Charge ordering (CO) is a (first- or second-order) occurring mostly in strongly correlated materials such as. Due to the strong interaction between electrons, are localized on different sites leading to a disproportionation and an. It appears in different patterns ranging from vertical to horizontal stripes to a checkerboard–like pattern, and it is not limited to the two-dimensional case.
The charge order transition is accompanied by and may lead to. It is often found in close proximity to. Charge order patternsBending and breaking of stripes in a charge ordered manganiteThis long range order phenomena was first discovered in magnetite (Fe 3O 4) by Verwey in 1939.He observed an increase of the by two orders of magnitude at T CO=120K, suggesting a phase transition which is now well known as the Verwey transition. He was the first to propose the idea of an ordering process in this context. The charge ordered structure of magnetite was solved in 2011 by a group led by with the results published in. Periodic lattice distortions associated with charge order were later mapped in the manganite lattice to reveal striped domains containing topological disorder.
Iron oxides are fundamentally important compounds for basic and applied sciences as well as in numerous industrial applications. In this work we report the synthesis and investigation of a new binary iron oxide with the hitherto unknown stoichiometry of Fe 7O 9. This new oxide was synthesized at high-pressure high-temperature (HP-HT) conditions, and its black single crystals were successfully recovered at ambient conditions.
Verwey Transition Lead To Semiconducitng To Metallic Behaviour Near 120 K
By means of single crystal X-ray diffraction we determined that Fe 7O 9 adopts a monoclinic C2/m lattice with the most distorted crystal structure among the binary iron oxides known to date. The synthesis of Fe 7O 9 opens a new portal to exotic iron-rich ( M,Fe) 7O 9 oxides with unusual stoichiometry and distorted crystal structures. Moreover, the crystal structure and phase relations of such new iron oxide groups may provide new insight into the cycling of volatiles in the Earth’s interior. Comparison of unit cells of crystal structures of iron oxides.( a) High-pressure orthorhombic polymorph of Fe 3O 4, ( b) Monoclinic Fe 7O 9 polymorph discovered in the present work. ( c) Orthorhombic Cmcm polymorph of Fe 4O 5 discovered in ref.
( d) Orthorhombic Cmcm polymorph of Fe 5O 6 discovered in ref. Different colors of the octahedra denote different crystallographic sites for Fe ions.At the moment the stability field of this new Fe 7O 9 polymorph is not well defined, although it appears to lie at pressures higher than those of Fe 4O 5 and Fe 5O 6.
The chemical compositions and the structural phases of iron-magnesium oxides in the Earth’s mantle remain a disputed issue that requires in situ investigations at HP-HT conditions under different oxygen fugacities. In this regard, the unexpected discovery of a Fe 7O 9 polymorph provides new insight into possible compositions of mantle phases, and provides a new type compound that may play a key role in determining physical and chemical properties.The new oxide, Fe 7O 9, is a compound with a ratio of Fe 3+/Fe 2+ intermediate between those of Fe 3O 4 and Fe 4O 5.
Both Fe 3O 4 and Fe 4O 5 are model systems for investigations of Fe 2+–Fe 3+ interactions in solids, demonstrating enigmatic low-temperature phase transitions of ‘metal-insulator’-type that lead to the formation of exotic ‘trimeron quasiparticles’ in Fe 3O 4 or to even more intricate ordering patterns in Fe 4O 5. We note that the low-temperature Verwey transition in Fe 3O 4 has had a strong impact on solid state physics and chemistry for decades.
Thus, Fe 7O 9 presents an exciting compound that promises important implications for geosciences, solid state physics and chemistry with potential for industrial applications.The recently discovered iron oxides may play important roles in the cycling of volatiles in the Earth’s deep interior,. For instance, oxygen could be released in the deeper part of the lower mantle via decomposition reactions of Fe 2O 3 and Fe 3O 4 into Fe 5O 7 and Fe 25O 32 above 60 GPa. Further, it was recently reported that FeO 2 could be formed in the lower mantle as a product of FeOOH goethite decomposition. Moreover, this reaction could supply hydrogen to the surrounding mantle. Physical and chemical properties of the newly-discovered iron oxides can therefore provide novel insights into the chemical evolution of the Earth’s interior.
.:28.12 ℹ CiteScore:2018: 28.120CiteScore measures the average citations received per document published in this title. CiteScore values are based on citation counts in a given year (e.g. 2015) to documents published in three previous calendar years (e.g. 2012 – 14), divided by the number of documents in these three previous years (e.g.
.:28.12 ℹ CiteScore:2018: 28.120CiteScore measures the average citations received per document published in this title. CiteScore values are based on citation counts in a given year (e.g.
2015) to documents published in three previous calendar years (e.g. 2012 – 14), divided by the number of documents in these three previous years (e.g.
AbstractThe presence of heavy metals (HMs) in the environment is a major threat for humans. Magnetic proxies provide a rapid method for assessing the degree of HM pollution in environment. We have studied farmland soil irrigated with polluted river water in the vicinity of a steel plant in Loudi city (Hunan Province, China) to test the efficiency of magnetic methods for detecting the degree of HM pollution. Both magnetic and non-magnetic (microscopic, chemical and statistical) methods were used to characterize these farmland soils. Enhanced magnetic concentration values were found in the upper arable soil horizon (0–20 cm), which is related to the presence of spherical ∼10 to 30 μm sized magnetite particles.
The spatial distribution of magnetic concentration and HM contents in the farmland soils matches with the spatial pattern of these parameters in river sediments. These findings provide evidence that HM pollution of the farmland soil is mainly caused by irrigation with wastewater. HMs Zn, Pb, Cu, Cd, Co, Ni, V are well correlate with magnetic susceptibility ( χ).
The pollution load index (PLI) of all nine anthropogenic HMs (including also Cr and Mo) and log 10( χ) are significantly correlated. Using the resulting linear PLI−log 10(χ) function, values of χ can serve as a convenient tool for semi-quantifying the degree of HM pollution in the uppermost ∼20 cm of the studied farmland soils. These findings suggest that magnetic methods can generally serve as a convenient tool for detecting and mapping HM pollution in farmland soil irrigated with wastewater from sites nearby heavy industrial activities. 1 INTRODUCTIONWith the development of mining industry, smelting activities and metal treatments, heavy metal contamination of rivers and the accumulation of heavy metals in farmland soils irrigated with river water from nearby mining or smelting areas has drawn public attention. Enormous amounts of hazardous wastes were released from base-metal mining and smelting activities and transported into rivers, inducing potential health risks as well as affecting soil ecosystems in the long term (Cartwright et al.; Jung & Thornton; Nicholson et al.; Zhao et al.; Makino et al.; Fang et al.).Wastewater irrigation is a widespread practice worldwide and numerous studies have been published on wastewater-irrigated soils contaminated with heavy metals (Mapanda et al.; Rattan et al.; Muchuweti et al.; Rothenberg et al.; Arora et al.). River water with elevated levels of harmful heavy metals such as Cd and Pb was utilized for domestic purposes without any treatment (Awofolu et al.). Concentrations of Cu, Zn, Cr, Cd, Ni, Pb and As significantly exceeding their permitted limits in soils were found in wastewater-irrigated soils indicating an important role of the application of wastewater for potential environmental and health risks (Mapanda et al.; Rattan et al.; Al Omron et al.).
Excessive accumulation of heavy metals in agricultural soils through wastewater irrigation not only results in soil contamination, but also leads to elevated heavy metal uptake by crops and vegetables and thus affects food quality and safety (Liu et al.; Muchuweti et al.; Rothenberg et al.; Arora et al.; Khan et al.). Humans consuming vegetables grown on polluted soils ingest significant amounts of heavy metals (Arora et al.; Khan et al.; Al Omron et al.). It is therefore an important issue to disclose the degree and extent of heavy metal pollution in wastewater-irrigated farmland soil.There are precise standard chemical methods for quantifying heavy metal contents, however, these are relatively time consuming and expensive and therefore not suitable for performing mapping or monitoring of pollution with high spatial sample density.
Magnetic methods turned out to provide a fast, non-intrusive, and cost-efficient tool for investigating the degree, sources, and the evolution of anthropogenic pollution. Their potential use for various scenarios has been extensively studied within the last two decades (Oldfield; Evans & Heller; Blaha et al.; Zhang et al.). Significant correlation between magnetic concentration parameters (magnetic susceptibility or remanent parameters) and contents of heavy metals like Pb, Zn, Cu and Cd has been reported. Magnetic parameters were used as proxies for semi-quantifying heavy metal contents in topsoil and arable soil, river sediments, lake sediments and marine sediments (Chan et al.; Wang & Qin; Chaparro et al.; Canbay et al.; Duan et al.; Zhang et al.). These previous studies demonstrate the suitability of magnetic measurements as a complimentary tool for site assessment, allowing a better selection of chemical sampling sites and thus improving the efficiency of chemical mapping. However, to our knowledge, no results have been reported for magnetic detection of heavy metal pollution in farmland irrigated with wastewater.
This has prompted our present study in which we are evaluating whether magnetic parameters can be used as proxies for such type of scenarios.In this paper, results obtained by magnetic measurements and heavy metal analyses of farmland soil irrigated with polluted river water are presented and discussed. Our main objective is to understand the underlying processes and to quantify statistical relationships between magnetic parameters and heavy metal contents. Samples were taken from farmland soil irrigated with polluted water (for short we call it wastewater) from Lianshui River near a steel plant in Loudi city (Hunan Province, China). This target area was chosen because from previous studies the degree and spatial distribution of heavy metal pollution in river sediments at Loudi city was known and could be related to emissions from the steel plant (Zhang et al.).
2 SAMPLING AND METHODOLOGIESLoudi city covers about 426 km 2 and is located near the central part of Hunan Province, China (Fig. ). The major industry and main pollution source is a steel plant with iron smelting activities at the northwestern side of the city, operating because about 50 yr. Lianshui River flows through the city and passes the steel plant complex at the entrance of the urban area. Previous results revealed higher heavy metal contents (Zn, Pb, Cd, Cu etc.) in river silts near the steel plant (Zhang et al., ). Nearby farmland is usually irrigated with water from this river. During 2009 July 21–24, six vertical soil sections (FP1–FP6) from surface to a depth of ∼60 cm were collected within vegetable farmland close to Lianshui River.
The sampling sites were distributed from the upstream region (before entering the city) to the downstream region (after leaving the city area; (Fig. ). Sites FP1 through FP5 are distributed along Lianshui River, site FP6 is located at an artificial branch in which water from Lianshui River is flowing towards west. Site FP4 was collected in a private vegetable yard, irrigated with groundwater, whereas at all other sites the farmland is irrigated with river water. In this region, the Quaternary cover is uniform and represented by red loam on parent limestone rock (Pan & Yang ). All sampling sites show similar soil patterns: at the top a 15–20 cm thick layer of soil reworked by agricultural activities (ploughing) comprising by a mixture of original O, A and B horizons, below the unchanged part of the B horizon (20–25 cm thick) and the C horizon (Fig. ).
The colour of the B horizon is lighter than the top layer, but darker than the C horizon which consists of weathering limestone. All sections were sampled at 2.5 cm intervals for further measurements. A photograph of sampling site FP1 is shown as an example for typical soil profiles at Loudi area.In the laboratory, the soil samples were air-dried and mechanical sieved through a 1 mm mesh to remove small stones and plant debris. Plastic boxes, 2 cm × 2 cm × 2 cm in size, were filled with individual samples for magnetic measurements. A Bartington MS2B instrument (operating frequency of 470 Hz) was used for measuring mass-specific susceptibility ( χ) values. Laboratory-induced anhysteretic remanent magnetization (ARM) was imparted using a peak alternating field (AF) of 80 mT with a biasing superimposed direct current (DC) field of 50 μT parallel to the AF; χ ARM values were calculated by mass-normalized ARM per unit bias DC field. Isothermal remanent magnetization (IRM) experiments were performed with a 2G pulse magnetizer; the IRM acquired in a field of 1.0 Tesla (T) was regarded as saturation IRM (SIRM).
S-ratio values were determined by −IRM −300mT/SIRM. ARM and IRM intensities were measured with a 2G-760 U-channel SQUID magnetometer system.In addition, further magnetic analyses such as hysteretic loops and thermomagnetic curves were performed for representative samples.
Hysteresis loops were measured at room temperature using a Model 3900 Micromag vibrating magnetometer. Saturation magnetization at 1T (M s), saturation remanence ( M rs), and coercivity ( B c) were determined after subtracting the paramagnetic contribution. High temperature dependence of saturation magnetization ( M s- T) was measured from room temperature up to 800 °C using a variable field translation balance system (applied field 10 Am −1) in air atmosphere; the graphical method of (Gromme et al.) was applied to determine the Curie temperature. Low-temperature properties were measured using a Quantum Design MPMS XP-5 SQUID magnetometer (sensitivity of 5.0 × 10 −10Am 2). Samples were cooled down from 300 to 5 K in zero magnetic field and saturation remanance acquired in a 5-T field at 5 K was measured during warming from 5 to 300 K. Furthermore, the low temperature dependence of AC susceptibility at 4 μT and frequencies of 1 Hz and 1000 Hz was measured by the MPMS from 300 to 5 K.Diffuse reflectance spectroscopy (DRS) was applied on powder samples grind to.
(a) Sampling locations of farmland soil and (b) gridded depth section of the pollution load index (PLI anthro) of river sediments (Zhang et al.); (c–f) comparison of magnetic susceptibility ( χ) results of farmland soil (FP sites; this study) and river sediments nearby the farmland sites (Zhang et al.).Vertical variation of several magnetic parameters is displayed in Fig. Differences among the six farmland sites can be related to their position in respect to the steel plant and the city boundaries (see Fig. For a location map). Site FP4 exhibits the lowest χ values, being generally 30 cm, corresponding to the C horizon in Fig. ).
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Sections FP3 and FP5 exhibit the largest enhancement in the top layer (at depths 30 cm), the χ values of all sections are in the range of ∼10–40 × 10 −8 m 3 kg −1. The obvious drop of χ at the depth of ∼20 cm in most of vertical farmland profiles corresponds to the agricultural cultivating depth (Duan et al.). The vertical trend of SIRM (Fig. ) is similar to χ (Fig. ), and the correlation between χ and SIRM is highly significant (R 2 = 0.90), indicating that ferrimagnetic minerals are responsible for χ magnetic enhancement in the farmland samples. S-ratios (Fig. ) show a clear tendency of higher values for sites with higher χ values and a general decrease with depth. These results indicate that higher coercivity minerals (such as hematite or goethite) play an important role in the studied soils, but it is also evident that enhancement of χ is related to the contribution of lower coercivity ferrimagnetic phases such as magnetite. The ARM/SIRM ratio (Fig. ) is a magnetic grain size indicator higher ratios for a higher contribution of fine single domain (SD) particles and shows the following features (Fig. ): (i) Site FP4 reveals exceptionally high values suggesting a significantly higher portion of fine magnetic grains compared to the other sections; (ii) the sites with the strongest χ enhancement (FP3, FP5) show lower values in the upper soil horizon indicating a higher portion of larger magnetic particles.
The observations described above indicate that the studied farmland soils, accumulated a significant input of anthropogenic magnetic material, particularly at depths. Opera browser old version. SEM images and EDX analysis results of magnetic extracts from 0–10 cm depths in the middle-stream section FP3. 3.3 Concentrations of elementsFor most elements and sites, mean concentrations at depths of 0–20 cm are higher than those from depths 30 cm. Above the obvious boundary at ∼20 cm depth, values are relatively constant and quickly decrease below (Figs ), similar to magnetic concentration parameters (Fig. ).
Concentrations of Pb, Zn, Cu and Cd at 0–20 cm display the following order: FP3FP6FP5FP2FP1FP4 (Table; Figs ). Site FP4 does not reveal a notable enhancement in the upper horizon. Concentrations of Rb (Fig. ), Cs, Ba, Nd and Be are relatively similar in all sites and they are independent of depth. For Mo and Cr, a depth dependence can be recognized, but it is less pronounced than for Pb, Zn, Cu and Cd. Detailed results of mean concentrations of 14 elements and their standard deviations, separately calculated for the upper (0–20 cm depth) and lower (30 cm depth) horizons are given in Table. 4 DISCUSSION 4.1 Relationship between heavy metal concentrations and magnetic parametersThe lateral and vertical variations of magnetic concentration parameters ( χ, SIRM, ARM) and some typical elements are similar (Figs, and ). To determine how closely these variables are related to each other, bivariate and multivariate statistical analyses were performed.
Correlation coefficients ( r) between elements concentrations and logarithmic (log) magnetic concentration parameters ( χ, SIRM and χ ARM) are listed in Table. Data from all six sites were combined for bivariate regression. Logarithmic values of χ, SIRM and χ ARM were employed to prevent prohibitive levels of skewness in the statistical distributions. Magnetic concentration parameters show a good positive correlation ( r 0.6) with Pb, Zn, Cu and Cd, a moderate positive correlation (0.4. To evaluate similarities of sources of the measured heavy metals in the farmland soils, cluster analysis was performed by applying Ward's method.
According to the dendrogram (Fig. ) the measured 14 elements can be separated into three main groups: (I) Zn, Pb, Cu and Cd, joining together with magnetic concentration parameters ( χ, SIRM and χ ARM); (II) Co, Ni, V, Cr and Mo; (III) Cs, Nd, Be, Rb and Ba. Elements of groups I and II join together at a relatively higher level.
These elements reveal notable enhancements in the upper horizon and low values in the underlying horizon (e.g. Figs ), implying that magnetic particles and these heavy metals come from anthropogenic activities.
Different from groups I and II, the elements of group III do not have a significant relationship with magnetic concentration parameters (Table ); these element contents are relatively similar in all sites and are independent of depth (e.g. Noting that Nd and Rb in the study area mainly stem from weathering and erosion of parent rock (limestone; Pan & Yang; Wang & Wei ), we infer that the elements from group III come from natural pedogenic sources (e.g. Weathering and erosion of parent rocks). Dendrogram result of farmland samples from Ward's method of hierarchical cluster analysis including 14 elements and the three magnetic concentration parameters. 4.2 Source of magnetic particles and anthropogenic heavy metals in farmland soilsMagnetic and microscopic characteristics (Figs ) reveal that the magnetic mineralogy of the farmland soils at depths 30 cm (C horizon in Fig. ) is dominated by goethite, paramagnetic minerals, and some mainly ultrafine SP magnetite. These particles most likely stem from weathering and erosion of the parent limestone.
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In shallower depths 30 μm are absent in farmland soils, even in the downstream region of the steel plant. This is a clear indication that the magnetic spherules with diameters of ∼10–30 μm found in farmland soils may not come from the steel plant directly.A previous study (Zhang et al.) showed that magnetic susceptibility values of street dust in Loudi range between 109 and 13067 × 10 −8 m 3 kg −1, and the main sources of magnetic particles are the steel plant and traffic emissions. As we know, traffic pollution is limited to few metres around roads (Hoffman et al.; Zhang et al.); therefore, little contribution of pollutants from traffic is expected for the farmland soils.
The main wind direction in the Loudi region is from NW, which explains the distribution of magnetic particles emitted from the steel plant. Street dust samples in the north-western (near FP2, Fig. ), northeastern (near FP4, Fig. ) and eastern areas of Loudi city all showed low values of χ 30 cm, most of PLI anthro values of at FP3 are in the range of 2.0 ∼ 3.0 and still decreasing downwards, demonstrating that part the anthropogenic heavy metals even migrated into the soil horizon below the agricultural boundary depth at this most heavily polluted site. This is not the case at all the other sites, for which relatively stable values are reached and the PLI anthro is only around 1.0 ∼ 2.0 at depths 30 cm.
At these sites the deeper soil horizon is likely not affected by anthropogenic pollution. (a) Vertical sections of PLI anthro for all farmland soil sections calculated from the equation in b.