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Advances in Comminution: From Crushing to Grinding Optimization
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Advances in Comminution: From Crushing to Grinding Optimization

A topical collection in Minerals (ISSN 2075-163X). This collection belongs to the section "Mineral Processing and Extractive Metallurgy".

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Editors

Prof. Dr. Weiran Zuo

E-Mail Website
Collection Editor
Zijin School of Geology and Mining, Fuzhou University, Fuzhou 350108, China
Interests: comminution; intelligent mineral processing; ore sorting; liberation; mineralogy; geometallurgy; classification; gravity separation; process control
Prof. Dr. Caibin Wu

E-Mail Website
Collection Editor
School of Resources and Environmental Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China
Interests: crushing; grinding; comminution; flotation
Dr. Ngonidzashe Chimwani

E-Mail Website
Collection Editor
Institute for the Development of Energy for African Sustainability, University of South Africa, Pretoria 0003, South Africa
Interests: crushing; grinding; comminution; comminution circuit optimisation.
Special Issues, Collections and Topics in MDPI journals

Topical Collection Information

Dear Colleagues,

Comminution—encompassing crushing and grinding—is a foundational step in the mineral processing industry. This inherently energy-intensive process aims to achieve optimal mineral liberation from gangue, delivering material with a suitable particle size distribution for downstream operations. Mounting energy and economic pressures, driven by increasingly complex orebodies and declining ore grades, make advancing energy-efficient comminution technology critically important for enhancing resource utilization, reducing operational costs, and minimizing environmental impact.

This Topical Collection invites contributions spanning advanced methodologies, fundamental liberation mechanisms, and industrial optimizations. We seek cutting-edge research and practical innovations that demonstrate significant potential to transform comminution efficiency and sustainability. Topics of interest include, but are not limited to, the following:

(1) Comminution circuit optimization.

(2) Advanced modeling and simulation technology.

(3) Intelligent process control systems and sensor-based automation.

(4) Pre-weakening, pre-concentration, and other pre-treatment strategies for comminution.

(5) Advancing equipment design and spare parts/grinding media/liner materials.

(6) Breakage and liberation mechanisms.

(7) Ore characterization.

(8) Screening and classification.

We look forward to receiving your contributions.

Prof. Dr. Weiran Zuo
Prof. Dr. Caibin Wu
Dr. Ngonidzashe Chimwani
Collection Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the collection website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • comminution circuit
  • process control
  • pre-treatment
  • energy efficiency
  • modeling
  • simulation
  • liner
  • liberation

Published Papers (7 papers)

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2026

Jump to: 2025

23 pages, 1804 KB  
Article
Macro–Meso-Parameter Calibration of Green Sandstone via XGBoost Screening and Stepwise Regression with Application to Impact-Fragmentation Analysis
by Chao Yu, Chuan Zhang, Tian Han, Xingjian Cao, Yingjia Zhao and Yongtai Pan
Minerals 2026, 16(5), 490; https://doi.org/10.3390/min16050490 - 7 May 2026
Viewed by 185
Abstract
Efficient calibration of discrete element meso-parameters is essential for reliable rock fragmentation modeling. This study focuses on green sandstone, combining uniaxial compression tests with PFC3D simulations to establish an XGBoost–stepwise regression framework for macro–meso-parameter calibration of the parallel bond model. XGBoost was used [...] Read more.
Efficient calibration of discrete element meso-parameters is essential for reliable rock fragmentation modeling. This study focuses on green sandstone, combining uniaxial compression tests with PFC3D simulations to establish an XGBoost–stepwise regression framework for macro–meso-parameter calibration of the parallel bond model. XGBoost was used to identify the dominant meso-parameters governing peak strength, elastic modulus, and Poisson’s ratio, and stepwise regression was applied to construct explicit nonlinear mapping equations. Peak strength is mainly controlled by shear strength τcp and normal strength σcp, while elastic modulus and Poisson’s ratio are primarily influenced by bond modulus Ecp and stiffness ratio kp*. Introducing quadratic and interaction terms improved model fit, with adjusted R2 increasing by 27.5% and 11.2%, respectively. The calibrated parameters reproduced laboratory mechanical indices with errors of 0.09%–3.745% and showed good agreement with the observed shear–brittle failure pattern. Based on the calibrated model, a representative impact-fragmentation simulation further revealed staged conversion of input energy into fracture-related energy during crack initiation, propagation, and through-failure. The proposed framework improves the efficiency and interpretability of PBM parameter calibration and supports DEM-based analysis of rock fragmentation and energy evolution. Full article
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14 pages, 1917 KB  
Article
Breakage Rate Modeling in Ball Mill Grinding of Calcined Clay and Limestone Mixtures
by María de Lourdes Pérez Lamorú, Iván Salazar, Hugo Javier Angulo-Palma, Yoalbys Retirado-Mediaceja, Yunior Correa-Cala, Yosvany Díaz Cárdenas, Juan Alberto Ribalta-Quesada, Roger Samuel Almenares Reyes, Manuel Saldana, Felipe M. Galleguillos Madrid and Norman Toro
Minerals 2026, 16(5), 458; https://doi.org/10.3390/min16050458 - 29 Apr 2026
Viewed by 225
Abstract
Replacing clinker with mixtures of calcined clay and limestone is one of the most sustainable strategies for decarbonizing the cement industry. However, the kinetic patterns governing the grinding behavior of these materials are not yet fully understood. This study developed a kinetic model [...] Read more.
Replacing clinker with mixtures of calcined clay and limestone is one of the most sustainable strategies for decarbonizing the cement industry. However, the kinetic patterns governing the grinding behavior of these materials are not yet fully understood. This study developed a kinetic model based on particle population balance to simulate this process. Experiments were conducted using a standard Bond ball mill, and the samples were characterized by X-ray diffraction. The results show that the grinding of calcined clay and its mixtures with limestone follows first-order kinetics. The proposed model simulates the process with a high degree of accuracy, with residual errors below 1.5% and a coefficient of determination exceeding 99%. Full article
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25 pages, 2146 KB  
Article
Machine Learning-Based Predictive Modelling of Key Operating Parameters in an Industrial-Scale Wet Vertical Stirred Media Mill
by Okay Altun, Aydın Kaya, Ali Seydi Keçeli, Ece Uzun, Meltem Güler and Nurettin Alper Toprak
Minerals 2026, 16(3), 311; https://doi.org/10.3390/min16030311 - 16 Mar 2026
Viewed by 785
Abstract
To the authors’ knowledge, this is the first industrial machine learning (ML) study focused on wet vertical stirred media milling. The study develops and validates machine learning (ML) models to predict the key operating parameters, namely mill discharge product size, mill feed slurry [...] Read more.
To the authors’ knowledge, this is the first industrial machine learning (ML) study focused on wet vertical stirred media milling. The study develops and validates machine learning (ML) models to predict the key operating parameters, namely mill discharge product size, mill feed slurry flow rate, mill power draw, and the specific energy consumption of an industrial wet vertical stirred media mill operating at a copper plant. A physics-guided workflow was adapted, combining relief coefficient-based variable screening with fundamental stirred milling principles to define 20 different structured model input scenarios. In the scope, six regression approaches, linear regression (LR), fine tree regression (FTR), support vector regression (SVR), random forest regression (RFR), artificial neural network regression (ANN), and Gaussian process regression (GPR), were trained and validated using plant sensor data and evaluated using R2 and RMSE. Overall performance was reasonable, with GPR providing the highest predictive accuracy, followed by RFR/ANN, while LR, SVR, and FTR performed lower. The potential benefit of feed size was also assessed conceptually through an upper-bound sensitivity analysis, representing a best-case scenario where an online feed size measurement would be available. Because the feed size descriptor (F80) was not independently measured but derived from an energy–size relationship, the associated accuracy gains are reported as theoretical upper-bound indications rather than independent predictive capability. Overall, the findings support ML-based decision support in stirred milling operations and motivate future work using independently measured feed size (or reliable proxy sensing). Full article
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23 pages, 4370 KB  
Article
Effect of Ball Filling Ratio on Fine Particle Production Characteristics During Ceramic Ball Grinding of Magnetite Ore
by Li Ling, Chengfang Yuan, Liying Sun, Caibin Wu, Quan Li, Ziyu Zhou and Zongyan Zhou
Minerals 2026, 16(3), 256; https://doi.org/10.3390/min16030256 - 28 Feb 2026
Viewed by 376
Abstract
To clarify the influence of the media filling ratio on fine particle production during ceramic ball grinding of magnetite, magnetite ore from the fine grinding stage of an industrial concentrator was investigated under different feed size classes and media filling ratios through grinding [...] Read more.
To clarify the influence of the media filling ratio on fine particle production during ceramic ball grinding of magnetite, magnetite ore from the fine grinding stage of an industrial concentrator was investigated under different feed size classes and media filling ratios through grinding kinetics experiments. The generation behavior of the fine and finest particle fractions during ceramic ball grinding was systematically analyzed. The results indicate that particle size fractions with sizes less than or equal to 0.150 mm exhibit pronounced zero-order production characteristics under different filling ratios, with cumulative yields showing a strong linear relationship with grinding time. This zero-order behavior is insensitive to variations in the media filling ratio. Conversely, the generation rate of the finest size fraction is significantly affected by the media filling ratio. For coarse feed sizes, the generation rate of the finest fraction initially increases and then decreases with increasing filling ratio, reaching a peak value of 6.23%/min at a filling ratio of 35%. When the feed falls below 1.18 mm, the generation rate of the finest fraction shows a strong positive correlation with the ceramic ball filling ratio. Furthermore, based on the functional relationship between the generation rate of the finest size fraction and the mill input power, an energy–size model for magnetite ceramic ball grinding was established, providing a quantitative description of the variation in the finest particle yield with respect to the input energy and media filling ratio. The findings provide a theoretical foundation for optimizing media filling ratios, enhancing fine grinding performance, and controlling overgrinding in industrial applications. Full article
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20 pages, 11536 KB  
Article
Kinetic Energy Evolution in the Impact Crushing of Typical Quasi-Brittle Materials
by Chuan Zhang, Xingjian Cao and Yongtai Pan
Minerals 2026, 16(1), 102; https://doi.org/10.3390/min16010102 - 21 Jan 2026
Viewed by 447
Abstract
Crushing is a critical step in the efficient utilization of quasi-brittle materials such as ores and solid wastes. During this process, materials undergo fracture, and the product particles are ejected, carrying significant kinetic energy. This study investigates typical quasi-brittle materials—concrete and quartz glass—by [...] Read more.
Crushing is a critical step in the efficient utilization of quasi-brittle materials such as ores and solid wastes. During this process, materials undergo fracture, and the product particles are ejected, carrying significant kinetic energy. This study investigates typical quasi-brittle materials—concrete and quartz glass—by conducting impact crushing tests using a drop-weight apparatus under varying contact modes and input energy levels. High-speed camera was employed to capture the fracture patterns of the materials and the trajectories of the ejected particles, enabling the calculation of kinetic energy during crushing. The results indicate that under point contact loading, both kinetic energy and its proportion increase significantly with rising input energy. In contrast, under surface contact loading, the kinetic energy and its proportion exhibit minimal change as input energy increases. The average ejection velocity of particles from quartz glass specimens during crushing was 6.28 m/s, which is 2.21 times that of concrete specimens. Moreover, the average proportion of kinetic energy in quartz glass crushing was 5.049%, approximately 14.43 times greater than that in concrete. Enhancing material toughness and adopting surface contact loading help reduce both the kinetic energy and its proportion during crushing. This research contributes to minimizing kinetic energy loss and improving the efficiency of energy utilization in crushing processes. Full article
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2025

Jump to: 2026

16 pages, 3147 KB  
Article
A Novel Approach for Ceramic Ball Media Formulation in Wet Ball Mills
by Yuqing Li, Ningning Liao, Caibin Wu, Jiemei Ye, Yue Cheng, Ruien Tao, Yongfei Ning and Yiwei Cheng
Minerals 2026, 16(1), 52; https://doi.org/10.3390/min16010052 - 31 Dec 2025
Cited by 1 | Viewed by 684
Abstract
Ceramic balls, as an emerging grinding medium, require a systematic method for optimizing their size distribution in wet ball mills. This study proposes an innovative approach that integrates Duan’s semi-theoretical ball diameter formula with breakage statistical mechanics to determine the optimal ceramic ball [...] Read more.
Ceramic balls, as an emerging grinding medium, require a systematic method for optimizing their size distribution in wet ball mills. This study proposes an innovative approach that integrates Duan’s semi-theoretical ball diameter formula with breakage statistical mechanics to determine the optimal ceramic ball size distribution. The ideal ball diameters for grinding 2.36–3.0 mm, 1.18–2.36 mm, 0.60–1.18 mm, and 0.30–0.60 mm tungsten ore were identified as 55 mm, 50 mm, 35 mm, and 20 mm, respectively. Subsequently, the optimal ball size distribution was formulated as CB3: Ø55 mm:Ø50 mm:Ø35 mm:Ø20 mm = 30%:40%:20%:10%. Comparative sieve analysis and discrete element method (DEM) simulations confirmed that the CB3 distribution yields the highest proportion of qualified particles, the most favorable collision frequency, and the greatest kinetic energy among all tested configurations. The proposed method demonstrates both accuracy and practicality, providing a theoretical foundation for the industrial application of ceramic ball grinding systems. Full article
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16 pages, 1274 KB  
Article
Study on the Effect of Grinding Media Material and Proportion on the Cyanide Gold Extraction Process
by Guiqiang Niu, Yunfeng Shao, Qingfei Xiao, Mengtao Wang, Saizhen Jin, Guobin Wang and Yijun Cao
Minerals 2025, 15(10), 1031; https://doi.org/10.3390/min15101031 - 28 Sep 2025
Viewed by 1494
Abstract
Laboratory and industrial tests were conducted to study the impact of grinding media material on key indicators such as grinding product particle size, sodium cyanide consumption, gold recovery rate, unit power consumption, and ball consumption. Laboratory test results indicate that the reasonable mixing [...] Read more.
Laboratory and industrial tests were conducted to study the impact of grinding media material on key indicators such as grinding product particle size, sodium cyanide consumption, gold recovery rate, unit power consumption, and ball consumption. Laboratory test results indicate that the reasonable mixing of ceramic and steel balls can achieve an increase of more than 2.8% in the fineness of the grinding product (−0.038 mm), an increase of 0.3% in the gold recovery rate, and a decrease of 1.3 kg/t in the consumption of sodium cyanide. Industrial trial studies indicate that, compared to the traditional steel ball scheme, using a ceramic ball to steel ball mass ratio of 3:1 under conditions of processing 50,000 tons of gold concentrate annually can save a total of 1.31 million yuan in annual ball consumption, electricity consumption, and cyanide consumption costs. Additionally, the improved recovery rate generates an additional economic benefit of 3.63 million yuan, resulting in an annual comprehensive economic benefit increase of 4.94 million yuan. In summary, in gold cyanide leaching grinding, the mixture ratio between ceramic balls and steel balls demonstrates significant potential for energy conservation, cost reduction, and efficiency enhancement, providing a theoretical basis and technical support for subsequent process optimization and green gold extraction. Full article
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