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Conventional oil collectors are difficult for low rank coal (LRC) to achieve satisfying flotation performance due to the abundant oxygen-containing functional groups. In this study, Fe2+ was added to float LRC using oleic acid (OA) as collector. The contact angle, induction time, zeta potential, chemical solution calculation and XPS were used to study the effects of Fe2+ on LRC flotation. Compared to OA alone, the yield of flotation concentrate and contact angle increased by at least 14% and 6.9°, the induction time decreased by 14 ms in presence of Fe2+, indicating that Fe2+ enhanced the hydrophobicity of LRC. Chemical solution calculation demonstrated that Fe2+ mainly existed in the form of Fe(OH)+ at natural pH. The XPS results indicated that Fe(OH)+ interacted with hydroxyl groups on LRC to form O-Fe+, which reacted with the carboxyl groups of OA to form metal-OA complex O-Fe-OA.

The effect mechanism of mixing ratio on the adsorption behavior of low-rank coal surface using mixed collectors has not been systematically studied. In this study, dodecane (D) and n-valeric acid (...

Bubble–particle interactions are crucial in the flotation process, and the influence of adsorbed chemicals on bubble-surface collisions/attachment is important to fully understand the role of mixed...

Monocular 3D object detection is an ill-posed problem due to the loss of geometry information in 2D images. To improve the reliability of monocular vision system, we propose to replace the deterministic estimation with a probabilistic prediction by computing both aleatoric and epistemic uncertainty in 3D detection task. We further design a continuous focal loss that can improve location accuracy and when combining with aleatoric uncertainty estimation, also reduce the effect of noise data during training. Our method is capable of estimating uncertainty in a single forward pass while achieving nearly real-time performance with 0.1s per image on a modern platform. Additionally, to make fair comparison between point and probabilistic prediction, we present a novel probabilistic localization evaluation metric which computes the average error over the predicted location distribution. Our experiments indicate that we achieve competitive result on the official KITTI 3D detection leaderboard, among other deterministic methods. Furthermore, our method gains more accurate localization accuracy under different localization evaluation metrics.

LiFePO4 soft package battery has been widely used in industry because of its high working voltage, low cost, good thermal stability and high security. However, there are so many steps to prepare a commercial soft package battery and the required equipments are too complex for one to complete all the operations. Also, the proportion of materials in each company is different and not completely public available, which makes it hard to analyze the changes of material structure after various treatments. Therefore, a simplified preparation of the LiFePO4 soft package full battery in laboratory needs to be realized for comparison and analysis in the follow-up study. In this paper, the laboratory simplified preparation process of LiFePO4 soft package battery was introduced in details. The morphology and cycle performance of three batteries with three different ratios of active materials, conductive agents and binders in the cathode material were studied. It was found that the battery with the mass ratio of 92:6.5:7 had the highest discharge platform (3.3 V), the largest specific capacity (153.4 mAh/g) and cycle retention rate. These discussions provide a good reference to repair and improve the industrial soft package full battery.

Estimating 3D orientation and translation of objects is essential for infrastructure-less autonomous navigation and driving. In case of monocular vision, successful methods have been mainly based on two ingredients: (i) a network generating 2D region proposals, (ii) a R-CNN structure predicting 3D object pose by utilizing the acquired regions of interest. We argue that the 2D detection network is redundant and introduces non-negligible noise for 3D detection. Hence, we propose a novel 3D object detection method, named SMOKE, in this paper that predicts a 3D bounding box for each detected object by combining a single keypoint estimate with regressed 3D variables. As a second contribution, we propose a multi-step disentangling approach for constructing the 3D bounding box, which significantly improves both training convergence and detection accuracy. In contrast to previous 3D detection techniques, our method does not require complicated pre/post-processing, extra data, and a refinement stage. Despite of its structural simplicity, our proposed SMOKE network outperforms all existing monocular 3D detection methods on the KITTI dataset, giving the best state-of-the-art result on both 3D object detection and Bird's eye view evaluation. The code will be made publicly available., 8 pages, 6 figures

Low-rank coals are difficult to float using common hydrocarbon oily collectors, such as dodecane and diesel. In this investigation, a mixture of dodecane and n-valeric acid was used as a collector ...

It is well known that the stability of hydration film on the particle surface affected the particle-bubble attachment in a flotation process. In this paper, the effect of attached nanosilica partic...

Waste motor oil/lubricating oil (WMO) is a hazardous and important resource. The waste siloxane-based motor oil/lubricating oil (WSMO) has a special composition based on siloxane. The WSMO has a large and increasing production worldwide. In this paper, the feasibility of WSMO as a collector for low-rank coal (LRC) flotation was discussed with a comparison to diesel oil (DO). The gas chromatography-mass spectrometry (GC/MS) and thermal gravimetric analysis (TGA) were used to analyze the chemical composition of WSMO. The flotation experiment was conducted to investigate the collectivity and selectivity of WSMO as an LRC collector. The interaction between WSMO and LRC was systematically analyzed using X-ray photoelectron spectroscopy (XPS), contact angle, zeta potential, and induction time measurements. The results indicated that WSMO majorly contained dimethylsiloxane and cyclodimethysiloxane with various chain lengths. High concentrates yield and low ash content was obtained in the flotation using WSMO. The adsorption of WSMO can mask the oxygen-containing groups (OCGs) on the LRC surface, leading to an increase of C content and a decrease in O content. This was beneficial to improve the hydrophobicity of the LRC surface so that the water-coal contact angle increased from 35.6° to 57.85° after WSMO treatment. Moreover, a significant increase in zeta potential was observed in the pH range of 4 to 10. LRC particles pretreated with WSMO were more easily adhere to the bubble surface in a short induction time of 40 ms. It was demonstrated that WSMO was an effective collector to promote LRC flotation.

The mesoscopic scale is usually used to realize the dynamics calculation on a larger spatial scale and time scale. However, there have been few dynamic simulation calculations attempted on the mesoscopic scale for coal flotation systems. In this study, based on the Martini force field, the Coarse-Grain (CG) models of coal, dodecane, and water were established, and the dynamics simulations were performed to study the collector droplet spreading at the coal-water interface. The CG dynamics simulations results showed that the interaction between dodecane and coal was a spontaneous process, and dodecane existed as a collector at the coal-water interface. The radial distribution function of dodecane around coal and water indicated that dodecane was more likely to be distributed around the coal, and as far away as possible from the water. The CG dynamics simulations also revealed the specific spreading stages of the dodecane droplet. The dodecane drop first moved in the form of droplets to the coal-water interface in the aqueous phase. Then at the coal-water interface, the circular droplet broke its shape and spread rapidly on the coal surface through the dodecane CG molecules. Finally, the dodecane CG molecules penetrated deeper into the coal surface layer and formed a dynamic and stable oil film. This provided a good attempt and reference for studying the spreading of collector droplets on the coal-water interface.

The article discusses the application of hydrophobic polystyrene nanoparticles as a collector for coal flotation, aiming to demonstrate the possibility of sorting coal fines with nanoparticles. The...

Waste motor oil (WMO) is a hazardous oil pollutant in the automobile industry and low-rank coal slime (LRCS) is a solid waste produced during coal preparation. This paper introduces a comprehensive utilization scheme for these two waste resources through froth flotation. Fourier Transform Infrared Spectroscopy (FTIR) measurement showed that WMO contains hydrocarbons and their oxides (alkane, aromatic derives, ester or carboxylic acid). When acting as a collector for the flotation of LRCS, WMO resulted in a cleaned coal yield of 77.29% and an ash content of 8.97% at the dosage of 5 kg/t, which was a significant improvement over the traditional collector, diesel oil. A novel co-treatment scheme for WMO and LRCS was proposed and discussed. The co-treatment scheme can bring high quality products for the coal preparation plant and give an alternative of disposing the WMO. The traditional WMO disposal methods like WMO regeneration may produce secondary pollution while the co-treatment scheme has little and controllable environmental impact. What’s more, the scheme has better economic benefit than LRCS flotation using diesel oil or the WMO traditional disposal method.