi 1/2 Na 1/2 )TiO 3 is also discussed.

36 MATERIALS SCIENCE↗

Versatile recognition of graphene layers from optical images under controlled illumination through green channel correlation method

In this study, a simple yet versatile method is proposed for identifying the number of exfoliated graphene layers transferred on an oxide substrate from optical images, utilizing a limited number of input images for training, paired with a more traditional number of a few thousand well-published Github images for testing and predicting. Two thresholding approaches, namely the standard deviation-based approach and the linear regression-based approach, were employed in this study. The method specifically leverages the red, green, and blue color channels of image pixels and creates a correlation between the green channel of the background and the green channel of the various layers of graphene. This method proves to be a feasible alternative to deep learning-based graphene recognition and traditional microscopic analysis. The proposed methodology performs well under conditions where the effect of surrounding light on the graphene-on-oxide sample is minimum and allows rapid identification of the various graphene layers. Here, the study additionally addresses the functionality of the proposed methodology with nonhomogeneous lighting conditions, showcasing successful prediction of graphene layers from images that are lower in quality compared to typically published in literature. In all, the proposed methodology opens up the possibility for the non-destructive identification of graphene layers from optical images by utilizing a new and versatile method that is quick, inexpensive, and works well with fewer images that are not necessarily of high quality.

36 MATERIALS SCIENCE↗

Large-area epitaxial growth of InAs nanowires and thin films on hexagonal boron nitride by metal organic chemical vapor deposition

Large-area epitaxial growth of III–V nanowires and thin films on van der Waals substrates is key to developing flexible optoelectronic devices. In our study, large-area InAs nanowires and planar structures are grown on hexagonal boron nitride templates using metal organic chemical vapor deposition method without any catalyst or pre-treatments. The effect of basic growth parameters on nanowire yield and thin film morphology is investigated. Under optimised growth conditions, a high nanowire density of 2.1 x 10 9 cm -2 is achieved. A novel growth strategy to achieve uniform InAs thin film on h-BN/SiO 2 /Si substrate is introduced. The approach involves controlling the growth process to suppress the nucleation and growth of InAs nanowires, while promoting the radial growth of nano-islands formed on the h-BN surface. A uniform polycrystalline InAs thin film is thus obtained over a large area with a dominant zinc-blende phase. The film exhibits near-band-edge emission at room temperature and a relatively high Hall mobility of 399 cm -2 /(Vs). This work suggests a promising path for the direct growth of large-area, low-temperature III–V thin films on van der Waals substrates.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

QSHS: an axion dark matter resonant search apparatus

We describe a resonant cavity search apparatus for axion dark matter constructed by the quantum sensors for the hidden sector collaboration. The apparatus is configured to search for QCD axion dark matter, though also has the capability to detect axion-like particles, dark photons, and some other forms of wave-like dark matter. Initially, a tuneable cylindrical oxygen-free copper cavity is read out using a low noise microwave amplifier feeding a heterodyne receiver. The cavity is housed in a dilution refrigerator (DF) and threaded by a solenoidal magnetic field, nominally 8 T. The apparatus also houses a magnetic field shield for housing superconducting electronics, and several other fixed-frequency resonators for use in testing and commissioning various prototype quantum electronic devices sensitive at a range of axion masses in the range 2.0–40 μ eV c -2 . The apparatus as currently configured is intended as a test stand for electronics over the relatively wide frequency band attainable with TM 010 the cavity mode used for axion searches. We present performance data for the resonator, DF, and magnet, and plans for the first science run.

Physics - Physics of elementary particles and fiel↗

3D correlations in the Lyman-α forest from early DESI data

We present the first measurements of Lyman-α (Lyα) forest correlations using early data from the Dark Energy Spectroscopic Instrument (DESI). We measure the auto-correlation of Lyα absorption using 88 509 quasars at z > 2, and its cross-correlation with quasars using a further 147 899 tracer quasars at z ≳ 1.77. Then, we fit these correlations using a 13-parameter model based on linear perturbation theory and find that it provides a good description of the data across a broad range of scales. We detect the BAO peak with a signal-to-noise ratio of 3.8σ, and show that our measurements of the auto- and cross-correlations are fully-consistent with previous measurements by the Extended Baryon Oscillation Spectroscopic Survey (eBOSS). Even though we only use here a small fraction of the final DESI dataset, our uncertainties are only a factor of 1.7 larger than those from the final eBOSS measurement. As a result, we validate the existing analysis methods of Lyα correlations in preparation for making a robust measurement of the BAO scale with the first year of DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗

Mock data sets for the Eboss and DESI Lyman-α forest surveys

We present a publicly-available code to generate sets of mock Lyman-α (Lyα) forest data that have realistic large-scale correlations including those due to the Baryonic Acoustic Oscillations (BAO). The primary purpose of these mocks is to test the analysis procedures of the Extended Baryon Oscillation Survey (eBOSS) and the Dark Energy Spectroscopy Instrument (DESI) surveys. The transmitted flux fraction, F(λ), of background quasars due to Lyα absorption in the intergalactic medium (IGM) is simulated using the Fluctuating Gunn-Petterson Approximation (FGPA) applied to Gaussian random fields produced through the use of fast Fourier transforms (FFT). The output includes the IGM-Lyα transmitted flux fraction along quasar lines of sight and a catalog of high-column-density systems appropriately placed at high-density regions of the IGM. This output serves as input to additional code that superimposes the IGM tranmission on realistic quasar spectra, adds absorption by high-column-density systems and metals, and simulates instrumental transmission and noise. Redshift space distortions (RSD) of the flux correlations are implemented by including the large-scale velocity-gradient field in the FGPA resulting in a correlation function of F(λ) that can be accurately predicted. One hundred realizations have been produced over the 14,000 deg 2 DESI survey footprint with 100 quasars per deg 2 . The analysis of these realizations shows that the correlations of F(λ) follows the prediction within the accuracy of eBOSS survey. Here, the most time-consuming part of the mock production occurs before application of the FGPA, and the existing pre-FGPA forests can be used to easily produce new mock sets with modified redshift-dependent bias parameters or observational conditions.

79 ASTRONOMY AND ASTROPHYSICS↗

Impact of systematic redshift errors on the cross-correlation of the Lyman-α forest with quasars at small scales using DESI Early Data

The Dark Energy Spectroscopic Instrument (DESI) will measure millions of quasar spectra by the end of its 5 year survey. Quasar redshift errors impact the shape of the Lyman-α forest correlation functions, which can affect cosmological analyses and therefore cosmological interpretations. Here, using data from the DESI Early Data Release and the first two months of the main survey, we measure the systematic redshift error from an offset in the cross-correlation of the Lyman-α forest with quasars. We find evidence for a redshift dependent bias causing redshifts to be underestimated with increasing redshift, stemming from improper modeling of the Lyman-α optical depth in the templates used for redshift estimation. New templates were derived for the DESI Year 1 quasar sample at z > 1.6 and we found the redshift dependent bias, Δr ∥ , increased from -1.94 ± 0.15 h -1 Mpc to -0.08 ± 0.04 h -1 Mpc (-205 ± 15 km s -1 to -9.0 ± 4.0 km s -1 ). These new templates will be used to provide redshifts for the DESI Year 1 quasar sample.

Lyman alpha forest↗