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At least 667 records · Page 37

Investigating a novel magnetic MAX phase nitride and its (001)-surfaces

We report magnetic MAX phases including their surfaces exhibit promising functional properties for magneto-electronic devices and self-monitoring smart coatings. By employing an integrated ab-initio approach, here we investigate a new member of the MAX phase, Mn 2 AuN. This compound satisfies the chemical, mechanical and dynamical stability criteria, leading to a possibility of its synthesis, and exhibits electronic and elastic anisotropy. The identified ferromagnetic configuration (with high Curie temperature) is the most energetically favorable among the five different spin configurations i.e., non-magnetic, ferromagnetic, and three anti-ferromagnetic. From the coatings perspective, the surface properties of Mn 2 AuN(001) terminations are investigated considering the four possible surface termination models. Remarkably, the magnetism does not get vanished even after cleaving the bulk unit cell into the (001)-surfaces. While evaluating the surface energetics in different chemical potentials, the N-001 terminated surface comes out to be the most stable termination contrasting with carbide MAX phases and is the only termination that exhibits the magnetic characteristics.

36 MATERIALS SCIENCE↗

Black textile with bottom metallized surface having enhanced radiative cooling under solar irradiation

We discuss the cooling performance of garments can play an important role of enabling comfortable human activities under extreme environments. Imparting extra cooling performance to a garment in a passive way is extremely challenging under the sunlight which provides a huge energy influx to the garment, especially made of black colored textile. In this study, a solar-adaptive-textile (SAT) has been designed and experimentally demonstrated. Near-infrared (NIR) transmittance to the human skin from the solar irradiance has been intercepted by incorporating a nanoscale sputtered thin aluminum metal film underneath the textile layer facing the skin. The high-pressure sputtering employed allows a deep penetration of aluminum into the fabric structure for enhanced solar-energy-blocking effect and film stability. The aluminum layer effectively reduces the solar irradiance as well as the thermal radiation from the textile, which gets heated in lieu of the human skin. The outdoor, under-the-sun measurements with a simulated skin showed an outstanding 2 °C cooling effect compared to the normal textile without the metal film, while preserving most of the given textile properties such as colors, air permeability and wicking behavior.

36 MATERIALS SCIENCE↗

Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions

Here we propose a new type of neural networks, Kronecker neural networks (KNNs), that form a general framework for neural networks with adaptive activation functions. KNNs employ the Kronecker product, which provides an efficient way of constructing a very wide network while keeping the number of parameters low. Our theoretical analysis reveals that under suitable conditions, KNNs induce a faster decay of the loss than that by the feed-forward networks. This is also empirically verified through a set of computational examples. Furthermore, under certain technical assumptions, we establish global convergence of gradient descent for KNNs. As a specific case, we propose the Rowdy activation function that is designed to get rid of any saturation region by injecting sinusoidal fluctuations, which include trainable parameters. The proposed Rowdy activation function can be employed in any neural network architecture like feed-forward neural networks, Recurrent neural networks, Convolutional neural networks etc. The effectiveness of KNNs with Rowdy activation is demonstrated through various computational experiments including function approximation using feed-forward neural networks, solution inference of partial differential equations using the physics-informed neural networks, and standard deep learning benchmark problems using convolutional and fully-connected neural networks.

97 MATHEMATICS AND COMPUTING↗

Using machine learning to predict the correlation of spectra using SDSS magnitudes as an improvement to the Locus Algorithm

The Locus Algorithm is a new technique to improve the quality of differential photometry by optimising the choices of reference stars. At the heart of this algorithm is a routine to assess how good each potential reference star is by comparing its SDSS magnitude values to those of the target star. In this way, the difference in wavelength-dependent effects of the Earth’s atmospheric scattering between target and reference can be minimised. This paper sets out a new way to estimate the quality of each reference star using machine learning. A random subset of stars from SDSS with spectra was chosen. For each one, a suitable reference star, also with a spectrum, was chosen. The correlation between the two spectra in the SDSS r band (between 550 nm and 700 nm) was taken to be the gold-standard measure of how well they match up for differential photometry. The five SDSS magnitude values for each of these stars were used as predictors. A number of supervised machine learning models were constructed on a training set of the stars and were each evaluated on a testing set. The model using Support Vector Regression had the best performance of these models. It was then tested on a final, hold-out, validation set of stars to get an unbiased measure of its performance. With an R 2 of 0.62, the SVR model presents enhanced performance for the Locus Algorithm technique.

79 ASTRONOMY AND ASTROPHYSICS↗

Beta-delayed charged-particle spectroscopy using TexAT

β-delayed charged-particle emission is a sensitive probe of three-body decays in light nuclei. Time Projection Chambers (TPCs) offer a significant advantage over traditional charged-particle spectroscopy techniques due to a low-energy threshold and a high-geometric efficiency (≈ 4π) which are essential for use with radioactive ion beams where the beam intensities are limited. The technique for high-sensitivity spectroscopy of β-delayed charged-particle emission is shown to be possible using the Texas Active Target (TexAT) TPC in conjunction with the General Electronics for TPCs (GET) system. The benchmark case studied was that of 12 N β-decay to the first α-unbound state in 12 C, the Hoyle state. Here, half-life and branching ratio measurements are presented and are in good agreement with previous studies. The efficacy of using TPCs to study such a near-threshold state and disentangle the three-body dynamics of the decay products is demonstrated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Analysis of the EMCCD point-source response using x-rays

Electron Multiplying Charge Coupled Devices, EMCCD are used as x-ray detectors. The NSLS-II Soft Inelastic x-ray Scattering (SIX) beam line has two EMCCDs for x-ray detection in the spectrometer arm. The spectrometer with high resolving power disperses x-rays vertically. The x-ray vertical position on the sensor plane is related to its energy. This allows for very accurate x-ray energy measurements through x-ray coordinates. X-rays interact with silicon and create a number of electron-hole pairs proportional to the x-ray energy. Electrons drift and diffuse toward pixel gates and are collected there. The diffused electrons form a charge cloud distributed over several neighboring pixels. This charge sharing enables coordinate measurements with accuracy better than the pixel pitch. The charge distribution shape has to be taken into account to achieve ultimate accuracy in coordinate measurements. In this paper, we present a method of the charge distribution shape analysis and demonstrate its applications. The drift and diffusion of electrons ftom the point of generation to pixel gates results in the bell-shaped electron cloud usually approximated by Gaussian shape. The number of electrons collected under a pixel is proportional to the shape function integral. These electron packets get transferred to the sense node of the output amplifier. The transfer process could introduce distortions to the original charge distribution. For example, during transfers, electrons in the packet could be exposed to traps if they are present in the sensor. The trapping and later the release processes distort the apparent shape of the charge distribution. Therefore, deviations of the charge distribution shape ftom the originally symmetrical form can indicate the presence of trap centers in the sensor and can be used for sensor diagnostics.

47 OTHER INSTRUMENTATION↗

Qualifying LaBr3:Ce+Sr detector performance for the Mu2e experiment at Fermilab Using the ELBE Accelerator

A LaBr3:Ce+Sr detector will be used to measure the stopped muon captures at the Mu2e experiment at Fermilab. It has been benchmarked in a test beam experiment performed at the ELBE electron accelerator located at the Helmholtz-Zentrum Dresden-Rossendorf, Germany. ELBE’s pulsed bremsstrahlung beam line was set to deliver an average γ -ray energy of between 4–5 MeV. The detector response was mapped to match Mu2e beam conditions, including rates up to 1 Mcps, energy flux, and time structure. A radioactive calibration source was used to mimic the characteristic 1808.7 keV γ -ray, emitted during the atomic muon nuclear capture in the Mu2e aluminum stopping target. The detector energy resolution was measured as a function of the average energy flux: up to 1 TeV/s for 0.34 s, the steady-operation beam-on time and up to 4 TeV/s for 5 ms to get a conservative estimate of the effect of high intensity Mu2e beam fluctuations. The PMT gain variation as a function of the beam spill length and average intensity has been parametrized and corrected for. When a PMT gain correction corresponding to the average beam-spill intensity is applied, the residual effect of beam intensity fluctuations around the average degrades the energy resolution, σ E γ /E γ , at 1808.7 keV from 0.66% to 0.83%.

Huang, Shihua [Purdue U., West Lafayette]↗

Root cause analysis of a molten salt pump in FLUSTFA

The primary salt pump installed in the high-temperature FLUoride Salt Test Facility (FLUSTFA) was successfully operated for some time, but later ceased operation. To understand what occurred, a Root Cause Analysis (RCA) was performed. Steps taken to try to get the pump operational include adjusting the shaft position, increasing the heating power of the tape heaters on the pump volute, and manually rotating the pump shaft. While removing the insulation, corrosion was noted on the outside of the pump volute, and decolorization of the insulation and tape heaters was observed. Significant corrosion products were also observed in the pump itself and the piping connected to the pump. The nitrogen cover gas was maintained from before salt was introduced into the loop until the pump was dismounted and continues to be maintained even after the pump was removed. After considering probable scenarios, causes were assigned and corrective actions were developed to prevent those causes. Then, the RCA was presented to an advisory committee for review, the “Review Committee,” consisting of experts in large molten salt systems: Brandon Haugh, David Holcomb, Kevin Robb, and Vicente Rojas. As a result, the advisory committee provided comprehensive feedback, which have been incorporated into a revised RCA. Findings have then been summarized and reported in this publication.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Probing mass orderings in presence of a very light sterile neutrino in a liquid argon detector

Results from experiments like LSND and MiniBooNE hint towards the possible presence of an extra eV scale sterile neutrino. The addition of such a neutrino will significantly impact the standard three flavor neutrino oscillations. In particular, it can give rise to additional degeneracies due to additional sterile parameters. For an eV scale sterile neutrino, the cosmological constraints dictate that the sterile state is heavier than the three active states. However, for lower masses of sterile neutrinos, the sterile state can be lighter than one and/or more of the three states. In such cases, the mass ordering of the sterile neutrinos also becomes unknown, along with the mass ordering of the active states. In this paper, we explore the mass ordering sensitivity in the presence of a sterile neutrino assuming the mass squared difference |Δ 41 | to be in the range 10 –4 –1 eV 2 . We study (i) how the ordering of the active states, i.e. the determination of the sign of Δ 31 gets affected by the presence of a sterile neutrino in the above mass range, (ii) the possible determination of the sign of Δ 41 for Δ 41 in the range 10 –4 –0.1 eV 2 . This analysis is done in the context of a liquid argon detector using beam neutrinos traveling a distance of 1300 km and atmospheric neutrinos that propagate through a distance ranging from 10 – 10000 km, allowing resonant matter effects. Apart from presenting separate results from these sources, we also do a combined study and probe the synergy between these two in giving an enhanced sensitivity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Effect of a nanoparticle on wettability alteration and wettability retainment of carbonate reservoirs

The oil recovery in many carbonate reservoirs is low due to oil-wetness and heterogeneity. In this study, nanoparticles are evaluated for altering the wettability of oil-wet limestones and their properties are compared with those of an anionic surfactant. A surface-modified silica nanoparticle (SiNP) with a negative zeta potential was found to be aqueous stable in brines. Wettability studies showed that the SiNP cannot change the wettability of an initially oil-wet calcite plate, but SiNP treated calcite surface can remain water-wet after aging in oil. Spontaneous imbibition tests confirmed the observations of wettability tests and showed that a SiNP treated carbonate core retained its water-wettability during oil injection and aging. The imbibition into a SiNP treated and oil aged core was comparable to that in a water-wet core. However, SiNP was not able to remove the oil layers in initially oil-wet cores and imbibe water into these cores. In contrast, the anionic surfactant could alter the oil-wet carbonate rocks to a more water-wet condition, but failed to prevent the water-wet surface from getting oil-wet during oil-aging. The results suggest that the SiNP can be injected into wettability-altered (water-wet) reservoirs/regions to help retain the water-wettability during the long-term oil production. The 0.5 wt% SiNP dispersions transported through 18 mD limestone cores without any plugging. The SiNP retention was measured to be 2.5 mg/m 2 , much higher than that of the anionic surfactant.

02 PETROLEUM↗

Novel deformation function creating or destroying any number of even kink solutions

Here, we present a one-parameter family of deformation functions f(Φ) which have novel properties. Firstly, the deformation function is its own inverse. We show that a class of potentials remains invariant under this deformation. Further, when applied to a certain class of kink bearing potentials, one obtains potentials which are not bounded from below. Besides, we show that there is a wide class of potentials having power law kink tails which are connected by this deformation but the corresponding kink tails of the two potentials have different asymptotic behavior. Finally, we show that when this deformation function is applied to an appropriate one-parameter family of potentials having two kink solutions, it creates new potentials with an arbitrary even number (2n) of kink solutions. Conversely, by starting from this potential with 2n kink solutions the deformation function annihilates 2n-2 kinks and we get back the potential which we started with having only two kink solutions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Deep spectral CNN for laser induced breakdown spectroscopy

This work proposes a spectral convolutional neural network (CNN) operating on laser induced breakdown spectroscopy (LIBS) signals to learn to (1) disentangle spectral signals from the sources of sensor uncertainty (i.e., pre-process) and (2) get qualitative and quantitative measures of chemical content of a sample given a spectral signal (i.e., calibrate). Once the spectral CNN is trained, it can accomplish either task through a single feed-forward pass, with real-time benefits and without any additional side information requirements including dark current, system response, temperature and detector-to-target range. Our experiments demonstrate that the proposed method outperforms the existing approaches used by the Mars Science Lab for pre-processing and calibration for remote sensing observations from the Mars rover, ‘Curiosity’.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Drug discovery efforts at George Mason University

With over 39,000 students, and research expenditures in excess of $200 million, George Mason University (GMU) is the largest R1 (Carnegie Classification of very high research activity) university in Virginia. Mason scientists have been involved in the discovery and development of novel diagnostics and therapeutics in areas as diverse as infectious diseases and cancer. Below are highlights of the efforts being led by Mason researchers in the drug discovery arena. To enable targeted cellular delivery, and non-biomedical applications, Veneziano and colleagues have developed a synthesis strategy that enables the design of self-assembling DNA nanoparticles (DNA origami) with prescribed shape and size in the 10 to 100 nm range. The nanoparticles can be loaded with molecules of interest such as drugs, proteins and peptides, and are a promising new addition to the drug delivery platforms currently in use. The investigators also recently used the DNA origami nanoparticles to fine tune the spatial presentation of immunogens to study the impact on B cell activation. These studies are an important step towards the rational design of vaccines for a variety of infectious agents. To elucidate the parameters for optimizing the delivery efficiency of lipid nanoparticles (LNPs), Buschmann, Paige and colleagues have devised methods for predicting and experimentally validating the pKa of LNPs based on the structure of the ionizable lipids used to formulate the LNPs. These studies may pave the way for the development of new LNP delivery vehicles that have reduced systemic distribution and improved endosomal release of their cargo post administration. To better understand protein-protein interactions and identify potential drug targets that disrupt such interactions, Luchini and colleagues have developed a methodology that identifies contact points between proteins using small molecule dyes. The dye molecules noncovalently bind to the accessible surfaces of a protein complex with very high affinity, but are excluded from contact regions. When the complex is denatured and digested with trypsin, the exposed regions covered by the dye do not get cleaved by the enzyme, whereas the contact points are digested. The resulting fragments can then be identified using mass spectrometry. The data generated can serve as the basis for designing small molecules and peptides that can disrupt the formation of protein complexes involved in disease processes. For example, using peptides based on the interleukin 1 receptor accessory protein (IL-1RAcP), Luchini, Liotta, Paige and colleagues disrupted the formation of IL-1/IL-R/IL-1RAcP complex and demonstrated that the inhibition of complex formation reduced the inflammatory response to IL-1B. Working on the discovery of novel antimicrobial agents, Bishop, van Hoek and colleagues have discovered a number of antimicrobial peptides from reptiles and other species. DRGN-1, is a synthetic peptide based on a histone H1-derived peptide that they had identified from Komodo Dragon plasma. DRGN-1 was shown to disrupt bacterial biofilms and promote wound healing in an animal model. The peptide, along with others, is being developed and tested in preclinical studies. Other research by van Hoek and colleagues focuses on in silico antimicrobial peptide discovery, screening of small molecules for antibacterial properties, as well as assessment of diffusible signal factors (DFS) as future therapeutics. The above examples provide insight into the cutting-edge studies undertaken by GMU scientists to develop novel methodologies and platform technologies important to drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗

Techno-economic and life cycle assessment of aluminum electrorefining from mixed scraps using ionic liquid

Aluminum production from bauxite ore uses significantly high amount of energy and capital expenditure. Recycle and reuse of aluminum can be economical and minimize the environmental impacts. Smelter based recycle and reuse of aluminum is used in recent days, however, it also uses high amount of energy with high cost of production and yields high life cycle impacts. The University of Alabama has developed aluminum electrorefining technology from mixed scraps using ionic liquids as an alternative to traditional smelter based recycle and reuse. This study has explored the techno-economical, and life cycle viability of that technology. An excel-based techno-economic and life cycle assessment model was developed at Idaho National Laboratory for techno-economic and life cycle assessment. SimaPro was used to get the necessary database for the life cycle assessment. This study determined that a 20,000 kg/day ionic liquid-based electrorefining system can be profitable with a net yearly profit of $2.00 million. Further, in terms of net global warming potential, it emits 0.92 kg CO 2 equivalent per kg of aluminum recycled, whereas the traditional smelter-based recycle technology emits 1.57 kg CO 2 equivalent per kg of aluminum recycled, and the aluminum production from bauxite ore emits 17.8 kg CO 2 equivalent per kg of aluminum produced. In other life cycle assessment categories, electrorefining of aluminum emits >88 % less than aluminum production from bauxite ore and it is also better than traditional aluminum recycling in six out of ten categories studied. This makes ionic liquid-based electrorefining technology a very promising technology in terms of process economics and environmental sustainability.

36 MATERIALS SCIENCE↗

Long-living excited states of a 2D diamagnetic exciton

Hydrogenic excited states of a 2D exciton are degenerate. In the presence of a weak magnetic field, the -states with a zero momentum of the center of mass get coupled to the -states with finite momentum of the center of mass. This field-induced coupling leads to a strong modification of the dispersion branches of the exciton spectrum. Namely, the lower branch acquires a shape of a “mexican hat” with a minimum at a finite momentum. At certain magnetic field, exciton branches exhibit a linear crossing, similarly to the spectrum of a 2D electron in the presence of spin–orbit coupling. While spin is not involved, degenerate and states play the role of the spin projections. Lifting of degeneracy due to diamagnetic shifts and deviation of electron–hole attraction from purely Coulomb suppresses the linear crossing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Establishment and characterization of a novel conditionally immortalized human parietal epithelial cell line

Highlights: • A novel conditionally immortalized human parietal epithelial cell (ciPEC) line was created. • ciPECs were isolated out of fresh human kidney tissue from an infant. • ciPECs show specific PEC characteristics. • ciPECs show no or little podocyte and glomerular endothelial cell marker expression. • ciPECs can be activated by IL-1β treatment. Parietal epithelial cells (PECs) are epithelial cells in the kidney, surrounding Bowman's space. When activated, PECs increase in cell volume, proliferate, migrate to the glomerular tuft and excrete extracellular matrix. Activated PECs are crucially involved in the formation of sclerotic lesions, seen in focal segmental glomerulosclerosis (FSGS). In FSGS, a number of glomeruli show segmental sclerotic lesions. Further disease progression will lead to increasing number of involved glomeruli and gradual destruction of the affected glomeruli. Although the involvement of PECs in FSGS has been acknowledged, little is known about the molecular processes driving PEC activation. To get more insights in this process, accurate in vivo and in vitro models are needed. Here, we describe the development and characterization of a novel conditionally immortalized human PEC (ciPEC) line. We demonstrated that ciPECs are differentiated when grown under growth-restrictive conditions and express important PEC-specific markers, while lacking podocyte and endothelial markers. In addition, ciPECs showed PEC-like morphology and responded to IL-1β treatment. We therefore conclude that we have successfully generated a novel PEC line, which can be used for future studies on the role of PECs in FSGS.

60 APPLIED LIFE SCIENCES↗

Construction of extracellular matrix-based 3D hydrogel and its effects on cardiomyocytes

Highlights: • SOD and Triton X-100 could efficiently decellularize cells to get cardiac ECM. • Main proteins of cECM were fibronectin, collagen, elastin, fibrillin, laminin, etc. • 75% cECM-containing 3D hydrogel promoted cell proliferation and anti-apoptosis. • cECM3DH facilitated the differentiation of ESCs into CMs. • APcECM3DH was more conducive to NCM and ESC-derived CM maturation. Some discoveries resulted from 2-dimensional (2D) cultured cardiac cells have been disqualified in animal testing and later clinical trials. Extracellular matrix (ECM) plays a vital role in cardiac homeostasis, cardiac ECM (cECM)-based 3D cell cultures can mimics the physiological and pathological conditions in vivo closely, it is hopeful of addressing this challenge. Construction of cECM-based 3-dimensional (3D) hydrogel (cECM3DH) and its effects on cell behaviors were studied here. The results indicated that cellular compartments could be efficiently removed from heart tissue via sodium dodecyl sulfonate (SDS)- and Triton X-100-mediated decellularization, remaining the natural fibrous network structure and major proteins. 3D hydrogel consisted of 1 × 10{sup 7} cells/mL cells and 75% cECM could promote the proliferation and anti-apoptosis ability of human embryonic kidney (HEK)-293T cells. 0.25% trypsin or 0.20% collagenase was suitable to retrieve these cells from 3D hydrogel for further researches. Compared with 2D culture system, cECM3DH could significantly increase the proportion of GATA 4{sup +} cardiomyocytes (CMs) derived from heart tissue of neonatal mouse or induced differentiation of embryonic stem cells (ESCs) (P < 0.05) The expression levels of mature genes including cTnT, JCN, CaV1.2, MYL2, CASQ2, NCX1, and Cx43 of these CMs in adult pig cECM-based 3D hydrogel (APcECM3DH) were significantly higher than that in 2D culture system and in newborn piglet cECM-based 3D hydrogel (NPcECM3DH), respectively (P < 0.05). Therefore, cECM3DH supports the generation of primary CMs and ESC-derived CMs, APcECM3DH was more conducive to promoting CM maturation, which contributes to building 3D model for pathogenesis exploration, drug screening, and regenerative medicine of heart diseases.

60 APPLIED LIFE SCIENCES↗

Multidisciplinary concurrent optimization framework for multi-phase building design process

Modern day building design projects require multidisciplinary expertise from architects and engineers across various phases of the design (conceptual, preliminary, and detailed) and construction processes. The Architecture Engineering and Construction (AEC) community has recently shifted gears toward leveraging design optimization techniques to make well-informed decisions in the design of buildings. However, most of the building design optimization efforts are either multidisciplinary optimization confined to just a specific design phase (conceptual/preliminary/detailed) or single disciplinary optimization (structural/thermal/daylighting/energy) spanning across multiple phases. Complexity in changing the optimization setup as the design progresses through subsequent phases, interoperability issues between modeling and physics-based analysis tools used at later stages, and the lack of an appropriate level of design detail to get meaningful results from these sophisticated analysis tools are few challenges that limit multi-phase multidisciplinary design optimization (MDO) in the AEC field. Here this paper proposes a computational building design platform leveraging concurrent engineering techniques such as interactive problem structuring, simulation-based optimization using meta models for energy and daylighting (machine learning based) and tradespace visualization. The proposed multi-phase concurrent MDO framework is demonstrated by using it to design and optimize a sample office building for energy and daylighting objectives across multiple phases. Furthermore, limitations of the proposed framework and future avenues of research are listed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗