Integrated micro X-ray fluorescence and chemometric analysis for printed circuit boards recycling

A novel approach, based on micro X-ray fluorescence (μXRF), was developed to define an efficient and fast automatic recognition procedure finalized to detect and topologically assess the presence of the different elements in waste electrical and electronic equipment (WEEE). More specifically, selected end-of-life (EOL) iPhone printed circuit boards (PCB) were investigated, whose technological improvement during time, can dramatically influence the recycling strategies (i.e. presence of different electronic components, in terms of size, shape, disposition and related elemental content). The implemented μXRF-based techniques allow to preliminary set up simple and fast quality control strategies based on the full recognition and characterization of precious and rare earth elements as detected inside the electronic boards. Furthermore, the proposed approach allows to identify the presence and the physical-chemical attributes of the other materials (i.e. mainly polymers), influencing the further physical-mechanical processing steps addressed to realize a pre-concentration of the valuable elements inside the PCB milled fractions, before the final chemical recovery

END OF LIFE MANAGEMENT OF ELECTRONIC WASTE

Electronic products are becoming obsolete at a very high rate due to rapid changes in consumer demand and technological advancements. However, on other hand End-of-Life (EOL) management of electronic products is not effectively approached while these products offer huge opportunities for effective recycling. In this context, this thesis has highlighted the current practices and issues related to EOL management of electronic products focusing on their different material compositions, the uses of their raw materials in the circular economy perspective. The thesis proposes the introduction of digital technologies into the recycling process to improve efficiency. More specifically, this thesis has focused on the corona electrostatic separation process and the improvement of efficiency based on the simulation of the particle trajectories to identify the most effective parameters. Thus, in this frame, a numerical model to predict the particle trajectories in a corona electrostatic separator is developed using COMSOL Multiphysics and MATLAB software and validated with experimental trials. The recycling of electronic waste is becoming challenging due to its diverse and constantly changing material composition. In this regard, this thesis illustrates the use of non-destructive visible near-infrared hyperspectral imaging (VNIR-HSI) technique to identify material accurately; the effectiveness of VNIR-HSI is demonstrated through an experimental campaign combined with machine learning models, such as Support Vector Machine, K-Nearest Neighbors and Neural Network.Nonostante i prodotti elettronici diventino obsoleti ad un ritmo molto elevato, a causa dei rapidi cambiamenti nella domanda dei consumatori e dei progressi tecnologici, la gestione del loro fine vita (End-of-Life (EOL)) non viene affrontata in modo efficace benché offra, invece, grandi opportunità di riciclo. In questo contesto, questa tesi ha evidenziato le attuali pratiche e problematiche relative alla gestione del fine vita dei prodotti elettronici concentrandosi sulla loro diversa composizione, l’utilizzo delle materie prime seconde ricavabili in una prospettiva di economia circolare. La tesi propone l’introduzione di tecnologie digitali nel processo di riciclo per migliorarne l'efficienza. In particolare, questa tesi si è concentrata sul processo di separazione elettrostatica a corona e sul miglioramento dell'efficienza grazie alla simulazione delle traiettorie delle particelle per identificare i parametri più efficaci. Pertanto, in questo studio, utilizzando i software COMSOL Multiphysics e MATLAB, è stato sviluppato un modello numerico per prevedere le traiettorie delle particelle in un separatore elettrostatico a corona; il modello è stato poi validato con prove sperimentali. Il riciclo dei rifiuti elettronici sta diventando sempre più complesso a causa della presenza di mix di materiali diversificati e in continua evoluzione. A questo proposito, la tecnologia di visione iperspettrale non distruttiva basata su lunghezze d’onda nel visibile e nel vicino infrarosso (VNIR-HSI) è stata utilizzata in questo lavoro di tesi per identificare il materiale in modo preciso; l'efficacia di VNIR-HSI, combinato con modelli di apprendimento automatico, come la Support Vector Machine, K-Nearest Neighbors e Neural Network, viene dimostrata attraverso una campagna sperimentale

Hierarchical modelling for recycling-oriented classification of shredded spent flat monitor products based on hyperspectral imaging

The number of flat monitors from televisions, notebooks and tablets has increased dramatically in recent years, thus resulting in a corresponding rise in Waste from Electrical and Electronic Equipment (WEEE). This fact is linked to the production of new high-performance electronic devices. Taking into account a future volume growth trend of WEEE, the implementation of adequate recycling architectures embedding recognition/classification logics to handle the collected WEEE physical-chemical at-tributes, is thus necessary. These integrated hardware and software architectures should be efficient, reliable, low cost, and capable of performing detection/control actions to assess: i) WEEE composition and ii) physical-chemical attributes of the resulting recovered flow streams. This information is fundamental in setting up and implementing appropriate recycling actions. In this study, a hierarchical classification modelling approach, based on Near InfraRed (NIR)-Hyperspectral Imaging (HSI), was carried out. More in detail, a 3-step hierarchical modelling procedure was designed, implemented and set up in order to recognize different materials present in a specific WEEE stream: End-of-Life (EoL) shredded monitors and flat screens. By adopting the proposed approach, different categories are correctly recognized. The results obtained showed how the proposed approach not only allows the set up of a “one shot” quality control system, but also contributes towards improving the sorting process

The negative index of refraction demystified

We study electromagnetic wave propagation in mediums in which the effective relative permittivity and the effective relative permeability are allowed to take any value in the upper half of the complex plane. A general condition is derived for the phase velocity to be oppositely directed to the power flow. That extends the recently studied case of propagation in mediums for which the relative permittivity and relative permeability are both simultaneously negative, to include dissipation as well. An illustrative case study demonstrates that in general the spectrum divides into five distinct regions.Comment: 5 pages, 4 figure

Computer-aided optical characterization and sensing applications: from minerals to waste

Optical based characterization techniques and related analytical methodologies, originally utilized in the mineral sector, can be profitably applied to solid waste streams products as resulting from different recycling processes. This approach, when supported by digital tools allows to perform a full characterization of compositional and textural attributes of the different particulate solids constituting the waste flow streams. To reach this goal specific physical-chemical attributes must be collected, analyzed and processed in order to define, according to market requirements, specific classes of quality to assume as reference to define optimal processing strategies. Computer-assisted optical characterization, coupled with hyperspectral sensing devices and embedding recognition/classification logics, can contribute to reach these goals, dramatically reducing analytical time and costs. In this work an example of this “transfer approach”, from minerals to waste, is presented, analyzed and discussed, with reference to a porphyry copper ore sample and a WEEE product

A Versatile Sensor Data Processing Framework for Resource Technology

Die Erweiterung experimenteller Infrastrukturen um neuartige Sensor eröffnen die Möglichkeit, qualitativ neuartige Erkenntnisse zu gewinnen. Um diese Informationen vollständig zu erschließen ist ein Abdecken der gesamten Verarbeitungskette von der Datenauslese bis zu anwendungsbezogenen Auswertung erforderlich. Eine Erweiterung bestehender wissenschaftlicher Instrumente beinhaltet die strukturelle und zeitbezogene Integration der neuen Sensordaten in das Bestandssystem. Das hier vorgestellte Framework bietet durch seinen flexiblen Ansatz das Potenzial, unterschiedliche Sensortypen in unterschiedliche, leistungsfähige Plattformen zu integrieren. Zwei unterschiedliche Integrationsansätze zeigen die Flexibilität dieses Ansatzes, wobei einer auf die Steigerung der Sensitivität einer Anlage zur Sekundärionenmassenspektroskopie und der andere auf die Bereitstellung eines Prototypen zur Untersuchung von Rezyklaten ausgerichtet ist. Die sehr unterschiedlichen Hardwarevoraussetzungen und Anforderungen der Anwendung bildeten die Basis zur Entwicklung eines flexiblen Softwareframeworks. Um komplexe und leistungsfähige Applikationsbausteine bereitzustellen wurde eine Softwaretechnologie entwickelt, die modulare Pipelinestrukturen mit Sensor- und Ausgabeschnittstellen sowie einer Wissensbasis mit entsprechenden Konfigurations- und Verarbeitungsmodulen kombiniert.:1. Introduction 2. Hardware Architecture and Application Background 3. Software Concept 4. Experimental Results 5. Conclusion and OutlookNovel sensors with the ability to collect qualitatively new information offer the potential to improve experimental infrastructure and methods in the field of research technology. In order to get full access to this information, the entire range from detector readout data transfer over proper data and knowledge models up to complex application functions has to be covered. The extension of existing scientific instruments comprises the integration of diverse sensor information into existing hardware, based on the expansion of pivotal event schemes and data models. Due to its flexible approach, the proposed framework has the potential to integrate additional sensor types and offers migration capabilities to high-performance computing platforms. Two different implementation setups prove the flexibility of this approach, one extending the material analyzing capabilities of a secondary ion mass spectrometry device, the other implementing a functional prototype setup for the online analysis of recyclate. Both setups can be regarded as two complementary parts of a highly topical and ground-breaking unique scientific application field. The requirements and possibilities resulting from different hardware concepts on one hand and diverse application fields on the other hand are the basis for the development of a versatile software framework. In order to support complex and efficient application functions under heterogeneous and flexible technical conditions, a software technology is proposed that offers modular processing pipeline structures with internal and external data interfaces backed by a knowledge base with respective configuration and conclusion mechanisms.:1. Introduction 2. Hardware Architecture and Application Background 3. Software Concept 4. Experimental Results 5. Conclusion and Outloo