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The vast seabed holds tremendous resource potential that can provide necessary materials for future human societal development. This study focuses on the mineralogy of seafloor manganese nodules off the coast of China in the Western Pacific and the primary techniques for extracting valuable metal elements from manganese nodules. The research indicates that the main valuable metal elements in the manganese nodules from this region include Cu, Co, Ni, Mn, Fe, etc. The key to extracting these valuable metals lies in reducing Mn(IV) to Mn(II) to disrupt the structure of the nodules, thereby releasing the valuable elements. The extraction processes for the main valuable metal elements of manganese nodules are mainly divided into two categories: pyrometallurgical–hydrometallurgical and solely hydrometallurgical. In order to cope with the challenges of environmental change and improve utilization efficiency, bioleaching, hydrogen metallurgy, and co-extraction are gaining increasing attention. For promoting commercialization, the future development of manganese nodule resources can refer to the technical route of efficient short-process extraction technology, the comprehensive recovery of associated resources, and tail-free utilization.

Design of a pick-up device using the Coandă effect in a deep-sea mining robot is vital to develop a reliable and sustainable deep-sea mining system. One of the crucial performance metrics of this device is the collection efficiency since it affects the mining efficiency of the entire system. However, the collection efficiency is significantly affected by the uncertainties of shape, size and mass of manganese nodules on the seabed. In this study, reliability-based design optimization (RBDO) was performed to improve the reliability of the collection efficiency of the pick-up device under these environmental uncertainties. First, a computational model based on the Coandă effect that predicts the collection efficiency of the pick-up device was developed. Next, RBDO based on the Akaike information criterion method was employed to design the pick-up device by using this model. The results demonstrated that the proposed design methodology significantly improved the design of the pick-up device for the pilot mining robot.

The objective of this study is to identify the feasibility of using rhamnolipid biosurfactant to remediate heavy metals contained in manganese nodules collected from the Clarion-Clipperton Fracture Zone, Pacific Ocean. Deep-sea manganese nodules may represent one of the most important future natural resources for heavy metals due to the depletion of resources on land. Since international marine environment guidelines for deep-sea mining will be set up by international organisations in the 2020s, remediation technologies are urgently required for deep-sea mining tailings. We show that rhamnolipid biosurfactant is an environmentally friendly substance and can be successfully used for the remediation of heavy metals in deep-sea mining tailings under various reaction conditions. Rhamnolipids therefore represent a useful extracting agent for heavy metals in deep-sea mining tailings. The removal of nickel (Ni), copper (Cu), and cadmium (Cd) would be enhanced in the presence of rhamnolipids with specific reaction times and concentrations. Future actual remediation technologies should be developed using rhamnolipid biosurfactant on the basis of these results.

In this paper, joint probability distribution for the size and mass of deep-sea manganese nodules is investigated and reliability-based design optimization (RBDO) of a deep-sea pilot mining robot is performed. As the size and mass of the manganese nodules are strongly correlated and their data are given as bivariate type I interval multiply censored data, a new statistical modeling method should be developed to deal with these issues. However, this is significantly difficult as the conventional methods cannot resolve these issues and there is no prior knowledge of the two physical properties. The proposed method, which employs the multinomial distribution to define the likelihood function and the Akaike information criterion to select the fittest marginal distribution and copula, provides a systematic approach to find the joint probability distribution using the type I interval multiply censored data. To demonstrate the accuracy and effectiveness of the proposed method, two numerical examples are tested. Then, the RBDO of the pilot mining robot is performed using the joint probability distribution resulted from the proposed method.

In an effort to enhance the efficiency and accuracy of deep-sea manganese nodule grasping behavior by a manipulator, a novel approach employing an improved YOLOv5 algorithm is proposed for the extraction of the shortest paths to manganese nodules targeted by the manipulator. The loss function of YOLOv5s has been improved by integrating a dual loss function that combines IoU and NWD, resulting in better accuracy for loss calculations across different target sizes. Additionally, substituting the initial C3 module in the network backbone with a C2f module is intended to improve the flow of gradient information while reducing computational demands. Once the geometric center of the manganese nodules is identified with the improved YOLOv5 algorithm, the next step involves planning the most efficient route for the manipulator to pick up the nodules using an upgraded elite strategy ant colony algorithm. Enhancements to the ACO algorithm consist of implementing an elite strategy and progressively decreasing the number of ants in each round. This method reduces both the number of iterations and the time required for each iteration, while also preventing the occurrence of local optimal solutions. The experimental findings indicate that the improved YOLOv5s detection algorithm boosts detection accuracy by 2.3%. Furthermore, when there are fewer than 30 target planning points, the improved algorithm requires, on average, 24% fewer iterations than the ACO algorithm to determine the shortest path. Additionally, the speed of calculation for each iteration is quicker while still providing the optimal solution.

PurposeThe aim of this study was to characterize the influence of soil contamination on the trace element accumulation in nodules, inter-element relationships inside the nodules, and mobility of trace elements incorporated in nodules.Materials and methodsWe collected nodules sized 2–4 mm from pollution-free areas and areas significantly contaminated by Pb, Cd, and Zn with Dystric Cambisols on the west coast of the Pacific Ocean and studied them using a combination of advanced analytical methods and noninvasive techniques.Results and discussionThe accumulation of trace elements by nodules was accompanied by a decrease of element mobility compared to surrounding soils. Nodules from uncontaminated soils can be highlighted as follows: (1) significant enrichment by Co and moderate enrichment by Ni, Cu, and Pb in the absence of Zn and Cd accumulation; (2) the strong affinities of Co and Cu towards Mn, association of Pb and Ni with both Mn and Fe; and (3) higher levels of Mn accumulation than in the nodules from contaminated soils. The main peculiarities of the nodules from contaminated soils were the increase in accumulation levels of Fe, Pb, Zn, and Cd, with the exception of Co; elements that were bound to Fe predominantly; and an increased trace element mobility compared to the nodules from the uncontaminated field. Nodules of two experimental fields had different composition of iron minerals.ConclusionsIron-Mn nodules act as barriers that limit the input of elements in soil solution. Increases in the Fe-containing compounds (both pedogenic and anthropogenic origin) in nodules enhanced the trace elements removed from the host-contaminated soils.

The geochemistry and mineralogy of Mn nodules offer crucial insights into the origins, environmental changes, and distribution of abyssal resources. However, the conventional laboratory X-ray diffractometer, usually employed for semi-quantitative analysis of mineral composition in Mn nodules, often fails to sufficiently detect minor phases due to beam flux limitations and high background signals. In this study, we investigated differences in manganate composition, even when comprising around 1% of the phase fraction, in two manganese nodules (KC-8 and KODOS-10) using high-resolution synchrotron X-ray diffraction. The Mn/Fe ratios of KC-8 and KODOS-10 were 1.32 and 6.24, respectively, indicating that KC-8 and KODOS-10 were predominantly formed in hydrogenetic and diagenetic environments. Both samples contained quartz, vernadite, buserite, and feldspar. Todorokite and illite were exclusively observed in KODOS-10. In KC-8, the phase fractions of vernadite and buserite among manganates ranged from 94(5)%–100(4)% and 6(1)%–0%, respectively. However, in KODOS-10, the fractions of vernadite, buserite, and todorokite ranged from 47(1)%–56(2)%, 33.6(4)%–40.1(3)%, and 10(3)%–16.3(8)%, respectively.

Ocean manganese nodules, which contain abundant Cu, Co, Ni and Mn resources, were reduced using biomass (sawdust) pyrolysis technology. Valuable metals were further extracted by acid leaching after the reduction process with high efficiency. The effects of sawdust dosage, reduction temperature, and time were investigated to obtain optimal operating parameters. The extraction rates of Mn, Cu, Co, and Ni reached as high as 96.1%, 91.7%, 92.5%, and 94.4%, respectively. Results from TGA show that the main pyrolysis process of sawdust occurs at temperature range of 250–375 °C with a mass loss of 59%, releasing a large amount of volatile substances to reduce the ocean manganese nodules. The pyrolysis activation energy of sawdust was calculated to be 52.68 kJ∙mol−1 by the non-isothermal kinetic model. Additionally, the main reduction reaction behind the main sawdust pyrolysis process was identified by the comparison of the assumed and actual TG curve. The thermodynamic analysis showed that the high valence manganese minerals were gradually reduced to Mn2O3, Mn3O4, and MnO by CO generated from sawdust pyrolysis. The shrinking core model showed that the reduction process is controlled by the surface chemical reaction with activation energy of 45.5 kJ∙mol−1. The surface of reduced ore and acid leached residue exhibited a structure composed of relatively finer pores and rougher morphology than the raw ore.

The occurrence of deep-sea ferromanganese nodules and crusts on the seafloor is widespread, providing an important resource for numerous metals such as Ni, Co, and Cu. Although they have been intensively studied in the past, the formation of micro-manganese nodules within carbonate rocks has received less attention, despite the considerable amounts of manganese released from the dissolution of the calcareous framework. The micro-petrographic and geochemical characteristics of reef carbonate rocks recovered from the Zhaoshu plateau in the Xisha uplift, north of the South China Sea, were studied using optical microscopy, scanning electron microscopy, confocal Raman spectrometry, and an electron probe micro-analyzer. The carbonate rocks are composed of biogenic debris, including frameworks of coralline algae and chambers of foraminifer, both of which are suffering strong micritization. Within the calcite micrite, numerous micro-manganese nodules were identified with laminated patterns. Mineral and elemental evidence showed that the Mn oxides in the carbonates are mixed with 10 Å vernadite, 7 Å vernadite and todorokite, both of which are closely associated with the carbonate matrix. The micro-nodules were found to have high Mn/Fe ratios, enriched in Ni and Cu and depleted in Co. We infer that theses nodules are mixed type with early diagenetic growth under oxic–suboxic conditions. The re-distribution of manganite within the rocks is likely influenced by micritization of the calcareous framework. We deduce that microbial-associated reduction of manganite induces the formation of diagenetic todorokite similar to nodules buried in marine sediments.

The recent and renewed interest in deep-sea mining relates to the decrease of ore grades of known land-based deposits, the increasing costs in land-based mining, as well as rising metal prices, and an increased demand for strategic metals. This study examines the economic requirements for future commercial mining projects focusing on manganese nodules. Beside the common measures of profitability, the net present value (NPV), and the internal rate of return (IRR), an additional measure, the net profit (NP), is presented to indicate the profitability by considering past and future cost and price trends. Furthermore, the approach may be applied to determine the areas of commercial interest. The Blue Mining project in the 7th Framework Programme of the European Commission serves as a reference case study. Having applied the developed methodology to a set of assumptions and estimates, results indicate that nodule mining projects would—at the time being and the foreseeable future—be launched at the verge of financial profitability.