Graphite is a critical mineral facing supply chain risks and growing demand that drives the need for reliable synthetic production methods. This study demonstrates a scalable approach for advanced graphite synthesis through carbonate electrolysis on molten tin-salt liquid-liquid interfaces. These interfaces offer unique physicochemical characteristics that can facilitate the layered sp2 carbon growth. Owing to its atomically smooth surface, molten tin suppresses step-edge pinning and defect-mediated nucleation of carbon atoms, while its minimal to no adhesion with carbon facilitates the release of thin carbon layers. Our results indicate that the presence of Co2+, Co3+ and Ni2+ ions at the liquid tin surface can significantly enhance the sp2 carbon growth into ultrathin graphitic carbon. The study also demonstrates graphite production at the gram-scale, using custom-designed electrochemical reactor prototypes based on molten tin cathodes. These reactors achieved a low onset cell potential of approximately 1.7-2.0 V, high faradaic efficiencies of up to 96%, current densities exceeding 450 mA cm-2 and a high carbon production rate of around 0.7 kg m-2 h-1. This study provides important insights into molten carbonate electrolysis and demonstrates its potential for the scalable CO2 valorisation into a high-value energy material.

A systematic approach was employed to evaluate and quantify the impact of ultra-fine particles on dewatering processes. Model suspensions were created by incorporating calcium carbonate particles of two distinct sizes (2.1 mu m and 12.2 mu m Sauter mean diameter) to simulate various levels of ultra-fine content. The objective was to compare differences based solely on particle size while maintaining consistent surface chemistry characteristics. As the ultra-fine content increased from 0 % to 100 %, the gel point decreased linearly from 38 v/v% to 22 v/v %, permeability decreased by up to 40 times, shear yield stress increased by 100 times, and extent of dewatering decreased from 63 v/v% to 53 v/v% at 600 kPa pressure. However, in specific blends, the dewatering extent exceeded expectations, whereby beyond a certain compressive load, the data is consistent with the optimal packing of smaller particles into the voids between the coarser particles. Furthermore, the impact of altering compressibility and permeability on dewatering was quantified using a numerical filter press model, highlighting the sensitivity of dewatering to the content of ultra-fine particles. The filtration time decreases exponentially with increasing Sauter mean diameter, following the relationship tF= 1142exp(- 0.28ds). Additionally, the filtration area is linearly related to the filtration time, as shown by the equation A = 1.37(tF + 300).

The liquid metal catalysts present catalytic systems with dynamic interfaces and mobile active atoms. The origin of catalytic performance in such a liquid phase system has remained elusive for the rational design of efficient liquid metal catalysts. A detailed understanding of the atomistic structure and fundamental chemistry at the interface of liquid metals would optimize materials for catalytic reactions. However, there has been limited success in fully addressing the atomic-level structural arrays of liquid metal catalysts and their reaction mechanisms in catalysis. Recently, liquid metals have emerged as catalysts with advantageous characteristics for a wide range of applications. This review explores the fundamental properties and reaction chemistry of liquid metal catalysts. Recent advances in liquid metal research are outlined with respect to thermal, electrochemical, and other catalysis. Considering available density functional theory calculations and ab initio molecular dynamics simulations, we highlight the exceptional capabilities of molecular simulation approaches in characterizing the surface structures, electronic properties, and catalytic properties of liquid metals and alloys on the atomic level. Furthermore, we discuss the current simulation challenges for liquid metal systems and outline how molecular simulation approaches can contribute to developing liquid metals in catalysis.

In this paper, we present spatiotemporal slope stability analytics for failure estimation (SSSAFE), a deterministic, data-driven model of force transmission in a rock slope. Its input solely comprises the spatiotemporal surface deformation of the slope, here gathered from slope stability radar (SSR). The model combines recent advances from data analytics, granular media physics and mechanics, and slope stability monitoring. SSSAFE is unique in its explicit connections to the underlying physics of strength and failure in the precursory failure regime (PFR) of granular systems. Distinct from the single pixel selection for time of failure methods, this model exploits all the kinematic information available on the entire monitoring domain to quantitatively track the coupled evolution of the preferred transmission pathways for force and energy (socalled force chains) and the preferential crack paths. This coupled evolution gives rise to a force bottleneck, which comprises vulnerable and congested sites closest to breaking point (fracture). The force bottleneck is an emergent structure that is not static. Prior studies have shown that the spatiotemporal dynamics of this bottleneck holds clues to the ultimate location and timing of failure. Initially, in the early stages of PFR, the bottleneck continually shifts in location in the rock body. This process is due to the inherent redundancies in the force pathways in the rock mass. Such redundant paths enable stresses to be redistributed and diverted away from the pre-existing bottleneck to another location where a new bottleneck may then form. However, as damage spreads, and the time of failure draws near, a tipping point is reached when all the redundant paths have been exhausted and no further stress reroutes are possible. At this point, a recurring bottleneck, invariant in space and time, emerges along which previously disconnected cracks begin to coalesce. Simultaneously, this process leads to a persistent kinematic clustering pattern, as the active region begins to detach from the rest of the slope and accelerate. That is, the closer it is to the time of failure, the more the kinematic clusters (the two groups of monitoring points on either side of the bottleneck) move such that intra-cluster motions become increasingly similar while inter-cluster motions become increasingly different. Here we demonstrate how to extract, quantify, and exploit this particular form of spatiotemporal dynamics from SSR data for two distinct open pit mine slopes, for the purposes of early prediction of failure of the geometry, location, and time of collapse.

Impending catastrophic failure of granular earth slopes manifests distinct kinematic patterns in space and time. While risk assessments of slope failure hazards have routinely relied on the monitoring of ground motion, such precursory failure patterns remain poorly understood. A key challenge is the multiplicity of spatiotemporal scales and dynamical regimes. In particular, there exist a precursory failure regime where two mesoscale mechanisms coevolve, namely, the preferred transmission paths for force and damage. Despite extensive studies, a formulation which can address their coevolution not just in laboratory tests but also in large, uncontrolled field environments has proved elusive. Here we address this problem by developing a slope stability analytics framework which uses network flow theory and mesoscience to model this coevolution and predict emergent kinematic clusters solely from surface ground motion data. We test this framework on four data sets: one at the laboratory scale using individual grain displacement data; three at the field scale using line-of-sight displacement of a slope surface, from ground-based radar in two mines and from space-borne radar for the 2017 Xinmo landslide. The dynamics of the kinematic clusters deliver an early prediction of the geometry, location and time of failure.

It is timely that Engineering should devote a special issue to the topic of clean energy. The authors of the research articles and the views and comments cover much of what is a very diverse and controversial field. Responses to this topic cover a spectrum ranging from those that argue for emergency action to prevent the extinction of the human race to those that deny the existence of climate change. Before dismissing any group, it is informative for engineers and technologists to note that there is a fairly even distribution across this spectrum

The optimisation of solid-liquid separation or dewatering processes for more efficient operation and reuse of material streams is of high importance. Suspension dewatering aims to increase the solids concentration and exhibits two limitations: the dewatering extent and the rate.A novel dewatering device, called High Pressure Dewatering Rolls (HPDR), has been developed. It combines shear and compression while maintaining a short filtration length between the rollers. The HPDR challenges the limitations of dewatering processes through the application of high pressures and induced shear to aid the extent of dewatering, and a short filtration length to allow fast dewatering. A prototype HPDR is described along with a performance assessment for different operating conditions as well as a comparison against state-of-the-art technology for a variety of industrial suspensions. The results demonstrate that the HPDR prototype, without any optimisation, outperforms or achieves comparable cake solids concentrations to existing equipment in a continuous mode of operation. Analysis of energy consumption and throughput remain outstanding and require further prototype development.

The history of mineral processing in general and flotation in particular is long and has always been tied to mining methods of the day. Building on the ever-improving fundamental understanding of the underlying science, the most significant trend in flotation has been the putting into practice the learnings from trailblazers such as Professor Fuerstenau that has given the confidence that enabled an ever-increasing scale of operations. There is, however, doubt this ongoing trend is enough to maintain the economics against global trends such as that of falling grades, increasing mining costs, pressure on water supply and demand, rising energy demands needed for mineral processing, and a focus on whole of life value and mine legacy issues.

Landslides are a common natural disaster that claims countless lives and causes huge devastation to infrastructure and the environment. The recent spate of landslides worldwide has prompted renewed calls for better forecasting methods which could boost the performance of early warning systems in real time. Although the variety, volume and precision of monitoring data have steadily increased, methods for analysing such data sets for landslide prediction have not kept pace with the rapid advances in complex systems data analytics and micromechanics of granular failure. Here we help close this gap by developing a new model to analyse kinematic data using complex networks. Like no other, our model incorporates lessons learned from micromechanics experiments on granular systems, with a focus on space-time variations and correlations in motion germane to the precursory dynamics of localised failure. We apply our model to ground-based radar data and predict where failure locates in a rock slope, spanning hundreds of meters, almost two weeks in advance. This is a first step in a broader effort to quantify the probability of a landslide occurring within a specified time based on data on kinematics and common triggers such as precipitation. (C) 2018 Elsevier Ltd. All rights reserved.

The paper starts by considering the broad framework of the industry, and in particular whether the current boom in production and the threatened shortages of certain strategic minerals are likely to lead to scarcities. The paper suggests that shortages are unlikely and that minerals will become even more widely available and at lower cost. That said, energy and maintaining the license to operate will drive the introduction of new technologies. Using copper as an example, we point out the inevitable lower grades that will be processed and for ever lower selling prices in real terms, as has happened for centuries. Technological innovation is the driver of these trends, and the paper highlights several areas where significant changes are poised to occur: in pre-conditioning and in minimizing grinding by removing gangue at coarser sizes earlier in the flowsheet; in recognition that the excessive energy used in comminution may be largely caused by the formation of force chains that bear the load and resist breakage events; and finally, two developments by Jameson (Can Metallurgical Quart 49(4), 324–330, 2010) for more energy efficient fine particle flotation and a significantly new concept for coarse particle flotation to 1400 micron.