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Meet Sadia Manzoor, a chemist turned laser technology expert, whose passion for innovation has taken her from academia to industry. Working with SPECTRAL Industries on the DINAMINE project, Sadia is advancing Laser-Induced Breakdown Spectroscopy (LIBS) to revolutionize real-time material characterization for the mining industry.

As Work Package leader, Sadia oversees the development of Mineral Processing Models (MPM) and cutting-edge LIBS sensors to enable quick, accurate analysis of materials—directly at mine sites.

By optimizing operations, reducing resource waste, and addressing industry challenges, her work is unlocking smarter, more sustainable mining practices.

Looking ahead, the DINAMINE project promises to transform mining digitization, with real-time sensing tools that improve decision-making and boost efficiency.

Discover more by reading her interview!

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Tell us about yourself 

I am originally from Pakistan, where I earned my degree in chemistry and began my career as a college educator. Although I was enjoying my teaching experience, I always had a desire to pursue higher studies. This ambition drove me to move to Madrid, where I completed both a Master and a PhD at the Department of Analytical Chemistry, Complutense University of Madrid (UCM). My studies and research at UCM, marked a turning point in my professional life, as my field of work transitioned from traditional “wet chemistry”, typically associated with classical laboratory methods and mixing chemicals, to a novel laser-based technology, i.e. LIBS – Laser Induced Breakdown Spectroscopy. Our research work directed towards exploring LIBS for analytical applications. LIBS, I would say, is a niche technology and occupies a unique space within laser research. My stay at UMALASERLAB, University of Malaga introduced me to SPECTRAL Industries, and I am happy that I have continued working in the same field exploring its potential. Working at SPECTRAL and undergoing the shift from academia to industry has allowed me to adopt a more practical approach and seeing that how scientific advancements can directly impact industries like mining. My roles at SPECTRAL range from engineering and research to currently Project Management connected to DINAMINE and exploring the mining sector in South America with respect to the use of LIBS sensors for inline analysis in South America. I have found both these mining-based projects an exciting opportunity, as along with offering and finding solutions in terms of technical innovation, I am also acquiring a deeper understanding of the challenges and opportunities of their implementation in the mining sector. 

What inspires you about working on the DINAMINE project? Tell us about your role as a Work Package leader. 

What inspires me most about the DINAMINE project is its holistic view on interfacing hardware technology and digital innovation on the same platform to provide practical solutions to the mines. Mine sites have usually a set of sensors installed but these are mostly working as independent units but making them all talk synergistically to come up with data that can help optimize operations, enhance sustainability and improve resource management benefitting mines will be a very rewarding outcome of the project, and I am excited to have this concept materialized by DINAMINE team. One of the most exciting aspects of this project is directly engaging with mining personnels, understanding operational challenges, environmental impacts and improvements that can be brought by implementing the desired practical solutions. Furthermore, learning about the modelling techniques being used in MPM development and data exchange protocols is a new and exciting area for me. My interaction with the personnels from mining and consultant companies during recent conferences made me realize that the kind of systems/solutions being developed in DINAMINE project leading to digitalization of mines are of great value. We at SPECTRAL are managing WP4, which has a main task of the development of Mineral Processing Model (MPM), one of the main modules in the project. The activity is based on the involvement of a multidisciplinary team including digital technology experts, engineers and sensing specialists. As a Work Package leader, I am working towards facilitating collaboration between different team members involved, so that with the diverse backgrounds and submodules, we work together to create a system which is innovative and useful for the project and potential future end users. On an internal level within SPECTRAL, I am also managing the engineering team, overviewing the whole current development phase of the LIBS sensors and their implementation later at the mine sites. 

 Can you walk us through the work already completed and planned in your Work Package? 

The activities in WP4 focus on two key tasks: the development of the MPM module and in-pit rock characterization by LIBS sensor. For the MPM module, the work includes the modeling of real-time and cuasi-real-time data from the sensors installed at multiple points in the mine and processing plant. The WP4 team has established a scheme for retrieving input data from sensors and sharing modelled output data within the module and across the project. While WSE is currently installing sensors and SPI is working on the development and implementation of LIBS sensors to monitor elemental concentrations, the team started working to analyze the existing historical data from the pilot sites, ensuring the readiness of a preliminary algorithm for when real-time sensor data starts becoming available. This analysis has allowed WP4 to complete initial modeling activities, using historical data to create baseline algorithms for future models based on real sensor data. These algorithms will be refined and adapted once real data is available. As of now, this modeling phase has already led to a better understanding of the pilot sites, their processes and operational parameters, highlighting the significant contributing factors. On the sensor technology side, the conveyor belt sensors, for the analysis of input material streams, have been fully assembled. The LIBS laboratory analyzer, which will be deployed at the FELMICA lab for the product analysis, has been designed, and its assembly will be started soon. Once the systems are fully operational, the next phase involves calibrating these sensors and shipping them to the pilot sites for installation. These sensors are planned to be installed in March 2025. Regarding the in-pit characterization of rocks, FELMICA and SPI, have designed the implementation plan, where FELMICA will take care of the onsite preparations. SPI will deploy its LIBS sensor, which will be moved to different types of materials piled in different areas. The outcome of these measurements will be classification of the material into low, medium and high grade and waste rock, to help mines ensure selective transportation. 

How do you envision the future of online material characterization?  

The possibility of online material characterization is a game-changer for mine sites. It enables end users to obtain results within minutes, compared to the hours or even days required by traditional or standard methods of analysis. This rapid turnaround significantly enables quick decision-making, which is a crucial step in optimizing mining processes. While I have highlighted the temporal advantage of online characterization, some of my recent visits to mine sites have offered me new perspectives and insights that I would like to share as concrete examples for our readers. Conversations with mine operators gave me understanding that the mines and plants have an urgent need for real-time analysis of raw materials, process optimization, and monitoring of key parameters such as sulfuric acid consumption or grades. For instance, in a wet processing plant where lixiviation is performed to extract copper from ore, the raw material is crushed and, after multiple crushing stages, stored as a pile for chemical separation using sulfuric acid leaching. If the final crushed material leaving the conveyor belt could be classified based on its elemental content using a LIBS sensor, it would allow operators to segregate the material into low, medium, and high-grade categories. This classification could optimize sulfuric acid consumption. Similarly, material with a higher calcium content would require more sulfuric acid, so early detection would enable adjustments to prevent unnecessary waste. Similarly, for FELMICA, where lithium is the desired element and iron is a contaminant, processing a batch with higher iron content is not used and goes to waste once analyzed by lab after hours of analysis. This leads to a waste of resources. In such a situation, an online characterization method with an alarm for high iron content would allow operators to make timely decisions and conserve resources. In other scenarios, the use of LIBS technology for applications like mine face mapping, drill core scanning, or in-situ exploration offers remarkable advantages. These tasks can now be performed with greater speed and precision, significantly reducing downtime and enabling more effective decision-making. It must be taken into consideration that as a traditional practice the samples are taken to the lab but for online characterization the lab (i.e. sensor) is taken to the sample in the field. This shift from lab-based to field-based analyses reflects a growing demand for practicality.  However, for successful implementation, it is crucial that the sensor is thoroughly trained to understand the material types and their expected variations. This enables the system to predict results with greater accuracy and reliability. 

 What outcomes are you aiming for with DINAMINE? 

The first outcome that comes to mind is DINAMINE’s development of a consolidated tool for mine digitization. By integrating advanced hardware and digital technologies, this tool represents a significant step forward for the mining industry, transitioning from manual and standalone practices to a more holistic, efficient and sustainable approach. DINAMINE’s focus on real-time sensing and resource monitoring should result in such a simplistic way that it provides a streamlined solution that is user-friendly and easy to implement. Secondly, the study of the pilot sites and collected and modelled data should give an indication of the critical spots of energy consumption or any and potential inefficiencies in resource management. This insight will allow for improvements in operations performance. Another key outcome of the DINAMINE project will be the development of LIBS sensors and their operation in real and rough mine environment. The possibility of real time measurements will be a great outcome regarding the online measurement demonstration of the material.