Scale-up of decanter centrifuges for the particle separation and mechanical dewatering in the minerals processing industry by means of a numerical process model

Decanter centrifuges are frequently used for thickening, dewatering, classification, or degritting in the mining industry and various other sectors. Their use in an industrial process chain requires a sufficiently accurate prediction of the product and the machine behaviour. For this purpose, experiments on a smaller pilot-scale are carried out for scale-up of a decanter centrifuge, which is usually a major challenge. Predicting the process behaviour of decanter centrifuges from laboratory tests is rather difficult. Basically, there are two common ways of scale-up: First, via analytical methods and the law of similarity, which often requires an enormous experimental effort. Second, using numerical models, which demands a mathematically and physically precise description of the multiple processes running simultaneously in such machines. This article provides an overview of both methods for scale-up of a decanter centrifuge. The concept of a previous developed numerical approach is introduced. Pros and cons of both scale-up methods are compared and further discussed. Experiments on lab-scale, pilot-scale, and industrial-scale decanter centrifuges with two different finely dispersed calcium carbonate water suspensions were carried out and simulations were done to investigate and prove the scale-up capability and transferability of the numerical approach

Autonomous Processes in Particle Technology

Battery materials, pharmaceuticals, solar cells, coffee powder, 3D printed components, etc., all these products have in common that they are predominantly made of particles. Ensuring high product quality with optimal raw material and energy utilization is only possible with extensive and many years of experience in the operation of such processes. This unsatisfactory situation is due to the complexity of particulate products, which still hinders extensive automation and autonomous process control. The challenge is to couple the respective basic operations with characterization devices, process dynamics and modern control algorithms to form a closed loop for process control. As a result, some day it should be possible to set the desired property profiles of particulate products with the most energy- and raw material-efficient operation possible with a “push of a button”

Grey box modelling of decanter centrifuges by coupling a numerical process model with a neural network

Continuously operating decanter centrifuges are often applied for solid-liquid separation in the chemical and mining industries. Simulation tools can assist in the configuration and optimisation of separation processes by, e.g., controlling the quality characteristics of the product. Increasing computation power has led to a renewed interest in hybrid models (subsequently named grey box model), which combine parametric and non-paramteric models. In this article, a grey box model for the simulation of the mechanical dewatering of a finely dispersed product in decanter centrifuges is discussed. Here, the grey box model consists of a mechanistic model (as white box model) presented in a previous research article and a neural network (as black box model). Experimentally determined data is used to train the neural network in the area of application. The mechanistic approach considers the settling behaviour, the sediment consolidation, and the sediment transport. In conclusion, the settings of the neural network and the results of the grey box model and white box model are compared and discussed. Now, the overall grey box model is able to increase the accuracy of the simulation and physical effects that are not modelled yet are integrated by training of a neural network using experimental data

Investigation of Centrifugal Fractionation with Time-Dependent Process Parameters as a New Approach Contributing to the Direct Recycling of Lithium-Ion Battery Components

Recycling of lithium-ion batteries will become imperative in the future, but comprehensive and sustainable processes for this are still rather lacking. Direct recycling comprising separation of the black mass components as a key step is regarded as the most seminal approach. This paper contributes a novel approach for such separation, that is fractionation in a tubular centrifuge. An aqueous dispersion of cathode materials (lithium iron phosphate, also referred to as LFP, and carbon black) serves as exemplary feed to be fractionated, desirably resulting in a sediment of pure LFP. This paper provides a detailed study of the commonly time-dependent output of the tubular centrifuge and introduces an approach aiming to achieve constant output. Therefore, three different settings are assessed, constantly low, constantly high and an increase in rotational speed over time. Constant settings result in the predictable unsatisfactory time-variant output, whereas rotational speed increase proves to be able to maintain constant centrate properties. With further process development, the concept of fractionation in tubular centrifuges may mature into a promising separation technique for black mass in a direct recycling process chain

Investigation of Centrifugal Fractionation with Time-Dependent Process Parameters as a New Approach Contributing to the Direct Recycling of Lithium-Ion Battery Components

Recycling of lithium-ion batteries will become imperative in the future, but comprehensive and sustainable processes for this are still rather lacking. Direct recycling comprising separation of the black mass components as a key step is regarded as the most seminal approach. This paper contributes a novel approach for such separation, that is fractionation in a tubular centrifuge. An aqueous dispersion of cathode materials (lithium iron phosphate, also referred to as LFP, and carbon black) serves as exemplary feed to be fractionated, desirably resulting in a sediment of pure LFP. This paper provides a detailed study of the commonly time-dependent output of the tubular centrifuge and introduces an approach aiming to achieve constant output. Therefore, three different settings are assessed, constantly low, constantly high and an increase in rotational speed over time. Constant settings result in the predictable unsatisfactory time-variant output, whereas rotational speed increase proves to be able to maintain constant centrate properties. With further process development, the concept of fractionation in tubular centrifuges may mature into a promising separation technique for black mass in a direct recycling process chain

Scale-Up of Decanter Centrifuges for the Particle Separation and Mechanical Dewatering in the Minerals Processing Industry by Means of a Numerical Process Model

Decanter centrifuges are frequently used for thickening, dewatering, classification, or degritting in the mining industry and various other sectors. Their use in an industrial process chain requires a sufficiently accurate prediction of the product and the machine behaviour. For this purpose, experiments on a smaller pilot-scale are carried out for scale-up of a decanter centrifuge, which is usually a major challenge. Predicting the process behaviour of decanter centrifuges from laboratory tests is rather difficult. Basically, there are two common ways of scale-up: First, via analytical methods and the law of similarity, which often requires an enormous experimental effort. Second, using numerical models, which demands a mathematically and physically precise description of the multiple processes running simultaneously in such machines. This article provides an overview of both methods for scale-up of a decanter centrifuge. The concept of a previous developed numerical approach is introduced. Pros and cons of both scale-up methods are compared and further discussed. Experiments on lab-scale, pilot-scale, and industrial-scale decanter centrifuges with two different finely dispersed calcium carbonate water suspensions were carried out and simulations were done to investigate and prove the scale-up capability and transferability of the numerical approach

MGMT promoter methylation in triple negative breast cancer of the GeparSixto trial

Triple-negative breast cancer (TNBC) is typically treated with chemotherapeutic agents, including carboplatin (Cb), an DNA platinating agent. The O6-methylguanine-DNA-methyltransferase gene (MGMT) encodes for the protein O6-alkylguanine-DNA-alkyltransferase (MGMT protein). MGMT protein is involved in DNA repair mechanisms to remove mutagenic and cytotoxic adducts from O6-guanine in DNA. In glioblastoma multiforme, MGMT methylation status is a predictive biomarker for increased response to temozolomide therapy. It has been suggested, that MGMT protein may have relevance for cellular adaptation and could have an influence on resistance to carboplatin therapy. We investigated the influence of MGMT promoter methylation on pathologic complete response and survival of patients with TNBC treated in the neoadjuvant GeparSixto trial. In 174 of 210 available TNBC tumors a valid MGMT promoter methylation status was determined by pyrosequencing of 5 CpG islands. In 21.8%, we detected a mean MGMT promoter methylation >10%. Overall, MGMT promoter methylation was not significantly associated with pathological complete response (pCR) rate. After stratification for the two therapy arms with and without Cb no statistically significant differences in therapy response rates between the two MGMT promoter methylation groups could be observed. Our results show that different MGMT promoter methylation status is not related to different chemotherapy response rates in the TNBC setting in GeparSixto

Low Expression of RGS2 Promotes Poor Prognosis in High-Grade Serous Ovarian Cancer

RGS2 regulates G-protein signaling by accelerating hydrolysis of GTP and has been identified as a potentially druggable target in carcinomas. Since the prognosis of patients with high-grade serous ovarian carcinoma (HGSOC) remains utterly poor, new therapeutic options are urgently needed. Previous in vitro studies have linked RGS2 suppression to chemoresistance in HGSOC, but in situ data are still missing. In this study, we characterized the expression of RGS2 and its relation to prognosis in HGSOC on the protein level by immunohistochemistry in 519 patients treated at Charité, on the mRNA level in 299 cases from TCGA and on the single-cell level in 19 cases from publicly available datasets. We found that RGS2 is barely detectable on the mRNA level in both bulk tissue (median 8.2. normalized mRNA reads) and single-cell data (median 0 normalized counts), but variably present on the protein level (median 34.5% positive tumor cells, moderate/strong expression in approximately 50% of samples). Interestingly, low expression of RGS2 had a negative impact on overall survival (p = 0.037) and progression-free survival (p = 0.058) on the protein level in lower FIGO stages and in the absence of residual tumor burden. A similar trend was detected on the mRNA level. Our results indicated a significant prognostic impact of RGS2 protein suppression in HGSOC. Due to diverging expression patterns of RGS2 on mRNA and protein levels, posttranslational modification of RGS2 is likely. Our findings warrant further research to unravel the functional role of RGS2 in HGSOC, especially in the light of new drug discovery

Human leucocyte antigen class I in hormone receptor-positive, HER2-negative breast cancer: association with response and survival after neoadjuvant chemotherapy

Background Clinical application of cancer immunotherapy requires a better understanding of tumor immunogenicity and the tumor microenvironment. HLA class I molecules present antigens to CD8+ cytotoxic cells. Their loss or downregulation is frequently found in tumors resulting in reduced T cell responses and worse prognosis. Methods We evaluated HLA class I heavy chain expression by immunohistochemistry in 863 biopsies (GeparTrio trial). Patients received neoadjuvant chemotherapy and adjuvant endocrine treatment if tumors were hormone receptor-positive (HR+). In parallel, the expression of HLA-A was analyzed using a microarray cohort of 320 breast cancer patients from the MD Anderson Cancer Center. We evaluated its association with clinical outcome, tumor-infiltrating lymphocytes (TILs), and immune cell metagenes. Results In HR+/HER2− breast cancer, HLA class I heavy chain expression was associated with increased TILs and better response to chemotherapy (7% vs. 14% pCR rate, P = 0.029), but worse disease-free survival (hazard ratio (HR) 1.6 (1.1–2.4); P = 0.024). The effect was significant in a multivariate model adjusted for clinical and pathological variables (HR 1.7 (1.1–2.6); P = 0.016) and was confirmed by analysis of HLA-A in a microarray cohort. HLA-A was correlated to most immune cell metagenes. There was no association with response or survival in triple-negative or HER2+ disease. Conclusions The study confirms the negative prognostic role of lymphocytes in HR+ breast cancer and points at a complex interaction between chemotherapy, endocrine treatment, and tumor immunogenicity. The results point at a subtype-specific and potentially treatment-specific role of tumor-immunological processes in breast cancer with different implications in triple-negative and hormone receptor-positive disease