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Abstract The present work is focused on the effect of substitution of Co2+ and Cu2+ ions on the structural, morphological, magnetic and optical properties of nanocrystalline ternary doped ferrite nanoparticles (NPs) having formula Mn 0.4 Co 0.6-x Cu x Fe 2 O 4 (x = 0, 0.2, 0.4, 0.6). They were synthesized using sol-gel precursor methodology and then sintered at 300 °C for 3 h and characterized by XRD, FT-IR, 57Fe Mössbauer and magnetometry. Alteration in surface morphology and surface area was studied using SEM-EDX, TEM and BET analyses. XRD patterns confirmed the formation of single phase ferrite NPs. Doping of Cu2+ ions in MnFe 2 O 4 NPs led to slight increase in magnetization, whereas doping with Co2+ ions appreciably increased the magnetization. The results were correlated to magnetic moment of cations. Maximum saturation magnetization value was 65.0 emu/g for ternary ferrite NPs having formula Mn 0.4 Co 0.4 Cu 0.2 Fe 2 O 4. Doping of MnFe 2 O 4 with Co2+ and Cu2+ ions enhanced surface area. The change in Mössbauer parameters suggested the alteration in environment of Fe3+ ions in presence of different divalent ions. Optical studies revealed lowering in band gap up to 2.03 eV on doping and minimum band gap was observed in Mn 0.4 Co 0.4 Cu 0.2 Fe 2 O 4 NPs. The results confirmed the improved magnetic and optical properties of ternary doped ferrite NPs as compared to pristine counterparts. Graphical abstract Image 1 [ABSTRACT FROM AUTHOR]

The Reduced Life Expectancy (RLE) Model (LC 50 = [ln(NLE) – ln(LT 50 )]/d) has been proposed as an alternative to Haber's Rule. The model is based on a linear relationship between LC 50 (Lethal Exposure Concentration) and lnLT 50 (Lethal Exposure Time) and uses NLE (Normal Life Expectancy) as a limiting point as well as a long term data point (where d is a constant). The purposes of this paper were to compare the RLE Model with Haber's Rule with available toxicity data and to evaluate the strengths and weaknesses of each approach. When LT 50 is relatively short and LC 50 is high, Haber's Rule is consistent with the RLE model. But the difference between the two was evident in the situation when LT 50 is relatively long and LC 50 is low where the RLE model is a marked departure from Haber's Rule. The RLE Model can be used to appropriately evaluate long term effects of exposure. [ABSTRACT FROM AUTHOR]

The relationship between exposure time (LT50) and lethal exposure concentration (LC50) has been evaluated over relatively long exposure times using a novel parameter, Normal Life Expectancy (NLT), as a long term toxicity point. The model equation, ln(LT50) = aLC50 ν + b, where a, b and ν are constants, was evaluated by plotting lnLT50 against LC50 using available toxicity data based on inhalation exposure from 7 species of mammals. With each specific toxicant a single consistent relationship was observed for all mammals with ν always <1. Use of NLT as a long term toxicity point provided a valuable limiting point for long exposure times. With organic compounds, the Kow can be used to calculate the model constants a and v where these are unknown. The model can be used to characterise toxicity to specific mammals and then be extended to estimate toxicity at any exposure time with other mammals. [Copyright &y& Elsevier]

Abstract: Traditionally in toxicological studies time is not studied as quantifiable variable but as a fixed endpoint. The Reduced Life Expectancy (RLE) model which relates exposure time and exposure concentration with lethal toxic effects was tested previously using fish data. In this current paper the effects of exposure time on aquatic toxicity with zooplanktons and various toxicants were evaluated using the RLE model based on ambient exposure concentration. The model was evaluated by plotting ln LT 50 against LC 50 using toxicity data with zooplanktons from the literature for metal, metalloid and organic compounds. Most of the experimental data sets can be satisfactorily correlated by use of the RLE model, but deviations occurred for some data sets. Those data sets were satisfactorily fitted by a two stage RLE model. This model was based on two phases: one in the peripheral system and other in the central system. Both the single and two stage RLE model support the hypothesis that toxicity is time dependent and decreases in a systematic way with increasing exposure time. A calculated normal life expectancy (NLT) can be obtained from the single stage model and is in accord with reported NLT but those obtained from the two stage RLE model are in excellent agreement. [Copyright &y& Elsevier]

Data on toxicity of chemicals is usually reported as the LD 50 , or LC 50 , with the exposure time from experimental testing in the laboratory reported. But the exposure time is not considered to be a quantifiable variable which can be used to evaluate its importance in expressed toxicity, often described in general terms such as acute, chronic and so on. For the last hundred years Habers Rule has been successfully used to extrapolate from reported exposure times to other exposure times which may be needed for setting standards, health risk assessments and other applications. But it has limitations particularly in environmental applications where exposure levels are low and exposure times are relatively long. The Reduced Life Expectancy (RLE) model overcomes these problems and can be utilised under all exposure conditions. It can be expressed as ln(LT50) = −a (LC50) ν + b where the constants ν , a and b can be evaluated by fitting the model to experimental data on the LC 50 , and corresponding LT 50 , together with the Normal Life Expectancy (NLE) of the organism being considered as a data point when the LC 50 is zero. The constant, ν , at a value of unity gives a linear relationship and where ν < 1 the relationship has a concave shape. In our extensive evaluations of the RLE model for fish, invertebrates and mammals involving 115 data sets and with a wide range of organic and inorganic toxicants the RLE model gave correlation coefficients of >0.8 with 107 sets of data. The RLE model can be used to extrapolate from a limited data set on exposure times and corresponding LT 50 values to any exposure time and corresponding LT 50 value. The discrepancy between Haber’s Rule and RLE model increases as the exposure time increases. [ABSTRACT FROM AUTHOR]