Correlation between aggregation structure and tailing mineral crystallinity

Direct reduction is an emerging technology for the utilization of refractory iron ore. With this technology, iron oxides in the ore can be reduced to recoverable elemental iron. The structure of granular aggregates in direct reduction products was investigated by X-ray diffraction （XRD）. The results show that iron is mainly generated as a shell in the outer edge of the aggregates. The thermal conductivity of the iron shell is higher than that of other minerals. Thus, minerals close to the iron shell cool faster than those in the inner shells and do not crystallize well. These minerals mainly become stage 2 tailings. Hence the XRD intensity of stage 2 tailings is lower than that of stage 1 tailhags. When iron is mainly generated in the interior of the aggregates, the crystallinity of stage 2 tailings will be higher than that of stage 1 tailings. This indicates that the crystallinity of tailings can be used as a marker for the aggregate structure.

Recovery of iron and copper from copper tailings by coal-based direct reduction and magnetic separation

A technique comprising coal-based direct reduction followed by magnetic separation was presented to recover iron and copper from copper slag flotation tailings.Optimal process parameters,such as reductant and additive ratios,reduction temperature,and reduction time,were experimentally determined and found to be as follows：a limestone ratio of 25%,a bitumite ratio of 30%,and reduction roasting at 1473 Kfor 90 min.Under these conditions,copper-bearing iron powders（CIP）with an iron content of 90.11% and copper content of 0.86%,indicating iron and copper recoveries of87.25% and 83.44%respectively,were effectively obtained.Scanning electron microscopy and energy dispersive spectroscopy of the CIP revealed that some tiny copper particles were embedded in metal iron and some copper formed alloy with iron,which was difficult to achieve the separation of these two metals.Thus,the copper went into magnetic products by magnetic separation.Adding copper into the steel can produce weathering steel.Therefore,the CIP can be used as an inexpensive raw material for weathering steel.

Characteristics of Mercury Intoxication Induced by Skin-lightening Products

Mercury is usually added to skin-lightening products due to its whitening effect.The Food and Drug Administration （FDA） limits the amount of mercury in cosmetics to trace amounts under 1 ppm.Nevertheless,many cosmetics contain mercury above 1000 ppm to increase the whitening effect.In a group of special patients in the study,pain,renal damage,and neuropsychiatric symptoms were the cardinal symptoms observed.

Morphology Evolution of Polystyrene-core/Poly(N-isopropylacrylamide)-shell Microgel Synthesized by One-pot Polymerization

One-pot polymerization with macroinitiator is supposed to be a robust, facile way to synthesize well-defined core- shell nanoparticles with fixed shell thickness. To testify this, we investigated the temperature-depending morphology evolution of polystyrene （PS） core/poly（N-isopropylacrylamide） （PNIPAM） shell microgel synthesized by one-pot polymerization with PNIPAM-RAFT as macroinitiator in dimethylformamide （DMF） by transmission electron microscopy （TEM）, dynamic/static light scattering （DLS/SLS） and small angle neutron scattering （SANS）. It is revealed that the microgel has a core-shell structure, i.e., the core is made of pure PS, but the shell is composed of both PNIPAM-RAFT macroinitiator and crosslinked PS. In fact, there are 92.0 wt% D20, 6.7 wt% PNIPAM and 1.3 wt% PS in the shell in its aqueous dispersion at 21 ℃; therefore, its shell thickness is much larger than the extended chain length of the macroinitiator as revealed by both SANS and DLS observations. Competitive growth of styrene, divinylbenzene and PNIPAM macroinitiator as well as possible chain transfer from amine proton of PNIPAM side chain may lead to the larger shell thickness, compared with the extended chain length of the macroinitiator. Our work can shed light on the real morphology control in one-pot polymerization.

Complex integrity constraint discovery: measuring trust in modern intelligent railroad systems

1Introduction Data are at the heart of intelligent rail systems in the high-speed transportation sector(Zhou et al.,2020;Ho et al.,2021;Hu et al.,2021;Chen et al.,2022).The core of modern intelligent railroad systems typically includes rail transportation and equipment monitoring models learned from large datasets,which are often optimized for specific data and workloads(Zhu et al.,2019;Tan et al.,2020).While these intelligent railroad systems have been widely adopted and successful,their reliability and proper function will change as the data used changes.If the data used(on which the system operates)deviates from the fundamental constraints of the initial data(on which the system is trained)then,in that case,the system performance degrades,and the results inferred by the system model become unreliable,so the system model must be retrained and redeployed to re-store reliable inference results(Sharma and Chandel,2013).The mechanism for assessing the trustworthiness of intelligent rail system inferences is of paramount importance,especially for rail systems performing safety-critical or high-impact operations.