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At least 1,279 records · Page 71

Diversifying and perennializing plants in agroecosystems alters retention of new C and N from crop residues

Abstract Managing soils to retain new plant inputs is key to moving toward a sustainable and regenerative agriculture. Management practices, like diversifying and perennializing agroecosystems, may affect the decomposer organisms that regulate how new residue is converted to persistent soil organic matter. Here we tested whether 12 years of diversifying/perennializing plants in agroecosystems through extended rotations or grassland restoration would decrease losses of new plant residue inputs and, thus, increase retention of carbon (C) and nitrogen (N) in soil. We tracked dual‐labeled ( 13 C and 15 N), isotopically enriched wheat ( Triticum aestivum ) residue in situ for 2 years as it decomposed in three agroecosystems: maize–soybean (CS) rotation, maize–soybean–wheat plus red clover and cereal rye cover crops (CSW2), and spring fallow management with regeneration of natural grassland species (seven to 10 species; SF). We measured losses of wheat residue (C wheat and N wheat ) in leached soil solution and greenhouse gas fluxes, as well as how much was recovered in microbial biomass and bulk soil at 5‐cm increments down to 20 cm. CSW2 and SF both had unique, significant effects on residue decomposition and retention dynamics that were clear only when using nuanced metrics that able to tease apart subtle differences. For example, SF retained a greater portion of C wheat in 0–5 cm surface soils (155%, p = 0.035) and narrowed the C wheat to N wheat ratio ( p < 0.030) compared to CS. CSW2 increased an index of carbon‐retention efficiency, C wheat retained in the mesocosm divided by total measured, from 0.18 to 0.27 (49%, p = 0.001), compared to CS. Overall, we found that diversifying and extending the duration of living plants in agroecosystems can lead to greater retention of new residue inputs in subtle ways that require further investigation to fully understand.

McDaniel, Marshall D.↗

Higgs Inflation and the Electroweak Gauge Sector

Abstract We introduce a method that allows the Higgs to be the inflaton. The Higgs is considered as a pseudo‐Nambu‐Goldstone (pNG) boson of a global coset symmetry , which is spontaneously breaks at an energy scale . A suitable Chern−Simons (CS) interaction is given to it, with representing the dimensionless CS coupling strength and an decay constant. As a result, slow‐roll inflation occurs via ‐induced friction down a steep sinusoidal potential. To obey electroweak symmetry, the lowest‐order CS interaction is required to be quadratic in the Higgs, with the coupling strength . Higher‐order interaction terms keep the full Lagrangian nearly invariant under the approximate pNG shift symmetry. Employing the simplest symmetry coset , ‐folds of inflation occur when . Successfully explaining inflation necessitates small values of the decay constant, ; this in turn requires large , which is ruled out by electric dipole measurements. Although the electroweak hierarchy problem while achieving successful inflation, the real benefit is found in providing a different path to identifying the Higgs as the inflaton, outside the standard modified‐gravity framework.

Alexander, Stephon [Brown Center for Theoretical P↗

Determination of the Collins-Soper Kernel from Lattice QCD

We present lattice results for the non-perturbative Collins-Soper (CS) kernel, which describes the energy-dependence of transverse momentum-dependent parton distributions (TMDs). The CS kernel is extracted from the ratios of first Mellin moments of quasi-TMDs evaluated at different nucleon momenta. The analysis is done with dynamical N f = 2 + 1 clover fermions for the CLS ensemble H101 (a = 0. 0854 fm, m π = m K = 422 MeV). The computed CS kernel is in good agreement with experimental extractions and previous lattice studies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Measurement of the branching fraction of ${\textrm{D}}_{\textrm{s}}^{+}$ → τ + ν τ via τ + → μ+ν μ $\overline{\nu}$τ

Utilizing 7 . 33 fb - 1 of e + e - collision data taken at the center-of-mass energies of 4.128, 4.157, 4.178, 4.189, 4.199, 4.209, 4.219, and 4.226 GeV with the BESIII detector, the branching fraction of the leptonic decay ${D}_s^{+}$ → τ + ν τ via τ + → μ + ν μ $\overline{\nu}$ τ is measured to be ${\mathcal{B}}_{D_s^{+}\to {\tau}^{+}{\nu}_{\tau }}$ = (5 . 37 ± 0 . 17 stat ± 0 . 15 syst )%. Combining this branching fraction with the world averages of the measurements of the masses of τ + and ${D}_s^{+}$ as well as the lifetime of ${D}_s^{+}$, we extract the product of the decay constant of ${D}_s^{+}$ and the c → s Cabibbo-Kobayashi-Maskawa matrix element to be ${f}_{D_s^{+}}$ |V cs | = (246 . 7 ± 3 . 9 stat ± 3 . 6 syst ) MeV. Taking |V cs | from a global fit in the standard model we obtain ${f}_{D_s^{+}}$ = (253 . 4 ± 4 . 0 stat ± 3 . 7 syst ) MeV. Conversely, taking ${f}_{D_s^{+}}$ from lattice quantum chromodynamics calculations, we obtain |V cs | = 0 . 987 ± 0 . 016 stat ± 0 . 014 syst .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Smart manufacturing approach to manufacture bulk nanocrystalline aluminum for lightweight applications

In this research, a smart manufacturing approach was used to enhance the mechanical properties of aluminum (Al) for lightweight applications. The smart manufacturing involved cryomilling of Al powders with and without 5 wt.% magnesium (Mg) powders for varying durations followed by a high-pressure cold spray (HPCS) additive manufacturing process to prepare bulk components. The morphological changes, crystallite size, and composition of the cryomilled powders and cold sprayed (CS’ed) components were examined using scanning electron microscopy (SEM), x-ray diffraction (XRD), and transmission electron microscopy (TEM) techniques. The results showed that the crystallite size reduces with an increase in cryomilling time and the addition of Mg dopant. To test the mechanical properties of the bulk CS’ed components, microhardness tests were performed using a Vickers microhardness tester. Uniaxial tensile tests were also carried out to ascertain the material’s tensile properties. The mechanical testing results showed great improvement in the hardness and tensile strength of CS’ed Al–Mg samples as compared to pure Al samples. Subsequently, fractography analysis of the tensile failed samples was carried out to determine the nature of the failure. Here, the research article also discusses the inherent mechanisms for the improvement in mechanical properties of smart manufactured components as a result of Mg doping and cryomilling.

36 MATERIALS SCIENCE↗

Exploiting chitosan to improve the interface of nanocellulose reinforced polymer composites

Cellulose nanofibrils (CNFs) have been widely used as a nanofiller for polymer composite reinforcement due to their excellent mechanical properties. However, CNF is produced in water and needs to be dried prior to use in composite materials. The presence of hydroxyl groups on the surface of CNF creates strong hydrogen bonding that makes it difficult and costly to dry. Additionally, the hydrophilicity at the fiber surface results in agglomeration of CNFs within many polymer matrices. In this study, chitosan (CS) was co-precipitated with CNF to produce a dual-bonding filler for use in poly (lactic acid) (PLA) composites. CS promotes improved interfacial interaction within the polymer matrix by forming strong hydrogen bonds with the CNF and potential covalent bonds with the PLA. Finally, the results confirmed that the addition of a small amount of CS significantly improved the mechanical properties compared to PLA + CNF composites and neat PLA. The detailed study of the PLA + CNF/CS composites reveals the synergetic effect of the hydrogen and covalent bonding mechanism for PLA reinforcement.

59 BASIC BIOLOGICAL SCIENCES↗

Synthesis of CdZnTeSe single crystals for room temperature radiation detector fabrication: mitigation of hole trapping effects using a convolutional neural network

In this article, we report the growth of Cd 0.9 Zn 0.1 Te 0.97 Se 0.03 (CZTS) wide bandgap semiconductor single crystals for room temperature gamma-ray detection using a modified vertical Bridgman method. Charge transport properties measured in the radiation detectors, fabricated from the grown CZTS crystals, indicated signs of hole trapping. Hole traps inhibit high-resolution radiation detection especially for energetic gamma rays. Machine learning (ML) applications are gaining tremendous mpetus in improving device and sensor performance by compensating for limi tations arising from such intrinsic material properties. In this article, we describe a deep convolutional neural network (CNN) that has demonstrated remarkable efficiency in identifying the energy of a gamma photon detected by a CZTS detector. The CNN has been trained using simulated data that resemble output pulses from actual CZTS detectors when exposed to 662-keV gamma photons. The device properties required for the simulation have been derived from radiation detection measurements on a real Cd 0.9 Zn 0.1 Te 0.97 Se 0.03 detector fabricated in our laboratory. The CNN has been trained with detector pulses arising through photoelectric (PE) and Compton scattering (CS) separately. The percentage error in predicting the detected energies, within an extremely small duration of 0.28 ms, was found to be lower than 0.1% for gamma energies above 50 keV and for training datasets con taining PE and CS events separately. The CNN was also validated for a mixed PE and CS dataset to obtain a prediction error of 1%. Additionally, the effect of detector resolution on the efficiency of the CNN was also explored.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Monte Carlo neutronics benchmarks on nuclear fuel depletion: A review

Monte Carlo (MC) neutronics codes are used widely for academic and industrial needs. Several schemes of coupling MC neutronics code with isotope generation and depletion code exist, which are used for performing nuclear fuel depletion simulations. These simulations can estimate the inventory of isotopes in neutron irradiated nuclear reactor fuel. However, the accuracy of these simulations shall be validated through experiments. MC codes are seldom validated by isotopic benchmarks compared to criticality benchmarks. This work compiles and analyzes the fuel depletion benchmarks and validations used to analyze the performance of MC-based fuel depletion neutronics codes. Analyses of these benchmarks and validations showed that the computed concentrations of 133 Cs, 135 Cs, 137 Cs, 148 Nd, 239 Pu, 240 Pu, and 241 Pu in the irradiated fuel by the depletion codes agreed with the measured values within 10% error. However, the computed concentrations of 125 Sb, 242 Cm, 243 Cm, 244 Cm, 245 Cm, and 246 Cm had errors more than 15% compared to the measured values. As a result, Ventina depletion code showed the most accurate predictions for the greatest number of isotope concentrations compared to ORIGEN2 and CINDER90.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Promoting the oxidative coupling of methanol and dimethylamine using group 1 alkali metals on palladium-gold nanoparticles

PdAu/SiO 2 catalysts were synthesized by strong electrostatic adsorption (SEA) and characterized by TEM, DRIFTS, XRD, XAS, and O 2 -TPD. The use of group 1 alkali salt solutions to control pH during SEA syntheses led to uptake of alkali metals observed reductions in the densities of terminal silanol groups of the SiO 2 support. In the absence of alkali metals, PdAu/SiO 2 catalyzes oxidative C-N bond formation between methanol and dimethylamine (DMA), yielding dimethylformamide (DMF) with ∼95 % carbon selectivity (CO 2 ∼5 %) at temperatures below 413 K. When Na, K, and Cs were present on the catalyst, methyl formate (MF) and tetramethylurea (TMU) were observed as additional products (combined ∼30 % carbon selectivity) while only TMU was detected for the Li-promoted catalyst. Total coupling product rate increased for promoted samples in the order Li < Na < Cs < K, and the apparent kinetics over the Cs-promoted catalyst were distinct from those over the alkali-free catalyst as the apparent reaction order with respect to DMA decreased and the apparent activation energy increased. Finally, this work demonstrates the sensitivity of oxidative coupling reactions to alkali metal promoters and the opportunity to achieve alkali promotion of metal catalysts during SEA synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low-temperature liquid-phase formation of environmentally stable copper halide nanocrystal superlattices and their application to anticounterfeiting patterns

Nanocrystal superlattices have the potential to create a new class of semiconductor materials by combining the photophysical properties of individual nanocrystals with bulk-like structure performance. However, the principles underlying the direct formation of superlattices in liquid phase have not been thoroughly investigated, particularly, those consisting of exciton self-trapping metal halides. Here, in this work, we explore the formation of Cs 3 Cu 2 Br 5 nanocrystal superlattices via liquid-phase crystallization of growing nanocrystals over a reaction period of only a few seconds. Importantly, the reaction temperature and the precursor concentration were found to be key parameters governing the concomitant nanocrystal growth and superlattice formation. The resulting Cs 3 Cu 2 Br 5 superlattices had a well-defined face-centered cubic structure and emitted a single-band bright blue emission when exposed to 280 nm light. Owing to their advantages, such as low toxicity, reabsorption-free, narrow absorption, strong emission, and high environmental stability, the Cs 3 Cu 2 Br 5 superlattices were applicable to anti-counterfeiting applications. Our findings shed light on the liquid-phase assembly of nanocrystals into superlattices and highlight the potential applications of the superlattices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models

This study aims to implement a hybrid ensemble surrogate machine learning technique in predicting the compressive strength (CS) of concrete, an important parameter used for durability design and service life prediction of concrete structures in civil engineering projects. For this purpose, an experimental database consisting of 1030 records has been compiled from the machine learning repository of the University of California, Irvine. The database was used to train and validate four conventional machine learning (CML) models, namely Artificial Neural Network (ANN), Linear and Non-Linear Multivariate Adaptive Regression Splines (MARS-L and MARS-C), Gaussian Process Regression (GPR), and Minimax Probability Machine Regression (MPMR). Subsequently, the predicted outputs of CML models were combined and trained using ANN to construct the Hybrid Ensemble Model (HENSM). It is observed that the proposed HENSM produces higher predictive accuracy compared to the CML models used in the present study. The predictive performance of all models for CS prediction was compared using the testing dataset and it is found that the HENSM model attained the highest predictive accuracy in both phases. Based on the experimental results, the newly constructed HENSM model is very potential to be a new alternative in handling the overfitting issues of CML models and hence, can be used to predict the concrete CS, including the design of less polluting and more sustainable concrete constructions.

36 MATERIALS SCIENCE↗

Alkali-silica reaction products and cracks: X-ray micro-tomography-based analysis of their spatial-temporal evolution at a mesoscale

In this study, we propose a laboratory-scale methodology, based on X-ray micro-tomography and caesium (Cs) as a contrast agent, to advance the understanding of cracking due to alkali-silica reaction (ASR) in concrete. The methodology allows achieving a completely non-destructive and time-lapse characterization of the spatial-temporal patterns of both the cracks and the ASR products. While Cs addition slightly accelerated the ASR kinetics, the crack patterns, with and without Cs addition, were statistically equivalent. Cracks with ASR products appeared first in the aggregates, close to the interface with the cement paste. They propagated afterwards towards the aggregates interior. Some products were then extruded for several mm into air voids and cracks in the cement paste. This process suggests that, in the early stage, the ASR products may be a low-viscosity gel that can flow away from the source aggregate and may settle later elsewhere as a rigid phase, upon calcium uptake.

36 MATERIALS SCIENCE↗

Impact of cyber attacks on distributed compressive sensing based state estimation in power distribution grids

Modern power distribution grids suffer from multiple vulnerabilities due to the tight integration between the physical system and the cyber infrastructure. Sophisticated and malicious cyber attacks continue to adversely impact the grid operation leading to performance degradation, service interruption, and grid failure. State estimation plays an essential role in grid monitoring and advancing cyber-attack situational awareness. In this regard, this paper first proposes a distributed compressive sensing (CS) state estimation approach for an unobservable distribution grid. Further, the proposed distributed CS approach divides the distribution grid into sub-areas to perform local state estimation. Then an alternating direction method of multipliers (ADMM) based iterative information exchange among neighboring areas is employed to complete the estimation process. In this estimation process, the impact of loss of measurement data, false data injection (FDI), replay, and neighborhood cyber-attacks is analyzed. Extensive simulations are performed on the IEEE 37-bus and IEEE 123-bus standard networks to demonstrate the algorithm’s robustness to the aforementioned cyber-attacks. A quantitative analysis of computational complexity and simulation time of the distributed CS based approach is also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Post-irradiation examinations of annular mixed oxide fuels with average burnup 4 and 5% FIMA

In this paper, we present post-irradiation examination results on two type of annular mixed oxide fuel pins irradiated in the Fast Flux Test Facility (FFTF) sodium cooled reactor to an average burnup between 4% and 5% fission of initial heavy atom (FIMA). The pins differed only from the initial Pu content, which was 22 wt% and 26 wt%, respectively. The overall performance of the pins was excellent, in line with previous historical results. The pins with higher Pu content experienced higher irradiation temperatures which influenced the fission gas release, fuel swelling, and Cs distribution compared to the other pins. All the post-irradiation examinations results are discussed against the irradiation parameters. In particular, the pins with higher initial Pu content, i.e., 26 wt%, experienced higher power that resulted in enhanced fission gas release compared to the other two pins with 22 wt% initial Pu content. For the pins with higher fission gas release, onset of Cs redistribution was observed. The two pins that had lower initial Pu content and burnup showed a Cs axial distribution similar to the as-produced one.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Electron microscopy characterization of the fuel-cladding interaction in medium burnup annular fast reactor MOX

In this work, we present electron microscopy data focused on the fuel-cladding interaction layer in annular fast reactor MOX with HT-9 cladding at medium burnup. In agreement with previous literature data, the volatile fission products Cs, Te and I have migrated radially into the extreme fuel periphery and partially interacted with the cladding. The accumulation of Cs has occurred in the outermost rim of the fuel pellet, where grain recrystallization has also been observed. Significant amounts of Pd have been found in the interaction zone, particularly in the sample taken from the upper half of the fissile column where the cladding temperatures are higher. At this axial location, Cr has been enriched at the cladding inner surface and diffused into the fuel. Furthermore, chromium remains mainly in metallic form, but locally formed oxides. The fission products Cs, Te and I are found, with variable composition, in form of nanocrystalline regions dispersed in the metallic Cr-rich layer. The morphology and chemical characteristics of the layer suggest a non-oxidative corrosion mechanism as principal cladding degradation phenomenon occurring in this sample, with local onset of Cr oxidation within the nanocrystalline precipitates.

36 MATERIALS SCIENCE↗

Manufacturing Oxide Dispersion Strengthened (ODS) steel plate via cold spray and friction stir processing

Oxide dispersion strengthened (ODS) steels, traditionally fabricated by ball milling and conventional powder metallurgy techniques to achieve bulk form, followed by intricate rolling and thermal treatment steps to achieve plate or sheet form. Here, we present a novel processing route that combines cold spray (CS) with friction stir processing (FSP) to manufacture ODS steel plate directly from gas atomization reaction synthesis (GARS)-prepared powder, thus no rolling steps involved. Microstructural and mechanical characterizations were performed to assess the quality and properties of the resulting ODS steel plate. Our findings demonstrate that the slightly porous CS deposited layer was fully consolidated after FSP, yielding a fully dense ODS steel plate that exhibited a favorable tradeoff between strength and ductility upon extraction from the substrate. Furthermore, through microstructural analysis, we revealed the presence of an appreciable density (∼10 22 /m 3 ) of nano-sized oxide particles, with the majority being smaller than 5 nm via the combined CS + FSP fabrication route. This work serves as a first proof-of-concept demonstration of the manufacturing approach described herein, offering a possible alternative route for producing ODS steel plates.

36 MATERIALS SCIENCE↗

Origin of ultralow phonon transport and strong anharmonicity in lead-free halide perovskites

All-inorganic lead-free halide double perovskites offer a promising avenue toward non-toxic, stable optoelectronic materials, properties that are missing in their prominent lead-containing counterparts. Their large thermopowers and high carrier mobilities also make them promising for thermoelectric applications. Here, in this work, we present a first-principles study of the lattice vibrations and thermal transport behaviors of Cs 2 SnI 6 and γ-CsSnI 3 , two prototypical compounds in this materials class. We show that conventional static zero temperature density functional theory (DFT) calculations severely underestimate the lattice thermal conductivities (κ l ) of these compounds, indicating the importance of dynamical effects. By calculating anharmonic renormalized phonon dispersions, we show that some optic phonons significantly harden with increasing temperature (T), which reduces the scattering of heat carrying phonons and enhances calculated κ l values when compared with standard zero temperature DFT. Furthermore, we demonstrate that coherence contributions to κ l , arising from wave like phonon tunneling, are important in both compounds. Overall, calculated κ l with temperature-dependent interatomic force constants, built from particle and coherence contributions, are in good agreement with available measured data, for both magnitude and temperature dependence. Large anharmonicity combined with low phonon group velocities yield ultralow values, with room temperature values of 0.26 W/m-K and 0.72 W/m-K predicted for Cs 2 SnI 6 and γ-CsSnI 3 , respectively. We further show that the lattice dynamics of these compounds are highly anharmonic, largely mediated by rotation of the SnI6 octahedra and localized modes originating from Cs rattling motion. These thermal characteristics combined with their previously computed excellent electronic properties make these perovskites promising candidates for optoelectronic and room temperature thermoelectric applications.

36 MATERIALS SCIENCE↗