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Editorial

Advances in Analytical Methods for Cultural Heritage

by
Federica Pozzi
1,* and
Catherine H. Stephens
2,*
1
Centro per la Conservazione ed il Restauro dei Beni Culturali “La Venaria Reale”, Via XX Settembre 18, 10078 Venaria Reale (Turin), Italy
2
The Museum of Modern Art, 11 West 53rd Street, New York, NY 10019, USA
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2024, 14(17), 7587; https://doi.org/10.3390/app14177587
Submission received: 13 August 2024 / Accepted: 21 August 2024 / Published: 27 August 2024
(This article belongs to the Special Issue Advances in Analytical Methods for Cultural Heritage)
Conservation science, also referred to as heritage science or cultural heritage science, is a unique field of scientific inquiry that addresses specific questions derived from the world of art, archaeology, architecture, and archives. Here, analytical methods strive to shed light on artistic practice and technologies, preserve cultural heritage in controlled or uncontrolled environments, or determine ways to extend the lifetime of an art object. The field merges concepts from myriad other technical fields, including―but not limited to―anthropology, archaeometry, engineering, chemistry, physics, geology, biology, metallurgy, materials science, computer science, art history, and studio art. Focus areas have included investigating the composition of art objects, developing analytical methods that require little to no physical sampling, using portable equipment that permits analysis of artifacts in situ, inventing instrumental devices to address gaps in our understanding of the behavior of materials found in art, or collaborating with scientists outside the field to gain access to cutting-edge instrumentation and knowledge to answer questions pertaining to cultural heritage.
The earliest studies in the field involved the implementation of existing technologies to study art. One example dates to the late 1890s, just after X-rays were discovered, when a radiographic image of a painting was taken [1]. In the intervening years, countless techniques originally developed for other purposes have been applied to the investigation of art materials and objects. Over time, significant advances in the analytical world have enhanced the field’s understanding of artists’ materials and methods, the environment, and the impact of time on cultural heritage. For instance, several traditional pointwise techniques, including X-ray fluorescence (XRF) spectroscopy, fiber optics reflectance spectroscopy (FORS), and Fourier-transform infrared spectroscopy (FTIR), have recently crossed the frontier from single location analysis into the world of chemical imaging, providing cultural heritage professionals with valuable means to map the spatial distribution of a wide variety of organic and inorganic materials across a given surface [2,3,4]. Thanks to the development of automated scanning frames and advanced sensors for ultra-sensitive detection on a macroscopic and microscopic scale, these techniques have also yielded high-resolution data with progressively reduced acquisition times. The resulting information-rich visual output may serve a multifold purpose in terms of materials identification, documentation of an object’s preservation state, enhancement of its relevance within a collection, and enjoyment by the public. Instrument manufacturers and research groups worldwide have also successfully combined multiple analytical tools within one instrumental unit, enabling the investigation of complex artifacts by delivering multimodal datasets from cumulative acquisition campaigns. Extant examples of these hyphenated techniques that have found increasing application in the cultural heritage world include XRF/reflectance imaging spectroscopy (RIS), XRF/X-ray diffractometry (XRD), XRD/Raman spectroscopy, and scanning electron microscopy (SEM)/Raman spectroscopy [5,6]. In addition, significant advances in the analysis of organic residues belonging to different molecular classes using proteomics, lipidomics, and glycomics have allowed researchers to safely remove trace-level material from museum objects, resolve complex mixtures, and achieve detailed specimen characterization at the molecular level [7].
Non-destructive analytical methodologies are ideal for collecting data while preserving the physical integrity of irreplaceable objects. In addition to X-radiography, XRF, and FORS―techniques inherently non-invasive―other non-sampling techniques, including hyperspectral imaging (HSI), have been adapted to understand artistic materials and methods [8]. However, myriad questions, including the organic composition of an artifact, the crystalline structure of a solid, or the degradation state of a polymer, often require sampling, which may prove undesirable or challenging. Enhancements in the spatial resolution or sensitivities in detectors through the years have led to micro-scale analytical techniques, including FTIR, Raman, and XRD, opening up these methods for use when sampling is allowed as the sample size required for measurement is microscopic. The development of ambient ionization techniques has permitted certain objects to be characterized without sampling at all [9,10]. Sorbent sampling methods have been harnessed to sample the airspace around art, identifying chemicals and pollutants harmful to collections [11].
Another compelling issue relates to accessibility, which in the field of cultural heritage research manifests in several forms. One way to increase accessibility is the optimization of analytical tools to create digital twins, providing virtual access to physically inaccessible sites and facilitating the preservation of invaluable objects [12]. Another aspect to be considered, from a methodological point of view, is the need to access artifacts that cannot be removed from conservation studios, museum galleries, or storage: in this regard, the availability of movable, portable, and handheld equipment is crucial for in-situ analytical campaigns [13,14]. The microfade tester (MFT), one of the few true inventions in the field [15], has recently been redesigned improving its portability. Although these significant advances have led to the successful analysis of immovable or cumbersome heritage objects, certain types of instrumentation continue to be available in benchtop format only; therefore, developing portable equipment remains an ongoing area of opportunity for the field.
Collaborating with experts in other scientific areas has provided opportunities to harness technologies useful to the cultural heritage community. For instance, the Library of Congress (USA) worked with the National Aeronautics and Space Administration (NASA) to develop a method to mass deacidify books [16]. This concept was later augmented by digitization technologies when Yale University collaborated with the Xerox Corporation, allowing books to be scanned directly into the digital sphere [17]. A collaboration involving the use of high-throughput technology developed at The Dow Chemical Company made it possible to determine ideal solvent systems to clean paint films [18]. In Europe and the United States, the ever-increasing use of synchrotron radiation to aid technical studies, made possible by the implementation of shared facilities’ international access programs, has pushed the limits of micro-analysis, enhancing current scholarship in the fields of art and archaeology while prompting numerous exciting discoveries into the materials used by artists and studio practice [19,20].
Despite increasingly rapid advances in available technology and methodological approaches, day-to-day work in the cultural heritage arena poses a series of unique challenges that are yet to be satisfactorily fulfilled, owing mainly to the small population of scientists working in the field and their requirement to meet the needs of home institutions. Addressing research queries becomes more complex if considered in the context of the global challenges that affect the preservation and enjoyment of artifacts of archeological, historical, and artistic significance―such as climate change and environmental sustainability―prompting the need for answers based on a systematic scientific approach and the use of the most advanced digital and technological resources available today. Increasingly relevant, for instance, is the necessity to propose sustainable solutions for the display and storage of artwork that account for energy consumption [21]. Also, there is a critical need to balance safe access to cultural heritage with sustainable tourism; this stimulates reflections on how best to measure and define ideal housing and display conditions for each cultural artifact based on its material type. Conservation scientists whose work focuses on preventive conservation are currently tackling how best to address these issues.
Another area of significant effort in the field is integrating artificial intelligence (AI) and machine learning methodologies into currently adopted techniques, including macro-XRF (MA-XRF) and micro-computational tomography (micro-CT), to enhance spectral information by significantly improving detection limits, chemical sensitivity, and spatial resolution [22,23]. Using big data to predict the behavior of art over long periods of time is also an area ripe for inquiry [24]. As with the rest of the scientific community, finding applications in the field that harness the capabilities of AI and pattern recognition (PR) is a developing research area [25].
Systematic work focused on addressing applied conservation efforts is generally less frequent in the conservation science field. However, relevant publications in this area have involved, among other subjects, the synthesis of nanostructured gels and microemulsions with various formulations as green products for consolidation and cleaning [26]. In terms of monitoring and evaluating conservation interventions, several analytical methods can provide a snapshot of the object’s condition at a certain treatment stage; at present, however, no scientific tool can yield real-time information on the progress of interventions.
Ultimately, collaboration will remain a key aspect of cultural heritage research, from technological and methodological innovation to the technical study and conservation of artifacts. The development of collaborative programs, both in Europe and the United States, has created opportunities for smaller institutions without science laboratories or scientists on staff to access state-of-the-art analytical instrumentation and highly specialized expertise to carry out in-depth analysis at shared facilities or conduct scientific investigations of previously unexplored art objects [27,28]. Thanks to the availability of funding to support these activities within these same programs and the advent of miniaturized equipment, this growing model ensures both economic and environmental sustainability and logistical feasibility for the operators and users.
In this context, this Special Issue aims to illustrate relevant recent advances in the field of analytical methods for cultural heritage while addressing some of the outstanding gaps that have been identified over time. Topics covered include the optimization of various imaging technologies for enhanced materials identification in complex artifacts using neural networks and for the digitization of surface data from objects located in constrained environments; the implementation of a multi-analytical approach, featuring cutting-edge mass spectrometry-based proteomics and chromatographic methods, to shed new light on understudied African collections and contemporary art installations; a study of materials’ properties for possible incorporation in cleaning practice, as well as the implementation of analytical techniques and methodologies for the identification of degradation products within specific types of materials and for the evaluation of conservation interventions; and a review of sampling techniques used in preventive conservation for the monitoring of indoor air quality in heritage environments.

Funding

No external funding was received to develop this manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Noble, P.; Verslype, I. The Use of X-radiographs in the Study of Paintings. Available online: https://countingvermeer.rkdstudies.nl/2-the-use-of-x-radiographs-in-the-study-of-paintings/ (accessed on 29 July 2024).
  2. Alfeld, M.; Janssens, A.; Dik, J.; de Nolf, W.; van der Snickt, G. Optimization of mobile scanning macro-XRF systems for the in situ investigation of historical paintings. J. Anal. At. Spectrom. 2011, 26, 899–909. [Google Scholar] [CrossRef]
  3. Cucci, C.; Delaney, J.K.; Picollo, M. Reflectance hyperspectral imaging for investigation of works of art: Old master paintings and illuminated manuscripts. Acc. Chem. Res. 2016, 49, 2070–2079. [Google Scholar] [CrossRef]
  4. Liu, G.L.; Kazarian, S.G. Recent advances and applications to cultural heritage using ATR-FTIR spectroscopy and ATR-FTIR spectroscopic imaging. Analyst 2022, 147, 1777–1797. [Google Scholar] [CrossRef] [PubMed]
  5. Occhipinti, M.; Alberti, R.; Parsani, T.; Dicorato, C.; Tirelli, P.; Gironda, M.; Tocchio, A.; Frizzi, T. IRIS: A novel integrated instrument for co-registered MA-XRF mapping and VNIR-SWIR hyperspectral imaging. X-Ray Spectrom. 2023. early view. [Google Scholar] [CrossRef]
  6. Moreau, R.; Calligaro, T.; Pichon, L.; Moignard, B.; Hermon, S.; Reiche, I. A multimodal scanner coupling XRF, UV–Vis–NIR photoluminescence and Vis-NIR-SWIR reflectance imaging spectroscopy for cultural heritage studies. X-Ray Spectrom. 2024, 53, 271–281. [Google Scholar] [CrossRef]
  7. Geddes da Filicaia, E.; Evershed, R.P.; Peggie, D.A. Review of recent advances on the use of mass spectrometry techniques for the study of organic materials in painted artworks. Anal. Chim. Acta 2023, 1246, 340575. [Google Scholar] [CrossRef]
  8. Delaney, J.K.; Dooley, K.A. Visible and infrared reflectance imaging spectroscopy of paintings and works on paper. In Analytical Chemistry for the Study of Paintings and the Detection of Forgeries; Colombini, M.P., Degano, I., Nevin, A., Eds.; Springer: Cham, Switzerland, 2022; pp. 115–132. [Google Scholar]
  9. Newsome, G.A.; Martin, K.M. Non-proximate Sampling and photoionization for damage-free mass spectrometric analysis of intact native American baskets. Anal. Chem. 2023, 95, 10695–10702. [Google Scholar] [CrossRef] [PubMed]
  10. Stephens, C.H.; Shrestha, B.; Morris, H.R.; Bier, M.E.; Whitmore, P.M.; Vertes, A. Minimally invasive monitoring of cellulose degradation by desorption electrospray ionization and laser ablation electrospray ionization mass spectrometry. Analyst 2010, 135, 2434–2444. [Google Scholar] [CrossRef] [PubMed]
  11. Grzywacz, C.M. Monitoring for Gaseous Pollutants in Museum Environments; Getty Publications: Los Angeles, CA, USA, 2006. [Google Scholar]
  12. Luther, W.; Baloian, N.; Biella, D.; Sacher, D. Digital twins and enabling technologies in museums and cultural heritage: An overview. Sensors 2023, 23, 1583. [Google Scholar] [CrossRef] [PubMed]
  13. Pozzi, F.; Rizzo, A.; Basso, E.; Angelin, E.M.; de Sá, S.F.; Cucci, C.; Picollo, M. Portable spectroscopy for cultural heritage: Applications and practical challenges. In Portable Spectroscopy and Spectrometry Volume 2: X-Ray, NMR and MS Instrumentation and Applications; Kammrath, B., Leary, P., Crocombe, R., Eds.; John Wiley & Sons: Hoboken, NJ, USA, 2021; pp. 501–524. [Google Scholar]
  14. Blumich, B.; Casanova, F.; Perlo, J.; Presciutti, F.; Anselmi, C.; Doherty, B. Noninvasive testing of art and cultural heritage by mobile NMR. Acc. Chem. Res. 2010, 43, 761–770. [Google Scholar] [CrossRef] [PubMed]
  15. Whitmore, P.M.; Pan, X.; Bailie, C. Predicting the fading of objects: Identification of fugitive colorants through direct nondestructive lightfastness measurements. J. Am. Inst. Conserv. 1999, 38, 395–409. [Google Scholar] [CrossRef]
  16. U.S. Congress, Office of Technology Assessment. Book Preservation Technologies, OTA0-375; U.S. Government Printing Office: Washington, DC, USA, 1988. [Google Scholar]
  17. Waters, D.J. From Microfilm to Digital Imagery; Commission on Preservation and Access: Washington, DC, USA, 1991. [Google Scholar]
  18. Ormsby, B.; Keefe, M.; Phenix, A.; von Aderkas, E.; Learner, T.; Tucker, C.; Kozak, C. Mineral spirits-based microemulsions: A novel cleaning system for painted surfaces. J. Am. Inst. Conserv. 2016, 55, 12–31. [Google Scholar] [CrossRef]
  19. Janssens, K.; Cotte, M. Using synchrotron radiation for characterization of cultural heritage materials. In Synchrotron Light Sources and Free-Electron Lasers; Jaeschke, E., Khan, S., Schneider, J., Hastings, J., Eds.; Springer: Cham, Switzerland, 2020; pp. 2457–2483. [Google Scholar]
  20. Broers, F.T.; Verslype, I.; Bossers, K.W.; Vanmeert, F.; Gonzalez, V.; Garrevoet, J.; Van Loon, A.; Van Duijn, E.; Krekeler, A.; De Keyser, N.; et al. Correlated X-ray fluorescence and ptychographic nano-tomography on Rembrandt’s The Night Watch reveals unknown lead “layer”. Sci. Adv. 2023, 9, eadj9394. [Google Scholar] [CrossRef] [PubMed]
  21. De Silva, M.; Henderson, J. Sustainability in conservation practice. J. Inst. Conserv. 2011, 34, 5–15. [Google Scholar] [CrossRef]
  22. Vermeulen, M.; McGeachy, A.; Xu, B.; Chopp, H.; Katsaggelos, A.; Meyers, R.; Alfed, M.; Walton, M. XRFast a new software package for processing of MA-XRF datasets using machine learning. J. Anal. At. Spectrom. 2022, 37, 2130–2143. [Google Scholar] [CrossRef]
  23. Parker, C.S.; Parsons, S.; Bandy, J.; Chapman, C.; Coppens, F.; Seales, W.B. From invisibility to readability: Recovering the ink of Herculaneum. PLoS ONE 2019, 14, e0215775. [Google Scholar] [CrossRef] [PubMed]
  24. Shimoni, M.; Croonenborghs, T.; Declercq, P.Y.; Drougkas, A.; Verstrynge, E.; Hocquet, F.P.; Hayen, R.; Van Balen, K. Advanced processing of remotely sensed big data for cultural heritage conservation. In Proceedings of the IGARSS 2019–2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 28 July—2 August 2019; pp. 5816–5819. [Google Scholar] [CrossRef]
  25. Fontanella, F.; Colace, F.; Molinara, M.; Di Freca, A.S.; Stanco, F. Pattern recognition and artificial intelligence techniques for cultural heritage. Pattern Recognit. Lett. 2020, 138, 23–29. [Google Scholar] [CrossRef]
  26. Chelazzi, D.; Baglioni, P. From nanoparticles to gels: A breakthrough in art conservation science. Langmuir 2023, 39, 10744–10755. [Google Scholar] [CrossRef] [PubMed]
  27. Miliani, C.; Rosi, F.; Brunetti, B.G.; Sgamellotti, A. In situ noninvasive study of artworks: The MOLAB multitechnique approach. Acc. Chem. Res. 2010, 43, 728–738. [Google Scholar] [CrossRef] [PubMed]
  28. Pozzi, F.; Basso, E. The Network Initiative for Conservation Science (NICS): A model of collaboration and resource sharing among neighbor museums. Herit. Sci. 2021, 9, 92. [Google Scholar] [CrossRef] [PubMed]
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Pozzi, F.; Stephens, C.H. Advances in Analytical Methods for Cultural Heritage. Appl. Sci. 2024, 14, 7587. https://doi.org/10.3390/app14177587

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Pozzi F, Stephens CH. Advances in Analytical Methods for Cultural Heritage. Applied Sciences. 2024; 14(17):7587. https://doi.org/10.3390/app14177587

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Pozzi, Federica, and Catherine H. Stephens. 2024. "Advances in Analytical Methods for Cultural Heritage" Applied Sciences 14, no. 17: 7587. https://doi.org/10.3390/app14177587

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