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The variant rock types of an Alkaline–Carbonatite Complex (ACC) comprising alkali pyroxenite, nepheline syenite, phoscorite, carbonatite, syenitic fenite and glimmerite along with REE and Nb–mineralization are found at different centres along WNW-ESE trending South Purulia Shear Zone (SPSZ) in parts of Singhbhum Crustal Province. The ACC occurs as intrusions within the Mesoproterozoic Singhbhum Group of rocks. Alkali pyroxenite comprises of aegirine augite, magnesiotaramite, magnesiokatophorite as major constituents. Pyrochlore and eucolite are ubiquitous in nepheline syenite. Phoscorite contains fluorapatite, dahllite, collophane, magnetite, hematite, goethite, phlogopite, calcite, sphene, monazite, pyrochlore, chlorite and quartz. Coarse fluorapatite shows overgrowth of secondary apatite (dahllite). Secondary apatite is derived from primary fluorapatite by solution and reprecipitation. The primary fluorapatite released REE to crystallize monazite grains girdling around primary apatite. Carbonatite is composed dominantly of Srcalcite along with dolomite, tetraferriphlogopite, phlogopitic biotite, aegirine augite, richterite, fluorapatite, altered magnetite, sphene and monazite. The minerals comprising of the carbonatite indicate middle stage of carbonatite development. Fenite is mineralogically syenite. Glimmerite contains 50–60% tetraferriphlogopite. An alkali trend in the evolution of amphiboles (magnesiotaramite–magnesiokatophorite–richterite) and chinopyroxenes (aegirine augite, aegirine) during the crystallization of the suite of rocks is noted. Monazite is the source of REE in phoscorite and carbonatite. Fluorapatite has low contents of REE, PbO, ThO2 and UO2. Pyrochlore reflects Nb-mineralization in nepheline syenite and it is enriched in Na2O, CaO, TiO2, PbO and UO2. Pyrochlore containing UO2 (6.605%) and PbO (0.914%) in nepheline syenite has been chemically dated at 948 ± 24 Ma by EPMA.

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Majority-inverter graphs (MIGs) are a logic representation with remarkable algebraic and Boolean properties that enable efficient logic optimizations beyond the capabilities of traditional logic representations. Further, since many nano-emerging technologies, such as quantum-dot cellular automata (QCA) or spin torque majority gates (STMG), are inherently majority-based, MIGs serve as a natural logic representation to map into these technologies. So far, MIG optimization methods predominantly target to reduce the depth of the logic networks, corresponding to low delay implementations in the respective technologies. In this paper, we introduce several methods to optimize the size of MIGs. They can be applied such that the depth of the logic network is preserved; therefore our methods have a direct effect on the physical area, without worsening the delay. Some methods are inspired by existing size optimization algorithms for non-majority-based logic networks, others make explicit use of the majority function and its properties. All methods are Boolean-in contrast to algebraic optimization methods-which has a positive effect on the quality but challenges their implementation. Our experiments show that using our methods the size of MIGs in the EPFL combinational benchmark suite can be reduced by up to 7.12%. When mapped to QCA and STMG technologies we reduce the average area-delay-energy product by 2.31% and 2.07%, respectively.