Stone porosity, wettability changes and other features detected by MRI and NMR relaxometry: a more than 15-year study

Efficacy of Chitosan-Carboxylic Acid Hydrogels in Reducing and Chelating Iron for the Removal of Rust from Stone Surface

In the field of stone conservation, the removal of iron stains is one of the most challenging issues due to the stability and low solubility of the ferrous species. In the present paper, three different chitosan-based hydrogels added with acetic, oxalic or citric acids are applied on different lithotypes, i.e., granite, travertine and marble, widely diffused in monumental heritages, and artificially stained by deposition of a rust dispersion. The reducing power of carboxylic acids is combined with the good chelating properties of chitosan to effectively remove rust from stone surfaces. As evidenced by colorimetry on three samples of each lithotype and confirmed by 1H-NMR relaxometry and SEM/EDS analyses, the chitosan-oxalic acid hydrogel shows the best performance and a single application of 24 h is enough to get a good restoration of the stone original features. Lastly, the chitosan-oxalic acid hydrogel performs well when a rusted iron grid is placed directly on the lithic surfaces to simulate a more realistic pollution. Current work in progress is devoted to finding better formulations for marble, which is the most challenging to clean or, with a different approach, to developing protective agents to prevent rust deposition.

Monitoring Water Absorption and Desorption in Untreated and Consolidated Tuff by a Non-Invasive Graphene-Based Humidity Sensor

A hybrid montmorillonite (MMT)/reduced graphene oxide (rGO) film was realised and used as a non-invasive sensor for the monitoring of water absorption and desorption in pristine and consolidated tuff stones. This film was obtained by casting from a water dispersion containing graphene oxide (GO), montmorillonite and ascorbic acid; then the GO component was thermo-chemically reduced and the ascorbic acid phase was removed by washing. The hybrid film showed electrical surface conductivity that varied linearly with the relative humidity, ranging from 2.3 × 10^-3 S in dry conditions to 5.0 × 10^-3 S at 100% RH. The sensor was applied onto tuff stone samples through the use of a high amorphous polyvinyl alcohol layer (HAVOH) adhesive, which guaranteed good water diffusion from the stone to the film and was tested during water capillary absorption and drying tests. Results show that the sensor is able to monitor water content changes in the stone, being potentially useful to evaluate the water absorption and desorption behaviour of porous samples both in laboratory environments and in situ.

Carbonaceous Materials Porosity Investigation in a Wet State by Low-Field NMR Relaxometry

The porosity of differently wetted carbonaceous material with disordered mesoporosity was investigated using low-field 1H NMR relaxometry. Spin−spin relaxation (relaxation time T2) was measured using the CPMG pulse sequence. We present a non-linear optimization method for the conversion of relaxation curves to the distribution of relaxation times by using non-specialized software. Our procedure consists of searching for the number of components, relaxation times, and their amplitudes, related to different types of hydrogen nuclei in the sample wetted with different amounts of water (different water-to-carbon ratio). We found that a maximum of five components with different relaxation times was sufficient to describe the observed relaxation. The individual components were attributed to a tightly bounded surface water layer (T2 up to 2 ms), water in small pores especially supermicropores (2 < T2 < 7 ms), mesopores (7 < T2 < 20 ms), water in large cavities between particles (20−1500 ms), and bulk water surrounding the materials (T2 > 1500 ms). To recalculate the distribution of relaxation times to the pore size distribution, we calculated the surface relaxivity based on the results provided by additional characterization techniques, such as thermoporometry (TPM) and N2/−196 °C physisorption.

Single-Sided Portable NMR Investigation to Assess and Monitor Cleaning Action of PVA-Borax Hydrogel in Travertine and Lecce Stone

In this work, we investigated the potential of PVA-borax hydrogel for cleaning limestones and the dependence of the cleaning on the porosity of the rock and on the action time of the hydrogel treatment. Towards this goal, we used a nuclear magnetic resonance (NMR) spectrometer, developed for non-invasive and non-destructive applications on cultural heritage. T2-NMR parameters were quantified on different samples of Lecce stone and Travertine cut perpendicular (Pe) and parallel (Pa) to the bedding planes under different experimental conditions: untreated samples, treated with Paraloid B72 and cleaned with PVA-PEO-borax hydrogel applied for 4 min and 2 h. The T2 results suggest that the effectiveness of the cleaning strongly depended on the porosity of the stones. In Lecce stone, the hydrogel seemed to eliminate both the paramagnetic impurities (in equal measure with 4 min and 2 h treatment) and Paraloid B72. In Travertine Pe, characterized by a smaller pore size compared to Lecce stone, no significant effects were found regarding both the cleaning and the treatment with Paraloid B72. In Travertine Pa, characterized by a larger pore size than the other two samples, the hydrogel seemed to clean the paramagnetic agents (it worked better if applied for a longer time) but it did not appear to have any effect on Paraloid B72 removal.

High Efficiency Fluorinated Oligo(ethylenesuccinamide) Coating for Stone

The protection of stone cultural assets is related to the transformation of the surface characteristic from hydrophilic to hydrophobic/superhydrophobic through the application of a coating. The suitability of a coating depends not only on its capability to dramatically change the surface wettability, but also on other parameters such as the modification of kinetics of water absorption, the permanence of vapor diffusivity, the resistance of the coating to aging and the low volatile organic compound emissions during its application. In this work, an oligo(ethylensuccinamide) containing low molecular pendant perfluoropolyether segments (SC2-PFPE) and soluble in environmentally friendly solvents was tested as a protective agent for historic stone artifacts. Magnetic resonance imaging and relaxometry were employed to evaluate the effects of the surface wettability change, to follow the water diffusion inside the rock and to study the porous structure evolution after the application of SC2-PFPE. A sun-like irradiation test was used to investigate the photo-stability of the product. The results demonstrate that the highly photo-stable SC2-PFPE minimizes the surface wettability of the stone by modifying the water sorptivity without significantly affecting its porous structure and vapor diffusivity. The improved performance of SC2-PFPE in comparison to other traditional coatings makes it a potential candidate as an advanced coating for stone cultural heritage protection.

Identification of complex structures of paintings on canvas by NMR: Correlation between NMR profile and stratigraphy

Paintings on canvas are complex structures created by superimposing layers of different composition. Investigations on the structure of these artworks can provide essential information on their state of conservation, pictorial technique, possible overpaintings, and in planning a proper conservation plan. Standard methods of investigation consist in sampling a limited number of fragments for stratigraphic analyses. Despite the recognized validity of these methods, they are affected by evident limitations. Nuclear magnetic resonance (NMR) profiling, often named NMR stratigraphy, is an NMR relaxometry technique applied by single-sided portable devices developed to overcome the disadvantages of microinvasive stratigraphic analyses. The potential of this approach on artworks, including wall paintings and a few examples of painted canvas, is described in the literature. In this study, NMR profiles of painting on canvas were examined by analyzing transverse relaxation time data by T₂ quasi-continuous distributions and the results compared with standard stratigraphic cross-sections analysis. Combining signal intensity and T₂ quasi-continuous distributions, the identification of textile, preparatory, and paint layers was enhanced. The diction "NMR stratigraphy" for these inhomogeneous layered artworks is also discussed. Indeed, unlike the stratigraphic cross-sections, NMR profiles provide information on a volume (flat slice), rather than on a surface, and the collected signal can derive from nonuniform and partially overlapping layers. This study paves the way for extensive investigations on relaxation time quasi-continuous distributions in various binder/pigment mixtures in order to improve the reliability of NMR profile as an innovative, non-invasive, and nondestructive method for analyzing paintings on canvas.

An Efficient Implementation of Deep Convolutional Neural Networks for MRI Segmentation

Image segmentation is one of the most common steps in digital image processing, classifying a digital image into different segments. The main goal of this paper is to segment brain tumors in magnetic resonance images (MRI) using deep learning. Tumors having different shapes, sizes, brightness and textures can appear anywhere in the brain. These complexities are the reasons to choose a high-capacity Deep Convolutional Neural Network (DCNN) containing more than one layer. The proposed DCNN contains two parts: architecture and learning algorithms. The architecture and the learning algorithms are used to design a network model and to optimize parameters for the network training phase, respectively. The architecture contains five convolutional layers, all using 3 × 3 kernels, and one fully connected layer. Due to the advantage of using small kernels with fold, it allows making the effect of larger kernels with smaller number of parameters and fewer computations. Using the Dice Similarity Coefficient metric, we report accuracy results on the BRATS 2016, brain tumor segmentation challenge dataset, for the complete, core, and enhancing regions as 0.90, 0.85, and 0.84 respectively. The learning algorithm includes the task-level parallelism. All the pixels of an MR image are classified using a patch-based approach for segmentation. We attain a good performance and the experimental results show that the proposed DCNN increases the segmentation accuracy compared to previous techniques.

An Environmental Friendly Fluorinated Oligoamide for Producing Nonwetting Coatings with High Performance on Porous Surfaces

The changes in the surface wettability of many materials are receiving increased attention in recent years. It is not too hard to fabricate resistant hydrophobic surfaces through products bearing both hydrophobic and reactive hydrophilic end groups. More challenging is obtaining resistant nonwetting surfaces through noncovalent reversible bonds. In this work, a fluorinated oligo(ethylenesuccinamide), soluble in solvent benign for operators and environment, has been synthesized. It contains two opposite functional groups (perfluoropolyether segments and amidic groups) (SC2-PFPE) that provide water repellency while hydrophilicity is retained. Its performance has been tested on porous calcarenite and investigated by magnetic resonance imaging, water capillary absorption, and vapor diffusivity tests. The results demonstrate that SC2-PFPE modifies the wettability of porous substrates in a drastic and durable way and reduces the vapor condensation inside the pore space due to the perfluoropolyether segments that act at the air/surface interface.