Conservation process of archaeological waterlogged wood studied by spectroscopy and gradient NMR methods
The properties of methyltrimethoxysilane-treated, waterlogged archeological elm wood were studied by magnetic resonance imaging and nuclear magnetic resonance (NMR) methods. The spatially resolved proton density images, spin–spin relaxation profiles, proton NMR spectra, and self-diffusion coefficients of the preservative agents were measured during drying. The resolution of the data allowed for the differentiation between the early and late wood areas of the elm wood and determination of the shrinkage of the sample in the tangential and radial directions, and it showed the different dynamics of methyltrimethoxysilane (MTMS) in the lumen cells of both early and late woods. The NMR spectra indicated that the MTMS, after rapid evaporation of ethanol, is bound to the wood. Identical measurements were also taken for the archeological elm wood treated with polyethylene glycol (PEG) and for an untreated wood sample. From the results, it can be concluded that MTMS showed significantly higher stability against shrinkage when compared to PEG. Therefore, it may be considered as an alternative preservative for archeological wood.
Waterlogged archaeological wood is most often characterized by a high degree of degradation, but it retains its shape and dimensions due to the presence of water that fills cell lumen and voids within the wood tissue. However, when wood is removed from water and placed in a dry atmosphere, the rapid evaporation of water leads to its further destruction resulting in shrinkage, cracking, and deformation (Siau 1984; Bugani et al. 2009). The only way to save waterlogged wooden objects is their proper conservation immediately after excavation from the wet environment. This involves the exchange of the water that fills the wood tissue for an appropriate chemical that will strengthen the wood structure and prevent its distortion, but unlike water, will not evaporate from the wood when exposed to air. Studies on conservation agents that meet such requirements have been conducted for years (Grattan 1982; Unger et al. 2001; Walsh et al. 2014; Imazu and Morgòs 1996; Christensen et al. 2012). Nevertheless, the most commonly used agent for the preservation of wet archaeological wood is still polyethylene glycol (PEG) (Jensen and Schnell 2004). However, the longstanding application of this conservation agent has shown that it has some serious drawbacks, which include leachability from wood under temperature and humidity changes; high hygroscopicity (especially low-molecular PEG); intense water absorption under relative humidity above 80%; and vulnerability to oxidation reactions, for example, catalyzed by iron ions, which are often found in archaeological wood, leading to its depolymerization and formation of acids causing further chemical degradation of wood (Smith 2003; Olek et al. 2016; Bjordal 2012; Almkvist 2013; Almkvist and Persson 2007; Sandström et al. 2005). Therefore, there is still a need for further research on novel and effective agents for waterlogged archaeological wood conservation. One newly tested group of chemicals is organosilicon compounds, which include alkoxysilanes and methyltrimethoxysilane (MTMS) among others (De Vetter et al. 2009, 2010; Mai and Militz 2004; Andriulo et al. 2017). The results of previous research indicate that MTMS can effectively stabilize the dimensions of archaeological waterlogged wood differing in the degree of degradation (Broda and Mazela 2017; Broda et al. 2018).
In this work, wet archaeological elm (Ulmus spp.) wood was treated with a 50% ethanol solution of MTMS. For comparison, waterlogged elm wood was also treated with 50% water solution of PEG 400. Untreated wood fully saturated with water was used as a control. The main goal of the research was to investigate the drying dynamics of wet archeological elm wood treated with MTMS or PEG solutions using spectroscopy and gradient NMR methods. The distribution and the concentration of the two modifying agents were also studied along with their effect on the dimensional stability of waterlogged wood.
Materials and methods
Waterlogged archaeological elm was excavated from the Lednica Lake in the Wielkopolska Region (Broda and Mazela 2017). For MRI studies, 10 × 10 × 10 mm-sized cubic samples were cut from the elm log and their middle layers of a thickness of 1 mm were analyzed. For diffusion and SPI measurements, the elm wood samples were cut to fit the 5-mm NMR probe. The NMR signal in these experiments was collected from the whole sample.
Magnetic resonance imaging
Magnetic resonance imaging (MRI) is a type of analysis that uses magnetic fields and radio waves to produce detailed images of the inside of a sample. Since the discovery of the method by Lauterbur and Mansfield (Lauterbur 1973; Mansfield and Grannell 1973), it has been successfully used in hospital diagnostics and basic research, including studies on wood (Gezici-Koç et al. 2017; Mikac et al. 2018; Kanazawa et al 2017; Žlahtič et al. 2017). Gezici-Koç et al. (2017) used MRI to study the state of water within a wood cell, and whether it is bound or free water, and used the data gained to determine the diffusion coefficient for several species of timber.
The method applies a time-dependent linear gradient field onto the static magnetic field to relate the magnetic field to the spatial position of the studied object. Because the nuclear magnetic resonance frequency, so-called Larmor frequency, is proportional to the magnetic field, there is a linear relationship between the resonant frequency and the spatial position. Tomographic images of the sample in 1D, 2D, or 3D display can be obtained with a spatial resolution of μm. Depending on the chosen pulse sequence and parameters of the experiment, it is possible to measure the spin density 𝜌(r), the spin–spin relaxation time T2, the spin–lattice relaxation time T1, or the diffusion D weighted images. The tomographic image of the studied sample is obtained with a 𝜌, T2, or D contrast, respectively, because the intensity of every point of the image is proportional to one of the above parameters of the resonance nuclei (mainly protons) in this point. It is worth noting that the MRI is a noninvasive method, which allows studying the same sample as a function of time and thus eliminate the possible effect of the difference between samples on the result obtained. In the presented research, the multi-slice multi-echo (MSME) and single point imaging (SPI) MRI methods were used (Callaghan 1991; Kimmich 1997; Blümich 2000).
The MSME experiments were performed on a Bruker AVANCE 300 MHz WB spectrometer equipped with imaging facilities. The static Bo field of 7.05 Tesla corresponds to the proton (1H) Larmor frequency of 300.23 MHz. A Bruker imaging probehead Micro 2.5 was used with a 20-mm birdcage coil, which allows the application of pulse gradients of up to 1T m−1. The images were acquired with the repetition time TR of 4000 ms, and the echo time TE was varied from 7 to 224 ms. The acquisition parameters were a field-of-view (FOV) of 22 × 22 mm digitized into 128 × 128 pixels with a slice thickness of 1 mm (i.e., each voxel equals 171 by 171 by 21 × 103 μm). The MRI measurements were taken at 23 °C.
In the present work, the SPI method was used to obtain 1D images (or 1D profiles) of the proton density of the conservation agent filling archaeological elm wood. The profiles were acquired in the z-direction with tp = 0.1 ms, FOV = 15 mm, and a resolution of 117 μm at 23 °C. The SPI method was implemented on a Bruker Avance III HD spectrometer operating at 500 MHz of 1H Larmor frequency and coupled to 11.4 T superconducting magnet. The spectrometer was equipped with a gradient unit allowing the application of a maximum gradient strength in the z-direction of 30 T m−1 and a diffusion probe with the coil of 5-mm diameter. The probe was used in the SPI method and in pulse-field gradient 1H NMR diffusion experiments. Details of the MRI methods have been published elsewhere (Gravina and Cory 1994; Kimmich 1997; Blümich 2000); therefore, they are only discussed briefly here.
Pulse gradient stimulated echo (PGSTE) NMR
The measurements were carried out as a function of the magnetic field gradient strength, g, that changed in 32 steps with a maximum gradient equal to 300, 1500, or 3000 G/cm depending on the experiment. The parameters 𝛿 and ∆ were equal to 1 ms and 20 ms, respectively, and remained unchanged during the measurements. The measurements were taken at 23 °C.
For a homogeneous system, the echo signal decay is well described by Eq. (3). However, when diffusion takes place in an inhomogeneous system, as, for example, wood tissue with cavities and pores of various sizes, a distribution of the self-diffusion coefficient D can occur and the observed echo decay is the sum of the function given by Eq. (3).
Proton NMR spectroscopy
1H NMR spectra of the treated elm samples were conducted on a Bruker Avance III HD spectrometer. The experiments were performed at 23 °C applying simple π/2 pulse to samples.
Linear wood shrinkage
Results and discussion
Drying process studied by MRI and NMR spectroscopy
The signal intensity (the shade of gray) at every point of the images shown in Fig. 1 is proportional to the number of hydrogen nuclei (i.e., to the proton density) present in water or the conservation solution filling the archeological wood sample. However, the main chemical wood components (cellulose, hemicellulose, and lignin) also contain protons; the experimental setup in the conducted experiment did not allow us to detect their signal. SEM images of the examined archaeological elm wood (Broda and Mazela 2017) showed a heterogeneous wood microstructure: early wood and late wood areas, the inner cavities called the lumen cells, and the surrounding structural layer called the cell walls. The shape and size of the lumen cells are irregular and the thickness of the cell walls is different. Generally, the early wood of archeological elm is characterized by a less dense structure with large inhomogeneous lumens whereas the size of lumens in the late wood is much smaller, and thus, the structure is denser. The following interesting features can be observed from images seen in Fig. 1: clearly visible areas of early and late wood, changes in the sample dimensions during drying, and different duration of the drying process depending on the solvent applied. The signal intensity of water (Fig. 1a), PEG (Fig. 1b), and MTMS solution (Fig. 1c) in early wood areas of saturated samples is considerably higher compared to late wood. This is due to a different anatomical microstructure of late and early woods. Larger cavities of early wood contain more solvent in comparison with late wood, which results in a higher MRI signal. During the drying process, the solvents used evaporate faster from the larger cell lumina. Therefore, the early wood areas become darker in the first place because of the loss of protons from solvents and thus the loss of an MRI signal.
Generally, the contraction of the tested samples increased upon drying, but the size and rate of shrinkage depended on the conservation agent/solvent used. MTMS-treated wood showed much higher stability against shrinkage compared with PEG. Shrinkage in both directions was comparable and was about 4%, in contrast to the results observed for PEG-treated wood, where it was 35% and 8% in the tangential and radial directions, respectively. The shortest drying time was recorded for the MTMS-treated sample (about 1420 min). A significantly longer time was necessary to dry PEG-treated and untreated samples (about 5600 and 6300 min, respectively). After these times, no MR signal was visible under the experimental conditions applied.
They were measured immediately after removal of the sample from the solution (before) and at a particular time of the drying process: after 24 h (1440 min) in the case of PEG and after 1 h (60 min) and 24 h (1440 min) for MTMS.
After 24 h of drying, a significant decrease in the intensity of the MTMS proton density profile is observed (Fig. 5 right). The observed signal probably comes from bound MTMS protons, but that can be measured in the conditions of the present experiment. The encoding time, tp,= 0.1 ms μs excludes from the current measurements of the very rigid MTMS molecules bound by hydrogen bonding with hydroxyl groups of hemicellulose, cellulose, and lignin–cellulose on the microfibrills surfaces. 1D SPI proton intensity profiles of PEG (Fig. 5 left) provide similar information to the spectra from Fig. 4. The drop in the signal intensities to about 40% of the initial value observed after 24 h of drying was caused by evaporation of a lot of water. It is worth noting that the 1D SPI proton density signals were collected from much smaller elm wood samples than in the MSME experiment. The magnetic gradient was applied in the longitudinal direction (parallel to the wood grain). The profile is the projection of the proton density from the entire sample to this axis. Therefore, contrary to the images obtained by MSME pulse sequence, SPI profiles do not distinguish between solvent signals from the early and late woods. They give the average signal from both areas of wood. The profiles shown in Fig. 5 indicate a homogeneous distribution of solvents in the microstructure of treated wood.
Dynamics of conservation agents studied by relaxation and diffusion
The hydrogen-containing molecules (i.e., the solution of PEG or MTMS) can randomly diffuse inside the cavities of the elm wood and collide with each other and with the cell walls. These interactions are the origin of T2 relaxation. Generally, T2 is longer for molecules diffusing freely (e.g., free solvent in large lumen cells) and shorter for molecules, whose mobility is restricted by small lumens or cavities, and very short for bound molecules. The same applies to the value of diffusion coefficients for solutions in wood. As seen in Fig. 6, the change in relaxation time resulting from drying the sample shows a similar character to that of the change in MRI signal intensity (Fig. 3, the right side); it decreases as a function of drying. Two relaxation times have also been distinguished and assigned to the solvent in the cell lumina of early and late woods. Cell lumina of early wood are larger and characterized by longer T2 compared to late wood (Cox et al. 2010). However, this is only true for the specific drying time of the sample: about 3000 min in the case of PEG and about 500 min for MTMS. After these times, the T2 of PEG and MTMS in the pores of early wood becomes less than or equal to the T2 values in the pores of late wood. This finding, in the case of wood filled with PEG, can be explained as follows: after fast evaporation of PEG from the largest pores in early elm wood, some water molecules still remain in the smallest pores of early wood, which are much smaller than in late wood. Thus, the motion of water is more limited, which leads to a shorter T2 compared to that characterizes the molecules in the pores of late wood. It cannot be ruled out, however, that after evaporation of free water, more mobile PEG molecules (for example, clusters with waters) contribute to the measured relaxation time. It should be mentioned that the relaxation time depicted in Fig. 6 is the average relaxation time. In the case of MTMS filling the elm wood sample, the T2relaxation time of the solvent in the lumina of early and late woods can be distinguished only up to about 400 min, after that both times become equal. Taking into account the previously analyzed results obtained by the method of SPI and NMR spectroscopy, the relaxation results confirm that, after rapid evaporation of ethanol, the MTMS molecules remained in the cell lumina of the early and late woods. The diffusometry gives proof that some of them are bound (they can polymerize into longer chains or interact with wood polymers).
The diffusion of water in the lumen is much faster than the diffusion in the cell walls. The average translational self-diffusion coefficient, Dev, of free water in the cell lumen is ≥ 10−9 m2/s depending on the size of the cells, whereas that of water in the cell wall is much longer. It was reported that water bound to cellulose fibers below fiber saturation point is characterized by Dev ≥ 10−12 m2/s (Topgard and Soderman 2001). Therefore, one can assume that the self-diffusion coefficient for bound water in wood cell walls is of the same order of magnitude (Engelund et al. 2013; Terenzi et al. 2013). Similar values can be expected for other solvents.
The echo decays of PEG and MTMS shown in Fig. 7 at the starting point of drying, immediately after removal of the sample from the solution, are well fitted by two components yielding two Dev values denoted as D1 and D2. For elm wood treated with PEG, D1 = 3.6 × 10−10 m2/s and D2 = 3.6 × 10−11 m2/s. For elm wood treated with MTMS, D1 = 3.6 × 10−9 m2/s and D2 = 3.6 × 10−10 m2/s. The diffusion measurements were also taken for wood treated with PEG after 24 h of drying and for wood impregnated with MTMS, after a few minutes of drying. The results of the fitting procedure give two diffusion coefficients for PEG (D1 = 3.1 × 10−12 m2/s and D2 = 0.9 × 10−11 m2/s) and three diffusion coefficients for MTMS (D1 = 2.1 × 10−9 m2/s, D2 = 2.5 × 10−10 m2/s, and D3 = 2.6 × 10−12 m2/s). In all cases, a single component does not fit the experimental data well.
According to the interpretation of the spin–spin relaxation time, two components of the self-diffusion coefficient obtained at the beginning of drying were also assigned to solvents in lumens of early wood (larger D) and late wood (smaller D). This interpretation is also valid for the results obtained at a later time of drying. The self-diffusion coefficient of PEG solvent in lumens of late wood (D2) does not change and is in the order of 10−11 m2/s (within 24 h of drying, water hardly evaporates from small lumens of elm late wood as shown in Fig. 3d). On the other hand, the average coefficient of solvent in lumens of early wood (D1) decreases during this time from 10−10 to 10−12 m2/s. This is the result of the evaporation of water from larger cells, where there is not much left. The remaining water in the cells is water, mainly bound by hydrogen bonding with PEG and PEG alone, and this slows the dynamics of the solvent.
The self-diffusion coefficient of MTMS solvent in lumens of late wood (D2) also does not change in a few minutes after starting drying and is in the order of 10−10 m2/s. However, in the case of MTMS in pores of early wood, two self-diffusion coefficients were distinguished: D1 = 2.1 × 10−9 m2/s (similar to that at the beginning of drying) and D3 = 2.6 × 10−12 m2/s. The D1 coefficient is assigned to ethanol molecules rapidly evaporated from the large lumens of early wood. After a few minutes of drying, a small amount of ethanol still remains (its contribution to the echo decay is equal to 8%). The D3 coefficient is attributed to the MTMS bound to wood polymers. The contribution of such protons to the total echo decay signal is equal to 22%.
The results presented in this paper clearly showed that MRI and NMR methods can be successfully used to observe the drying stage of a waterlogged archaeological wood conservation process with the use of PEG or MTMS. Due to the high sensitivity of the MRI method, it was possible to monitor the evaporation of particular solvents from the early and late wood areas of the elm wood during drying and also to demonstrate different dynamics of the applied conservation solutions inside the wood structure. The data obtained indicated a high probability of chemical modification of elm wood with silane, which would explain the observed high dimensional stability of wood treated with MTMS. However, the hypothesis of chemical binding of MTMS to wood polymers should be confirmed in further studies.
This work was supported by the Polish Ministry of Science and Higher Education as a part of the “Cultural heritage research into innovative solutions and methods for historic wood conservation” project within the National Program for the Development of Humanities in 2016–2019 (Project No. 2bH 15 0037 83).
Compliance with ethical standards
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
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