Effects of chemical composition and B2 order on phonons in bcc Fe–Co alloys

The phonon density of states (DOS) gives insight into interatomic forces and provides the vibrational entropy, making it a key thermodynamic function for understanding alloy phase transformations. Nuclear resonant inelastic x-ray scattering and inelastic neutron scattering were used to measure the chemical dependence of the DOS of bcc Fe–Co alloys. For the equiatomic alloy, the A2→B2 (chemically disordered→chemically ordered) phase transformation caused measurable changes in the phonon spectrum. The measured change in vibrational entropy upon ordering was −0.02±0.02 k_B/atom, suggesting that vibrational entropy results in a reduction in the order–disorder transition temperature by 60±60 K. The Connolly–Williams cluster inversion method was used to obtain interaction DOS (IDOS) curves that show how point and pair variables altered the phonon DOS of disordered bcc Fe–Co alloys. These IDOS curves accurately captured the change in the phonon DOS and vibrational entropy of the B2 ordering transition

Local and nonlocal solvable structures in ODEs reduction

Solvable structures, likewise solvable algebras of local symmetries, can be used to integrate scalar ODEs by quadratures. Solvable structures, however, are particularly suitable for the integration of ODEs with a lack of local symmetries. In fact, under regularity assumptions, any given ODE always admits solvable structures even though finding them in general could be a very difficult task. In practice a noteworthy simplification may come by computing solvable structures which are adapted to some admitted symmetry algebra. In this paper we consider solvable structures adapted to local and nonlocal symmetry algebras of any order (i.e., classical and higher). In particular we introduce the notion of nonlocal solvable structure

Reviews and syntheses: Iron – a driver of nitrogen bioavailability in soils?

An adequate supply of bioavailable nitrogen (N) is critical to soil microbial communities and plants. Over the last decades, research efforts have rarely considered the importance of reactive iron (Fe) minerals in the processes that produce or consume bioavailable N in soils compared to other factors such as soil texture, pH, and organic matter (OM). However, Fe is involved in both enzymatic and non-enzymatic reactions that influence the N cycle. More broadly, reactive Fe minerals restrict soil organic matter (SOM) cycling through sorption processes but also promote SOM decomposition and denitrification in anoxic conditions. By synthesizing available research, we show that Fe plays diverse roles in N bioavailability. Fe affects N bioavailability directly by acting as a sorbent, catalyst, and electron transfer agent or indirectly by promoting certain soil features, such as aggregate formation and stability, which affect N turnover processes. These roles can lead to different outcomes in terms of N bioavailability, depending on environmental conditions such as soil redox shifts during wet–dry cycles. We provide examples of Fe–N interactions and discuss the possible underlying mechanisms, which can be abiotic or microbially meditated. We also discuss how Fe participates in three complex phenomena that influence N bioavailability: priming, the Birch effect, and freeze–thaw cycles. Furthermore, we highlight how Fe–N bioavailability interactions are influenced by global change and identify methodological constraints that hinder the development of a mechanistic understanding of Fe in terms of controlling N bioavailability and highlight the areas of needed research.</p

Technical report: Modeling nitrate leaching risk from specialty crop fields during on-farm managed floodwater recharge in the Kings Groundwater Basin and the potential for its management

This project has focused on better understanding the potential impact of On-Farm Flood Capture and Recharge (OFFCR) on groundwater quality pertaining to salts and nitrate and on assessing potential management opportunities. To achieve these goals, we used a combination of field and modeling studies. For the field study, soil cores were taken to a depth of 30 feet in replicate across fields with three different specialty crops identified as important to the San Joaquin Valley (tomatoes, almonds, vineyards) and with potential suitability for OFFCR. A prime goal of the field study was to provide data for parameterizing two models developed to assess nitrate, salt and water transport through the vadose zone, prior to percolating into the groundwater aquifer. However, the field study also resulted in key findings that show its value as a stand-alone study: 1) Nitrate concentrations are highest in the upper vadose zone and affected by texture. Those effects are not evident in the deeper vadose zone. 2) Vadose zone nitrate concentrations are affected by the crop grown. These results suggest an opportunity for lower legacy mass transport for grapes and higher legacy mass transport for both tomatoes and almonds. 3) Variability in individual farmers’ past and present fertilizer and water management practices contributes to different legacy salt and nitrate loads in the vadose zone. Data from the field study and other related and concurrent OFFCR field efforts were used during model development. The overall modeling approach was designed to model nitrate and salt transport for lands under OFFCR operation for different crop types, vadose zone characteristics and groundwater characteristics. The defined goals of this design and modeling approach were to: 1) model nitrate and salt movement through the vadose zone and into groundwater; 2) test the model against scenarios that consider different recharge rates, cultural practices, soil types, and depths to groundwater, assessing the timing and magnitude of loading through the vadose zone and the effects on underlying groundwater; and 3) recommend management practices to mitigate potential groundwater impacts. To achieve these goals, two models were integrated to simulate nitrate and salt transport through the vadose zone to groundwater under different scenarios: a 1D Hydrus model and an analytical groundwater model (AGM)

New results on group classification of nonlinear diffusion-convection equations

Using a new method and additional (conditional and partial) equivalence transformations, we performed group classification in a class of variable coefficient $(1+1)$-dimensional nonlinear diffusion-convection equations of the general form $f(x)u_t=(D(u)u_x)_x+K(u)u_x.$ We obtain new interesting cases of such equations with the density $f$ localized in space, which have large invariance algebra. Exact solutions of these equations are constructed. We also consider the problem of investigation of the possible local trasformations for an arbitrary pair of equations from the class under consideration, i.e. of describing all the possible partial equivalence transformations in this class.Comment: LaTeX2e, 19 page

Group Analysis of Variable Coefficient Diffusion-Convection Equations. I. Enhanced Group Classification

We discuss the classical statement of group classification problem and some its extensions in the general case. After that, we carry out the complete extended group classification for a class of (1+1)-dimensional nonlinear diffusion--convection equations with coefficients depending on the space variable. At first, we construct the usual equivalence group and the extended one including transformations which are nonlocal with respect to arbitrary elements. The extended equivalence group has interesting structure since it contains a non-trivial subgroup of non-local gauge equivalence transformations. The complete group classification of the class under consideration is carried out with respect to the extended equivalence group and with respect to the set of all point transformations. Usage of extended equivalence and correct choice of gauges of arbitrary elements play the major role for simple and clear formulation of the final results. The set of admissible transformations of this class is preliminary investigated.Comment: 25 page

Realizations of Real Low-Dimensional Lie Algebras

Using a new powerful technique based on the notion of megaideal, we construct a complete set of inequivalent realizations of real Lie algebras of dimension no greater than four in vector fields on a space of an arbitrary (finite) number of variables. Our classification amends and essentially generalizes earlier works on the subject. Known results on classification of low-dimensional real Lie algebras, their automorphisms, differentiations, ideals, subalgebras and realizations are reviewed.Comment: LaTeX2e, 39 pages. Essentially exetended version. Misprints in Appendix are correcte

Enhanced Group Analysis and Exact Solutions of Variable Coefficient Semilinear Diffusion Equations with a Power Source

A new approach to group classification problems and more general investigations on transformational properties of classes of differential equations is proposed. It is based on mappings between classes of differential equations, generated by families of point transformations. A class of variable coefficient (1+1)-dimensional semilinear reaction-diffusion equations of the general form $f(x)u_t=(g(x)u_x)_x+h(x)u^m$ ($m\ne0,1$) is studied from the symmetry point of view in the framework of the approach proposed. The singular subclass of the equations with $m=2$ is singled out. The group classifications of the entire class, the singular subclass and their images are performed with respect to both the corresponding (generalized extended) equivalence groups and all point transformations. The set of admissible transformations of the imaged class is exhaustively described in the general case $m\ne2$. The procedure of classification of nonclassical symmetries, which involves mappings between classes of differential equations, is discussed. Wide families of new exact solutions are also constructed for equations from the classes under consideration by the classical method of Lie reductions and by generation of new solutions from known ones for other equations with point transformations of different kinds (such as additional equivalence transformations and mappings between classes of equations).Comment: 40 pages, this is version published in Acta Applicanda Mathematica

Higher yields and lower methane emissions with new rice cultivars

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Breeding high-yielding rice cultivars through increasing biomass is a key strategy to meet rising global food demands. Yet, increasing rice growth can stimulate methane (CH4 ) emissions, exacerbating global climate change, as rice cultivation is a major source of this powerful greenhouse gas. Here, we show in a series of experiments that high-yielding rice cultivars actually reduce CH4 emissions from typical paddy soils. Averaged across 33 rice cultivars, a biomass increase of 10% resulted in a 10.3% decrease in CH4 emissions in a soil with a high carbon (C) content. Compared to a low-yielding cultivar, a high-yielding cultivar significantly increased root porosity and the abundance of methane-consuming microorganisms, suggesting that the larger and more porous root systems of high-yielding cultivars facilitated CH4 oxidation by promoting O2 transport to soils. Our results were further supported by a meta-analysis, showing that high-yielding rice cultivars strongly decrease CH4 emissions from paddy soils with high organic C contents. Based on our results, increasing rice biomass by 10% could reduce annual CH4 emissions from Chinese rice agriculture by 7.1%. Our findings suggest that modern rice breeding strategies for high-yielding cultivars can substantially mitigate paddy CH4 emission in China and other rice growing regions.This work was supported by the National Key Research and Development Program China (2016YFD0300903, 2016YFD0300501, and 2015BAC02B02), Special Fund for Agro-scientific Research in the Public Interest (201503122), Central Public interest Scientific Institution Basal Research Fund of Institute of Crop Science, the Innovation Program of CAAS (Y2016PT12, Y2016XT01), and the China Scholarship Council

A high resolution record of Greenland mass balance

We map recent Greenland Ice Sheet elevation change at high spatial (5-km) and temporal (monthly) resolution using CryoSat-2 altimetry. After correcting for the impact of changing snowpack properties associated with unprecedented surface melting in 2012, we find good agreement (3 cm/yr bias) with airborne measurements. With the aid of regional climate and firn modelling, we compute high spatial and temporal resolution records of Greenland mass evolution, which correlate (R=0.96) with monthly satellite gravimetry, and reveal glacier dynamic imbalance. During 2011-2014, Greenland mass loss averaged 269±51 Gt/yr. Atmospherically-driven losses were widespread, with surface melt variability driving large fluctuations in the annual mass deficit. Terminus regions of five dynamically-thinning glaciers, which constitute less than 1% of Greenland's area, contributed more than 12% of the net ice loss. This high-resolution record demonstrates that mass deficits extending over small spatial and temporal scales have made a relatively large contribution to recent ice sheet imbalance