Neutron Imaging and Learning Algorithms: New Perspectives in Cultural Heritage Applications.

Recently, learning algorithms such as Convolutional Neural Networks have been successfully applied in different stages of data processing from the acquisition to the data analysis in the imaging context. The aim of these algorithms is the dimensionality of data reduction and the computational effort, to find benchmarks and extract features, to improve the resolution, and reproducibility performances of the imaging data. Currently, no Neutron Imaging combined with learning algorithms was applied on cultural heritage domain, but future applications could help to solve challenges of this research field. Here, a review of pioneering works to exploit the use of Machine Learning and Deep Learning models applied to X-ray imaging and Neutron Imaging data processing is reported, spanning from biomedicine, microbiology, and materials science to give new perspectives on future cultural heritage applications.

Hydrogen Detection Limits and Instrument Sensitivity of High-Resolution Broadband Neutron Spectrometers.

The limits of detection (LOD) and quantitation (LOQ) in the mass domain, for broadband vibrational spectroscopy with neutrons on the TOSCA spectrometer at the ISIS Pulsed Neutron and Muon Source (UK), have been studied. The well-known 3σ and 10σ approaches are used through a specifically developed analytical procedure that is based on the calculation of the integrated spectral intensities in selected energy-transfer ranges, as a function of mass of standard reference materials and calibrants, such as ZrH2, 2,5-diiodothiophene, and low-density polyethylene. The analysis shows that the blank, that is, the instrument setup without the analyte, plays a critical role in the measurement performance, especially for small specimen quantities. The results point that TOSCA enables detection of 128 µmol (LODH) and quantitation of 428 µmol (LOQH) of elemental hydrogen analytes in ZrH2. The determined values for this and other standards allow for the assessment of the calibration curve design and instrument sensitivity and define a method to be used for inelastic neutron scattering spectrometers such as TOSCA, or VESPA, the new beamline under construction at the European Spallation Source in Lund (Sweden).

Soluble Salts Quantitative Characterization and Thermodynamic Modeling on Roman Bricks to Assess the Origin of Their Formation.

The environmental weathering and the formation of efflorescences on the brick walls are studied at the "Casa di Diana" Mithraeum at Ostia Antica archaeological site. Previous studies on subsoil, bedrock, hydrological systems and environmental conditions, and new ion chromatography analysis combined with ECOS-RUNSALT and Medusa-Hydra thermodynamic modelling software, had allowed us to identify the subsoil contamination related to soluble salts. The atmospheric acidic gases, CO2 and SO2, are determined as the main salt weathering species. A dry deposition after a subsequent hydration action from the shallow freshwater aquifer that reaches up to 1 m on the walls is identified as the mechanism of salt formation. An evaluation of potential sources such as the nearby Fiumicino airport, CO2-rich gases inputs from fumaroles and CO2 inputs was also debated. The risk level of contamination the surfaces of the materials should be considered mildly/very polluted with a medium/high risk of hygroscopic moisture due to the high concentration of sulphates.

Chemometric Tools to Point Out Benchmarks and Chromophores in Pigments through Spectroscopic Data Analyses.

Spectral preprocessing data and chemometric tools are analytical methods widely applied in several scientific contexts i.e., in archaeometric applications. A systematic classification of natural powdered pigments of organic and inorganic nature through Principal Component Analysis with a multi-instruments spectroscopic study is presented here. The methodology allows the access to elementary and molecular unique benchmarks to guide and speed up the identification of an unknown pigment and its recipe. This study is conducted on a set of 48 powdered pigments and tested on a real-case sample from the wall painting in S. Maria Delle Palate di Tusa (Messina, Italy). Four spectroscopic techniques (X-ray Fluorescence, Raman, Attenuated Total Reflectance and Total Reflectance Infrared Spectroscopies) and six different spectrometers are tested to evaluate the impact of different setups. The novelty of the work is to use a systematic approach on this initial dataset using the entire spectroscopic energy range without any windows selection to solve problems linked with the manipulation of large analytes/materials to find an indistinct property of one or more spectral bands opening new frontiers in the dataset spectroscopic analyses.

A Python Algorithm to Analyze Inelastic Neutron Scattering Spectra Based on the y-Scale Formalism.

This paper presents a Python-based algorithm, named INSCorNorm, to correct the inelastic neutron scattering (INS) spectra for both sample and container self-shielding and to normalize the experimental spectral intensity to an absolute physical scale (barn/energy unit) facilitating the comparison with computer simulations and interpretation. The algorithm is benchmarked against INS measurements of ZrH2 performed on the TOSCA spectrometer at the ISIS Facility. We also apply the algorithm to the INS spectra from l-lysine, a system of broad interest in biology and medicine, and we discuss how corrected INS data provide an experimental benchmark for theoretical calculations of nuclear anisotropic displacement parameters in molecular systems. The total neutron sample cross section to use for the self-shielding corrections is discussed, as well as the best approach to derive experimentally the cross section at the VESUVIO spectrometer, together with the experimental value of the hydrogen nuclear mean kinetic energy, ⟨Ek⟩. The algorithm is made available to the neutron user community within the MANTID software.

Neutrons for Cultural Heritage-Techniques, Sensors, and Detection.

Advances in research in Cultural Heritage see increasing application of a multidisciplinary approach and the combined use of physical and chemical characterization of artefacts that can be used to define their structure and their state of conservation, also providing valuable information in selecting the most suitable microclimatic conditions for the exhibition environment. This approach provides a platform for a synergic collaboration amongst researchers, restorers, conservators, and archaeologists. Existing state-of-the-art technologies for neutron-based methods are currently being applied to the study of objects of historical and cultural interest in several neutron-beam facilities around the world. Such techniques are non-invasive and non-destructive and are, therefore, ideal to provide structural information about artefacts, such as their composition, presence of alterations due to the environmental conditions, inclusions, structure of the bulk, manufacturing techniques, and elemental composition, which provide an overall fingerprint of the object's characteristics, thanks to the nature of the interaction of neutrons with matter. Here, we present an overview of the main neutron methods for the characterization of materials of interest in Cultural Heritage and we provide a brief introduction to the sensors and detectors that are used in this framework. We conclude with some case studies underlining the impact of these applications in different archaeological and historical contexts.

High Frequency Data Acquisition System for Modelling the Impact of Visitors on the Thermo-Hygrometric Conditions of Archaeological Sites: A Casa di Diana (Ostia Antica, Italy) Case Study.

The characterization of the microclimatic conditions is fundamental for the preventive conservation of archaeological sites. In this context, the identification of the factors that influence the thermo-hygrometric equilibrium is key to determine the causes of cultural heritage deterioration. In this work, a characterization of the thermo-hygrometric conditions of Casa di Diana (Ostia Antica, Italy) is carried out analyzing the data of temperature and relative humidity recorded by a system of sensors with high monitoring frequency. Sensors are installed in parallel, calibrated and synchronized with a microcontroller. A data set of 793,620 data, arranged in a matrix with 66,135 rows and 12 columns, was used. Furthermore, the influence of human impact (visitors) is evaluated through a multiple linear regression model and a logistic regression model. The visitors do not affect the environmental humidity as it is very high and constant all the year. The results show a significant influence of the visitors in the upset of the thermal balance. When a tourist guide takes place, the probability that the hourly temperature variation reaches values higher than its monthly average is 10.64 times higher than it remains equal or less to its monthly average. The analysis of the regression residuals shows the influence of outdoor climatic variables in the thermal balance, such as solar radiation or ventilation.

Combination of in situ spectroscopy and chemometric techniques to discriminate different types of Roman bricks and the influence of microclimate environment.

Red and yellow bricks are the wall-building materials generally used in Roman masonries. The reasons for the different coloration are not always understood, causing loss of crucial information both for the conservation and for the archaeological knowledge of the cultural sites. In this work, a combination of in situ analyses, employing portable Raman spectroscopy and handheld energy dispersive X-ray fluorescence (HH-ED-XRF) spectroscopy along with chemometric analysis, was carried out on ancient Roman bricks of the "Casa di Diana" building (Ostia Antica, Italy-130 CE). Specifically, the compounds and the characteristic elements, which describe each type of brick (red and yellow), were studied avoiding destructive or invasive sampling. The molecular analysis allowed us to identify the major and minor compounds that characterise the bricks (anatase, hematite, quartz, calcite and silicates). However, the elemental analysis gave more useful information. Thus, the complex HH-ED-XRF data matrix generated was treated by a specific principal component analysis (PCA) to identify behavioural differences of the coloured bricks. The results revealed that Ca and Fe are the discriminatory elements for the two types of bricks. The PCA outcomes suggest that the contribution of certain elements is different in the bricks (mainly Ca, P, Sr, As and S, for yellow bricks), which could indicate different raw materials. Even among bricks with the same red colour (Al, Si, Ti, K, Fe, Cr, Mn, Ni, Zn, Cu, Rb and Zr, seemed to be the elements linked to raw materials), as a function of the surface impacts (orientation and microclimate affect the salts' formation), a distinction was made. Furthermore, the PCA pointed out that the yellow bricks are those more affected by decaying processes (related with Ca, P and S), complying with the Raman spectroscopy results in which the efflorescences (gypsum) affect especially the surface of these types of bricks.