不同条件下水钠锰矿对氧化锑的氧化性溶解影响

<正>锑(Sb)是元素周期表中第五周期VA主族元素,原子序数和原子量分别为51和121.75。锑原子最外层结构为5s25p3,以p3充填形式存在,较易失去电子和捕获电子,使得锑具有较强的活性。由于锑潜在的慢性毒性及被证实具有致癌性,其被美国环保局及欧盟列为优先污染物,在巴塞尔公约中关于危险废物的越境迁移限定中将锑列为危险废物之列。我国是世界上锑的主要生产国和出口国,因而对锑污染的研究不容     

关于原子吸收分光光度计吸光度自吸的探讨

通过笔者多年对原子吸收分光光度计仪器的使用,发现在测量金、银、铜、铅等多种元素时,其吸光度值在超过一定值后,吸光度和测量溶度就不完全符合A=KC。A=-lgI/I0=-lgT=KC是原子吸收仪器计算吸光度和溶度的基本公式,本实验就是研究在不同实验条件下得出不同的吸光度是否均符合此公式。     

基于Curvelet变换冗余字典的重力数据稀疏表示与重建

压缩感知理论为低采样建立大面积、高精度的重力场模型提供了理论指导。构造合适的变换基,实现二维重力数据更为稀疏的表示,对于测量矩阵的设计和重构精度的提高具有重大意义。采用Curvelet变换作为核函数构造过完备冗余字典,选取不同尺度不同方向的曲波系数作为原子组成不同的字典,对EGM2008模型分辨率为1′×1′的某海域重力异常数据进行稀疏表示和重建,根据PSNR值,稀疏度和η值作为评估标准确定最优原子个数。最后采用OMP算法对重力数据稀疏表示并重建。     

第三讲 铜的地球化学性质、含量和共生元素

(一)铜的地球化学性质铜是亲硫元素的典型代表,四周期最后一个过渡金属元素,属I_B族.与四周期I_A族元素钾相比,其特征和外电子层、原子半径、第一电离势之区别,见表1.铜的原子结构复杂,外电子层多五个3d轨道、十个电子.因之,核与外层电子联系力较强,原子半径较小,价电子的电离势高,不易失去,成离子键的倾向小.自然界铜与氧的亲和力弱,铜的氧化物较不稳定,只在强氧化环境才形成.因此自然界赤铜矿(Cu_2O)、黑铜矿(CuO)分布不广.而     

用作半導体及光电效应的稀有元素

半導体是介于導电体与絕緣体之間的物質。半導体原子中能帶的分布与絕緣体相似,所不同的就是原子的能带中禁帶的間隙距离,经絕緣体中的禁帶狹窄而已。半導体在相当溫度或电場的作用下,原子內滿带(裝滿电子的帶)中的电子就能被激發而跳过禁帶的范圍,跑到容帶中去,或跑到雜質能帶中,或者电子由雜質能帶跑進容帶中去,因而能導电。倘溫度愈高,則电子跳过禁帶的机会也愈多,導电性也就愈大。由于半導体有这种物理性能,因而能用作整流器。整流就是把交流电变为直流电。半導体除了整流作用     

矿物中水的分子折射度和分子体积

矿物中的水分为结晶水,结构水(氢氧根)、层间水、沸石水和吸附水等几种结构状态。不同结构状态的水对矿物的性质应有不同的影响。但是著名矿物学家拉尔森^[1](E.S.Larsen)给定矿物中水的比折射度k值(又称格拉斯顿-代尔常数),不论是对何种结构状态的水都适用。曾经有许多人对这一点产生过疑义,最近曼达利诺^[2](J.A.Mandarino)修正k值时,对各种结构状态的水仍是同用一值。矿物中各种水的折射度是否变化呢?本文作者将列举大量数据来说明这一问题。     

高应力条件下的岩芯电磁性能变化

根据标准晶格模型理论,在高应力作用下,岩石的Si-O键最外层电子将被挤入晶格间隙里,松散外逸的电子云在电场中将产生直流电流（DC）,进而吸收电磁波,转换成交流电流（AC）。直流电流来源于量子力学穿隧效应电子和断键电子。穿隧效应电子的形成过程和原理:氧原子的最外电子被束缚在浅位能井（shallow potential well）（0.38 V）,当高应力作用时,电子吸收部分能量,增加其动能,虽然这种轻微的动能增加不足以使电子克服并跳出它的位能井（potential well）,但它足以增加穿过井壁（well wall）进入晶格空隙间的概率,这个概率乘以可用氧原子的数目即为由于隧穿效应形成电子云的电子数量,其量级通常为微微库伦（picocoulombs）到纳米库伦（nanocoulombs）。断键电子的形成过程和原理:从微裂纹开始断裂键释放电子,并且裂纹成核点极可能开始是平行排列的,每当Si-O键断裂时,就会产生一个+Si悬键,伴随着一个自由电子附着在-O原子上,这个电子将从原子跃迁到原子,这种电子电流与裂纹的表面积和电池电极的收集效率成正比。断键形成的电子云比穿隧效应多很多。两种电子均被试验所证实。在高应力条件下岩石破裂之前,由电子穿隧效应,DC缓慢增加,随着岩石破裂的发生而导致断键电子增多,DC急剧增加;AC的电压振幅（V）随电流（I）增大而减小,当电流减小到正常时,在岩石破裂后电压振幅回归正常;遵守能量守恒原理,吸收的电磁波能量（E）与交流电流功率（V×I）相等,即E=V×I。研究结果表明电磁波监测可用于探测地壳高应力变化和岩石破裂特征,当应力达到岩体断裂的临界强度时,其应变晶体结构开始释放越来越多的外逸电子,最终岩体晶体结构断裂产生一个地震或滑动事件。岩石破裂的电磁性能变化研究可用于研发电磁波地学监测仪器,电磁波监测可以作为地应力监测的一种补充和对比分析方法,两种方法相结合比地应力监测一种方法更可靠。此外,在高应力条件下岩石还有其它现象:应变蠕变辐射、光发射、声发射、静电等,这些现象的观测也是预测地质事件需要考虑的条件。      

集对分析径向基函数神经网络预测模型

将集对分析与径向基函数神经网络结合,提出了集对分析径向基函数神经网络预测模型。模型思路是将研究对象t-1时和t时的影响因子集构造为集对并计算联系度,由联系度的同一度、差异度、对立度及研究对象t-1时的值为输入,研究对象t时的值为输出,构建径向基函数神经网络。以年径流预测为例研究表明,模型结构清晰、步骤明确、预测精度较高,为集对分析应用于水文预测提供了新思路。     

一种提取声波测井频散波相慢度的适应函数方法

提出了一种对声波测井频散波数据频散校正的适应函数方法。通过提取频散波的频率慢度相关图,得到频散波的频散曲线,由频散曲线在慢度轴上的投影可得到关于地层波慢度的统计直方图。构造一种适应函数与直方图进行非线性最小二乘拟合,得到与统计直方图最优匹配的适应函数,这个适应函数起始点对应的慢度即为真实的地层波慢度。给出了采用该方法处理理论模拟的偶极子波及现场实测的偶极子波资料的例子。对理论模拟的偶极子波处理,计算的偶极子波慢度值与地层真实横波慢度基本一致;对现场实测的偶极子波数据处理,计算的偶极子波慢度与频率慢度投影曲线相匹配。处理结果表明,采用该方法对频散波进行频散校正是可靠有效的。     

铜陵冬瓜山铜矿床的品位分形结构特征及其地质意义

文章以冬瓜山铜矿床为研究对象,应用分形理论对矿床品位的分形结构特征进行研究,计算了主矿体整体和不同区段的品位分布的分维数D值,D值变化反映矿体在50～52线之间变化最不均匀,为确定勘探网度和矿床经济价值评估提供有益的参考.     

A quantum-chemical model of calculating the bond energy of crystals

A model has been obtained from a strict expression of crystal energy by introducing S and valence approximations. The Mulliken approximation has been used for double-centered exchange and three-center integrals. The calculations have been carried out for Slater type atomic orbitals, varying the screening parameters. The bond energy has been represented as a sum of the energy for forming partial differential electronic densities, E _A, the interatomic interaction energy E _IA, and the correlation energy of atomic states in the crystal, E _S . The computed bond energies for four oxides of alkaline-earth metals and six oxides of transition (iron group) metals are in good agreement with experimental data.     

On the Ratios between Elastic Modulus and Uniaxial Compressive Strength of Heterogeneous Carbonate Rocks

The ratios M _R = E/σ _c for 11 heterogeneous carbonate (dolomites, limestones and chalks) rock formations collected from different regions of Israel were examined. Sixty-eight uniaxial compressive tests were conducted on weak-to-strong (5 MPa < σ _c < 100 MPa) and very strong (σ _c > 100 MPa) rock samples exhibiting wide ranges of elastic modulus (E = 6100–82300 MPa), uniaxial compressive strength (σ _c = 14–273.9 MPa), Poisson's ratio (ν = 0.13–0.49), and dry bulk density (ρ = 1.7–2.7 g/cm³). The observed range of M _R = 60.9–1011.4 and mean value of M _R = 380.5 are compared with the results obtained by Deere (Rock mechanics in engineering practice, Wiley, London, pp 1–20, 1968) for limestones and dolomites, and the statistical analysis of M _R distribution is performed. Mutual relations between E, σ _c, ρ, M _R for all studied rocks, and separately for concrete rock formations are revealed. Linear multiple correlations between E on the one hand and σ _c and ρ on the other for Nekorot and Bina limestone and Aminadav dolomite are obtained. It is established that the elastic modulus and M _R in very strong carbonate samples are more correlated with ρ−σ _c combination and ε _a max, respectively, than in weak to strong samples. The relation between M _R and maximum axial strain (ε _a max) for all studied rock samples (weak-to-strong and very strong) is discussed.     

Computation of surface energies in an electrostatic point charge model: II. Application to zircon (ZrSiO4)

The attachment energies, the slice energies and the specific surface energies can be calculated in an electrostatic point charge model using the formula derived by Madelung for the potential introduced by an infinite row of equally spaced point charges. Power series are given for the Hankel function iH ₍₀₎ ⁽¹⁾ (iy) and (x)=d ln x!/dx. The logarithmic expression in the Madelung formula converges rapidly when applying a power series, which combines equally charged cations and anions. Besides the specific surface energy ( ^hkl), the slice energy (E _s ^hkl ) and the attachment energy (E _a ^hkl ) can be considered as special categories of surface energies as they depend on surface configurations as well. The specific surface energy is the energy per unit area of surface needed to split the crystal parallel to a face (hkl). The attachment energy (E _a) is the energy released per mole, when a new slice of thickness d _hkl crystallizes on an already existing crystal face (hkl). The growth rate of the crystal face (hkl) is a function of its attachment energy. The slice energy (E _s) is the energy released per mole, when a new slice d _hkl is formed from the vapour neglecting the influence of edge energies. The lattice energy (E _c) which is the energy released per mole of a crystal crystallizing from the vapour, is given by the following relation: E _c=E _a+E _s.     

On the relationship between refractive index and density for SiO2 polymorphs

The Gladstone-Dale law (specific refraction) and the Drude law (molecular refraction) for silica polymorphs, at “sodium light” (λ _D =0.5893 μm), are derived from simple atomic properties of SiO₂ complex (atomic weight, first ionization potential). The considerations are based on the Lorentz electron theory of solids. The characteristic frequency (or eigenfrequency) v ₀ of elementary electron oscillators (in energy units, hv) is identified with the band gap E _G of a solid; on the other hand, this E _G -gap is identified with the single ionization potential \(\tilde U\) of non-free atoms. For \(\tilde U\) =E _G =10.2 eV (energy gap of quartz, see Nitsan and Shankland 1976b) the Gladstone-Dale law, or specific refraction, is (n?1)/ρ=0.208 cm³/g, where n and ρ are the refractive index and the density of medium, respectively. According to empirical data, the average value of the specific refraction of pure SiO₂ polymorphs (except stishovite-high density phase of silica) is (〈n〉?1)/ρ=0.207±0.001 (〈n〉 denotes the mean refractive index of crystal). For stishovite the Drude law (n ²?1)/ρ=0.542 cm³/g is valid under an assumption that the first ionization potential \(\tilde U\) =E _G ≈9 eV; this result is good agreement with the empirical value (〈n〉²?1)/ρ=0.536 cm³/g.     

Utilization of Gaussian Process Regression for Determination of Soil Electrical Resistivity

Soil electrical resistivity (R_E) is an important parameter for geotechnical engineering projects. This article employs Gaussian process regression (GPR) for prediction of R_E of soil based on soil thermal resistivity (R_T), percentage sum of the gravel and sand size fractions (F), and degree of saturation (S_r). GPR is derived from the perspective of Bayesian nonparametric regression. Two models (Model I and Model II) have been developed. The developed GPR has been compared with the artificial neural network. It gives the variance of the predicted R_E. The results show the developed GPR is an efficient tool for prediction of R_E of soil.     

Kuranakhite discovered in China for the first time

Kuranakhite was firstly discovered in the oxidized zone of the Kuranakh gold mine, southern Russia, and since then there has been no report on it. Kuranakhite in this paper was discovered in the Jialu gold mine, Luonan County, Shaanxi Province. The mineral often occurs as irregular granular aggregates varying from 0. 05 to 0. 25 mm in size. The mineral is light brown to brown in color, translucent, brown in steak, and vitreous in luster. Hv is 231 – 439kg/mm², H_M = 4∼5 and measured density is 6.72(2)g/cm³. Its reflection color is bluishgray to light-blue and it shows middle anisotropism and weak bireflectance. Its polarization color is blue to grayish-brown and there is no internal reflection. The index of refraction is:N _a = 2.01,N _β = 1. 98,N _γ = 1. 96. The average composition is PbO 45. 40 wt %, MnO₂ 16.41wt%, TeO₃ 38.10wt%, totalling 99. 91wt%. The empirical formula is Pb_0.99Mn_0.92 Te_1.06O₆, which can be simplified as PbMnTeO₆. Principal lines in the X-ray power pattern [d(I)(hkl)] are:0.341 (100), (111); 0.2556(60), (130); 0.2043 (50), (041);0.1666 (20), (310); 0.1598(40), (241); and 0.1472(15), (330). It was determined that kuranakhite is orthorhombic; its space group may be C;a = 0.511(1) nm,b = 0.891(2)nm,c = 0.532(l)nm, a:b = 0.57, c:b = 0.60;V = 0.242 (3) nm³;Z = 2, and calculated density = 6.66(1) g/ cm³. This project was financially supported by both the Armed Police Headquarters of Gold Exploration and the Science Foundation of Shaanxi Provincial Educational Commission (No.HJ96-2-4;96JK-026).     

Fe-Li云母化学成分的解释和分类

用置换矢量概念解释了115个天然 Fe-Li 云母化学成分的变化。Fe-Li 云母是三八面体 Li-Fe-Al 云母,其基本置换是四锂云母置换。由于 Al-Li 白云母置换和白云母置换的影响,其化学组成变化的基本趋势呈明显的非线性,因而 Fe-Li 云母不是真正的二元系。作为 Fe-Li 云母,富铁黑云母和铁叶云母都是最富铁的成员,因而建议称 Fe-Li 云母为黑云母-锂云母系列。根据化学成分,晶胞参数和折光率的异常变化还提出了该系列自然分类的方案。     

Estimating the number of casualties in earthquakes from early field reports and improving the estimate with time

We investigate the time dependence of the number of deaths reported through Internet after earthquakes and/or earthquake-generated tsunami. An approximate relation N(t) = N ₀ [1 − exp(−αt)] is used to describe such temporal variation, in which N(t) is the number of deaths reported at time t, N ₀ is the final number of deaths, and α is the coefficient reflecting the rescue process. We considered 12 earthquake cases since 2001 using the information from the web, which shows that the N-t relation approximates the data, and the logarithm of α is reversely proportional to the magnitude of earthquake, albeit with significant uncertainties. Quick and rough estimate of the final death toll can be made using this simple and approximate relation, with the empirical α-M relation as a reference. For the 12 cases under consideration, quick and rough estimate of fatalities can be obtained 2 days after the earthquake, fitting the real situation in the order of magnitudes. Although being very rough, this estimate can assist the emergency decision-making and can be revised as time lapses. When more and more data becomes available, curve fitting can provide both N ₀ and α at the same time. The method is tested against the data of the recent Yushu earthquake on April 14, 2010.     

Relationship of drought frequency and severity with range of annual temperature variation

The frequency and severity of occurrence of meteorological droughts in different climatic regions depend on regional climatic factors. This study has made an effort to explore the relationship of range of annual temperature variation at a given place with the frequency of occurrence of drought and the maximum magnitude of seasonal rainfall deficit (i.e., severity). The seasonal rainfall refers to sum of monsoon season (rainy season) rainfall in India. The monthly precipitation data of 113 years (1901–2013) for 256 stations in different parts of India have been used to estimate the return period of meteorological drought at different stations. The daily normal values of observed maximum and minimum temperatures from 40 years of records have been utilized to estimate range of temperature variation (θ_R) during the year at each stations. In various parts of India, the θ_R ranges from 10 °C in humid regions to 40 °C in arid regions. The various climatic regions have been experiencing maximum deficiency of annual rainfall ranging from 30% (humid) to 90% (arid). The results reveal that places exhibiting θ_R values between 40 to 30 °C face more frequent droughts with average frequency of once in 3 to once in 6 years. The occurrence of extreme and severe drought events is more frequent in the regions with higher values of θ_R compare to that in lesser values of θ_R. The regions with θ_R values between 30 to 25 °C mostly face severe and moderate events having the average drought return period of 6–9 years, and the occurrence of extreme droughts in these regions is rare. Furthermore, regions with θ_R?<?20 °C face moderate droughts only with an average return period of 14 years. This study divulges that the average return period and magnitude of deficiency of drought events have notable relationship with the range of temperature variation during the year at a given place.

     

Uncertainties in downscaled relative humidity for a semi-arid region in India

Monthly scenarios of relative humidity (R _H) were obtained for the Malaprabha river basin in India using a statistical downscaling technique. Large-scale atmospheric variables (air temperature and specific humidity at 925 mb, surface air temperature and latent heat flux) were chosen as predictors. The predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis dataset for the period 1978–2000, and (2) simulations of the third generation Canadian Coupled Global Climate Model for the period 1978–2100. The objective of this study was to investigate the uncertainties in regional scenarios developed for R _H due to the choice of emission scenarios (A1B, A2, B1 and COMMIT) and the predictors selected. Multi-linear regression with stepwise screening is the downscaling technique used in this study. To study the uncertainty in the regional scenarios of R _H, due to the selected predictors, eight sets of predictors were chosen and a downscaling model was developed for each set. Performance of the downscaling models in the baseline period (1978–2000) was studied using three measures (1) Nash–Sutcliffe error estimate (E _f), (2) mean absolute error (MAE), and (3) product moment correlation (P). Results show that the performances vary between 0.59 and 0.68, 0.42 and 0.50 and 0.77 and 0.82 for E _f, MAE and P. Cumulative distribution functions were prepared from the regional scenarios of R _H developed for combinations of predictors and emission scenarios. Results show a variation of 1 to 6% R _H in the scenarios developed for combination of predictor sets for baseline period. For a future period (2001–2100), a variation of 6 to 15% R _H was observed for the combination of emission scenarios and predictors. The variation was highest for A2 scenario and least for COMMIT and B1 scenario.