Electrolytic refining of lead in molten chloride electrolytes

Three types of antimony and bismuth electrolytic cells to be used for lead electrorefining were developed and tested. The electrolytic cell with the bipolar metallic electrode, the electrolytic cell with two anodes and one cathode, and the electrolytic cell with the porous diaphragm were studied. The tests demonstrated that lead is effectively separated from the metallic impurities in all constructions. Grade lead may be obtained at the cathode, and lead-antimony and lead-bismuth alloys may be produced at the anode. The electrolytic cell with a porous diaphragm was found to double the production rate and greatly decrease the electrical potential of the cell as compared to the other two constructions. © IJTech 2017

Theoretical modeling of electrochemical nucleation and growth of a single metal nanocluster on a nanoelectrode

Theory of the initial stages of electrochemical formation and growth of a single metal nanocluster on an indifferent nanoelectrode has been developed and analyzed. General theoretical time dependences of the current and nanocluster size have been presented for the case of diffusion controlled growth at potentio- A nd galvanostatic deposition, and cyclic voltammetry. © 2020 The Royal Society of Chemistry

Сopper powders formation in the cathodic and anodic half-periods with industrial alternating current

For the first time, an installation was created for producing copper powders in the anodic and cathodic half-periods of industrial alternating current with a frequency of 50 Hz. This device consists of two electrolytic cells interconnected in parallel, in each electrolyzer there are two copper electrodes. Two diodes are also included in the electrochemical circuit to allow current flowing in opposite directions. The influence of electrodes current density, sulfuric acid concentration, copper ions, on current output of copper powder formation in each cell was investigated. It was established that the current output increases within the current density from 2000-8000 A/m2 and decreases with further increase of this parameter. When sulfuric acid concentration was 100 g/l and copper ions concentration was 15 g/l, the maximum current output of powder in electrolyzes was 50.1-53.3%, and the total current output exceeded 100%. Using a JSM-661 LV scanning electron microscope, the shape and size of obtained powders were investigated. On the basis of the conducted studies and captured oscillograms, the mechanism for copper powders formation in the anodic and cathodic half-cycles of alternating current was established. For the first time it was shown that the proposed installation allows to obtain copper powders in two half periods of alternating current. It was established that at the same time ultrafine metal powders with particle sizes of 1.0-1.5 microns had been formed. © National Academy of Sciences of the Republic of Kazakhstan, 2019

Peculiarities of some mafic-ultramafic- and ultramafic-hosted massive sulfide deposits fom the Main Uralian Fault Zone, southern Urals

Some Cu-rich, mafic-ultramafic- and ultramafic-hosted massive sulfide deposits from the southern segment of the Main Uralian Fault Zone (Ivanovka and Ishkinino deposits, southern Urals) show unusual characteristics. Their major features include: (i) relatively high Co (Ni, An), very low Zn and negligible Pb grades; (ii) a pyrrhotite-dominated mineralization, locally characterized by the presence of open- latticework aggregates of lamellar pyrrhotite with Mg-saponite Mg-chlorite and carbonate matrix; (iii) hydrothermal alteration of ultramafic host rocks into talc carbonate quartz chlorite and of mafic host rocks into chloritites; (iv) the presence of clastic facies with reworked sulfide and ultramafic or mafic components; (v) the widespread occurrence of sulfide-associated chromite; (vi) the specific mineralogy of Co, Ni, Fe and As, including sulfoarsenides, mono- and diarsenides, and Co-rich pentlandite and pyrite; (vii) the supra-subduction -zone geochemical signature of the host serpentinites and volcanic rocks. Although some of these features have been separately reported in certain modem ocean-seafloor and ophiolite-hosted fossil deposits, a true equivalent has yet to be found. Based on recognized partial analogies with a few modem seafloor examples, the arc tholeiitic-boninitic geochemical signature of sulfide-associated volcanic rocks and the highly refractory compositions of sulfide-hosted chromite relicts, the studied deposits are believed to have formed by seafloor-subseafloor hydrothermal processes in an oceanic island arc setting. Possible tectonostratigraphic correlation of sulfide-associated units with infant, non-accretionary arc volcanic units of the adjacent Magnitogorsk oceanic island-arc system suggests formation of the studied deposits during the earliest stages of Devonian subduction-related volcanism

Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge

This competition concerns educational diagnostic questions, which are pedagogically effective, multiple-choice questions (MCQs) whose distractors embody misconceptions. With a large and ever-increasing number of such questions, it becomes overwhelming for teachers to know which questions are the best ones to use for their students. We thus seek to answer the following question: how can we use data on hundreds of millions of answers to MCQs to drive automatic personalized learning in large-scale learning scenarios where manual personalization is infeasible? Success in using MCQ data at scale helps build more intelligent, personalized learning platforms that ultimately improve the quality of education en masse. To this end, we introduce a new, large-scale, real-world dataset and formulate 4 data mining tasks on MCQs that mimic real learning scenarios and target various aspects of the above question in a competition setting at NeurIPS 2020. We report on our NeurIPS competition in which nearly 400 teams submitted approximately 4000 submissions, with encouragingly diverse and effective approaches to each of our tasks

Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge

This competition concerns educational diagnostic questions, which are pedagogically effective, multiple-choice questions (MCQs) whose distractors embody misconceptions. With a large and ever-increasing number of such questions, it becomes overwhelming for teachers to know which questions are the best ones to use for their students. We thus seek to answer the following question: how can we use data on hundreds of millions of answers to MCQs to drive automatic personalized learning in large-scale learning scenarios where manual personalization is infeasible? Success in using MCQ data at scale helps build more intelligent, personalized learning platforms that ultimately improve the quality of education en masse. To this end, we introduce a new, large-scale, real-world dataset and formulate 4 data mining tasks on MCQs that mimic real learning scenarios and target various aspects of the above question in a competition setting at NeurIPS 2020. We report on our NeurIPS competition in which nearly 400 teams submitted approximately 4000 submissions, with encouragingly diverse and effective approaches to each of our tasks