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About

About

I was born in Lisbon, Portugal, in 1983 and graduated from Faculdade de Ciências e Tecnologia Universidade Nova de Lisboa (FCT-UNL) in Physics Engineering in 2006. My undergraduate research consisted in developing and assembly of a specialized X-ray fluorescence spectrometer. This work lead to a Master in Physics Engineering (FCT-UNL, 2007) and a PhD in Atomic Physics (FCT-UNL, 2011) entitled: “Measurement of lead concentration in biological tissues by atomic spectroscopy techniques”.

In 2012, I moved to Albany (New York, USA) as a Postdoc in Analytical Chemistry, to work at the Trace Elements group, Wadsworth Center New York State Department of Health. In the same year I transitioned to a Research Scientist position and became supervisor of the X-ray lab. Here I participated in multiple projects concerning biomonitoring and environmental analysis of trace elements in several matrices (food, cosmetics, medicines, consumer products, human tissues and body fluids) using analytical techniques based on atomic spectrometry, including synchrotron radiation at the Cornell University. I also spent 2 years as a Research Assistant Professor at the University at Albany, State University of New York – School of Public Health, Department of Environmental Health Sciences.

In 2016 I decided to shift my research focus from atomic to nuclear radiation.  I moved to Porto, Portugal, and I am currently working at INESC-TEC developing fiber optic sensors to detect the presence of Radon, a radioactive element, in marine environments.

Interest
Topics
Details

Details

  • Name

    Diana Filipa Guimarães
  • Role

    Assistant Researcher
  • Since

    07th November 2016
  • Nationality

    Portugal
  • Centre

    Applied Photonics
  • Contacts

    +351220402301
    diana.f.guimaraes@inesctec.pt
006
Publications

2025

Improving LIBS-based mineral identification with Raman imaging and spectral knowledge distillation

Authors
Lopes, T; Cavaco, R; Capela, D; Dias, F; Teixeira, J; Monteiro, CS; Lima, A; Guimaraes, D; Jorge, PAS; Silva, NA;

Publication
TALANTA

Abstract
Combining data from different sensing modalities has been a promising research topic for building better and more reliable data-driven models. In particular, it is known that multimodal spectral imaging can improve the analytical capabilities of standalone spectroscopy techniques through fusion, hyphenation, or knowledge distillation techniques. In this manuscript, we focus on the latter, exploring how one can increase the performance of a Laser-induced Breakdown Spectroscopy system for mineral classification problems using additional spectral imaging techniques. Specifically, focusing on a scenario where Raman spectroscopy delivers accurate mineral classification performance, we show how to deploy a knowledge distillation pipeline where Raman spectroscopy may act as an autonomous supervisor for LIBS. For a case study concerning a challenging Li-bearing mineral identification of spodumene and petalite, our results demonstrate the advantages of this method in improving the performance of a single-technique system. LIBS trained with labels obtained by Raman presents an enhanced classification performance. Furthermore, leveraging the interpretability of the model deployed, the workflow opens opportunities for the deployment of assisted feature discovery pipelines, which may impact future academic and industrial applications.

2025

Enhancing spectral imaging with multi-condition image fusion

Authors
Teixeira, J; Lopes, T; Capela, D; Monteiro, CS; Guimarães, D; Lima, A; Jorge, PAS; Silva, NA;

Publication
Scientific Reports

Abstract

2024

From sensor fusion to knowledge distillation in collaborative LIBS and hyperspectral imaging for mineral identification

Authors
Lopes, T; Capela, D; Guimaraes, D; Ferreira, MFS; Jorge, PAS; Silva, NA;

Publication
SCIENTIFIC REPORTS

Abstract
Multimodal spectral imaging offers a unique approach to the enhancement of the analytical capabilities of standalone spectroscopy techniques by combining information gathered from distinct sources. In this manuscript, we explore such opportunities by focusing on two well-known spectral imaging techniques, namely laser-induced breakdown spectroscopy, and hyperspectral imaging, and explore the opportunities of collaborative sensing for a case study involving mineral identification. In specific, the work builds upon two distinct approaches: a traditional sensor fusion, where we strive to increase the information gathered by including information from the two modalities; and a knowledge distillation approach, where the Laser Induced Breakdown spectroscopy is used as an autonomous supervisor for hyperspectral imaging. Our results show the potential of both approaches in enhancing the performance over a single modality sensing system, highlighting, in particular, the advantages of the knowledge distillation framework in maximizing the potential benefits of using multiple techniques to build more interpretable models and paving for industrial applications.

2024

Identification of Relevant Spectral Ranges in Laser-Induced Breakdown Spectroscopy Imaging Using the Fourier Space

Authors
Lopes, T; Capela, D; Ferreira, MFS; Guimaraes, D; Jorge, PAS; Silva, NA;

Publication
APPLIED SPECTROSCOPY

Abstract
Laser-induced breakdown spectroscopy (LIBS) imaging has now a well-established position in the subject of spectral imaging, leveraging multi-element detection capabilities and fast acquisition rates to support applications both at academic and technological levels. In current applications, the standard processing pipeline to explore LIBS imaging data sets revolves around identifying an element that is suspected to exist within the sample and generating maps based on its characteristic emission lines. Such an approach requires some previous expert knowledge both on the technique and on the sample side, which hinders a wider and more transparent accessibility of the LIBS imaging technique by non-specialists. To address this issue, techniques based on visual analysis or peak finding algorithms are applied on the average or maximum spectrum, and may be employed for automatically identifying relevant spectral regions. Yet, maps containing relevant information may often be discarded due to low signal-to-noise ratios or interference with other elements. In this context, this work presents an agnostic processing pipeline based on a spatial information ratio metric that is computed in the Fourier space for each wavelength and that allows for the identification of relevant spectral ranges in LIBS. The results suggest a more robust and streamlined approach to feature extraction in LIBS imaging compared with traditional inspection of the spectra, which can introduce novel opportunities not only for spectral data analysis but also in the field of data compression.

2024

Analysing Heavy Metal Contaminants in Wood Wastes using Laser-Induced Breakdown Spectroscopy (LIBS)

Authors
Capela, D; Lopesa, T; Ferreira, MFS; Magalhaes, P; Jorge, PAS; Silva, NA; Guimaraes, D;

Publication
OPTICAL SENSING AND DETECTION VIII

Abstract
Circular economy policies and recycling play a pivotal role in fostering sustainable models for the wood industry capable of reducing the environmental impact of our consumption patterns. The production of Particleboard is a good example of industry that uses high quantities of recycled wood. However, it poses risks since wood often have contaminants that compromise compliance of safety standards. Thus, it is necessary to develop methodologies for rapid analysis of chemical contaminants in wood wastes that allow easy detection of these elements. In this work, the capability of Laser-induced breakdown spectroscopy (LIBS) to detect a set of heavy metals in wood samples was explored. Some advantages of this technique, such as portability, minimal to no sample preparation, and quick analysis are characteristics that make this method one of the most suitable for this purpose of analysis. In the majority of cases, the contamination comes from the pigments used in paints, varnishes, or coatings. Titanium (Ti) e.g. is a common element in white pigments and Chromium (Cr) in red and green pigments. To ensure the presence or absence of Cr and Ti, a set of 3 lines was analysed. The results revealed the presence of these elements and that 30% of the samples seem to be highly contaminated. The LIBS technique proved to be a powerful methodogy for decision-making purposes.

Supervised
thesis

2023

Laser-induced breakdown spectroscopy: Innovative software tools to bridge the gap between science and technology

Author
Diana Faria Capela

Institution
INESCTEC