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A great variety of applications requires to process two-dimensional NMR (2DNMR) data to obtain information about the materials properties. In order to face the increasing request for software to easily process 2DNMR data, in (Bortolotti et al. (2019) [1]), the authors released Upen2dTool, an open source MATLAB software tool implementing nonnegatively constrained uniform penalty locally adapted norm-based regularization for 2DNMR data inversion. This paper presents MUPen2DTool a new open-source MATLAB software tool implementing an unconstrained multipenalty regularization method based on and norms. The new software MUPen2DTool outperforms Upen2dTool since the implemented uniform multipenalty method allows to compute very accurate 2DNMR data inversion at reduced computational cost. By means of MUPen2DTool, the user can choose among several types of NMR experiments, and the free software provides codes that can be used and extended easily. Furthermore, a MATLAB interface makes it easier to include users own data. The practical use is demonstrated in the reported examples of both synthetic and real NMR data.

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.

Numerical simulations are important tools for the assessment of exploiting geothermal energy in heat pump applications. They can be used to evaluate the performance of the system, the long-term production scenarios and the sustainability of the geothermal reservoir. The present work introduces and describes a numerical model, in which a dedicated Matlab script has been realized to allow sequentially coupled simulations of a shallow geothermal reservoir and of a heat pump system. A mathematical model of a dual-source heat pump, working alternatively with the ground or the air as heat source/sink, has been developed in Matlab environment. The heat exchangers of the heat pump have been modelled considering the equations that govern the physical phenomena. The dynamic numerical simulator FEFLOW, based on the finite element method, has been used to simulate the behaviour of the geothermal reservoir, subjected to heat extraction/reinjection by a closed loop vertical heat exchangers field. This methodological approach is useful to evaluate the performance of the coupled system in the long term, and it is important for understanding the advantages and limits of the dual-source heat pump in assuring sustainability over time avoiding the depletion of geothermal resources. The models and their coupling have been calibrated and validated with experimental data from a shallow geothermal plant located in Tribano (Padova, IT). It consists of eight coaxial borehole heat exchangers 30 m deep, connected to a 16 kW dual-source heat pump prototype. The heat pump system provides heating and cooling to an office area. The coupled model has been used to compare the performance of the heat pump when working in air-mode only or in ground-mode only. This allowed the development of a switching control strategy between the two thermal sources. Yearly simulations with the switching strategy have shown that the seasonal performance factor of the dual-source heat pump during the heating mode can be 13.8 % higher compared to the one obtained with a conventional air source heat pump and 3.8 % higher with respect to a ground source heat pump.

During CO2 injection operation start-up, strong transient flow occurs. It may lead to sudden changes in CO2 flowing pressure and temperature profiles, and possible phase transition. Moreover, wellbore flow behaviour affects the temperature at which CO2 enters the reservoir posing operational risks such as hydrates precipitation in the reservoir, ice formation around the wellbore, and thermal shocks of the casing. This indicates the importance of a reliable simulation of the coupled wellbore and reservoir flow to design the injection operations. The T2Well-ECO2M coupled wellbore-reservoir simulator allows the modelling of three-phase flow with the possible coexistence of liquid and gaseous CO2. T2Well-ECO2M offers a numerical and a semi-analytical approach to calculate heat exchange between the wellbore and surrounding formation. The full numerical approach is the most accurate, however, it requires building and solving spatial grids with many additional discretisation elements just for the modelling of heat conduction. The semi-analytical approach for wellbore heat exchange is based on the Ramey’s method with or without time-convolution. The numerical and the semi-analytical option with time-convolution approach options were compared with reference to the simulation of dry CO2 injection at constant wellhead rate and enthalpy in a simple 1D radial reservoir containing CO2 and immobile brine. The conceptual model, considered in both approaches, assumes a reservoir at depth of 3067 m with a radial extension of 2000 m. The evolution of flowing pressure and temperature profiles as well as the radial distribution of reservoir thermodynamic conditions are compared. The computation time to solve the time-convolution semi-analytical case was approximately 2.5 % of the time necessary to solve the numerical case with, overall, a good approximation of the numerical solution.

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.

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Fast Field-Cycling Nuclear Magnetic Resonance relaxometry is a non-destructive technique to investigate molecular dynamics and structure of systems having a wide range of ap- plications such as environment, biology, and food. Besides a considerable amount of liter- ature about modeling and application of such technique in specific areas, an algorithmic approach to the related parameter identification problem is still lacking. We believe that a robust algorithmic approach will allow a unified treatment of different samples in several application areas. In this paper, we model the parameters identification problem as a con- strained L 1 -regularized non-linear least squares problem. Following the approach proposed in [ Analytical Chemistry 2021 93 (24)], the non-linear least squares term imposes data con- sistency by decomposing the acquired relaxation profiles into relaxation contributions as- sociated with 1 H −1 H and 1 H −14 N dipole-dipole interactions. The data fitting and the L 1 - based regularization terms are balanced by the so-called regularization parameter. For the parameters identification, we propose an algorithm that computes, at each iteration, both the regularization parameter and the model parameters. In particular, the regularization parameter value is updated according to a Balancing Principle and the model parameters values are obtained by solving the corresponding L 1 -regularized non-linear least squares problem by means of the non-linear Gauss-Seidel method. We analyse the convergence properties of the proposed algorithm and run extensive testing on synthetic and real data. A Matlab software, implementing the presented algorithm, is available upon request to the authors.

It is recognized that biochar undergoes changes when it is applied to soils. However, the mechanisms of biochar alterations are not fully understood yet. To this purpose, the present study is designed to investigate the transformations in the soil of two different biochars obtained from pyrolysis of fir-wood pellets. The production of the biochars differed for the dry and wet quenching procedures used to terminate the pyrolysis. Both biochars were applied to clay soil (26% sand, 6% silt, and 68% clay) placed into lysimeters. After water saturation and 15 days of equilibration, seeds of watercress (Lepidium sativum) were cultivated. After a further 7 weeks, the biochars were manually separated from the systems. A total of four samples were collected. They were analyzed for chemical–physical characteristics by using an innovative technique referred to as fast field cycling nuclear magnetic resonance relaxometry. The results showed that the dry−quenching produced a material that was mainly chemically altered after application to soil compared to the biochar obtained by the wet−quenching. Indeed, the latter was both chemically and physically modified. In particular, results showed that water was better retained in the soil treated with the dry−quenched material. Consequently, we may suggest that crop productivity and environmental remediation may be modulated by applying either the dry−quenched or the wet−quenched biochar.

Nuclear Magnetic Resonance (NMR) is a well-suited methodology to study bone composition and structural properties. This is because the NMR parameters, such as the T2 relaxation time, are sensitive to the chemical and physical environment of the 1H nuclei. Although magnetic resonance imaging (MRI) allows bone structure assessment in vivo, its cost limits the suitability of conventional MRI for routine bone screening. With difficulty accessing clinically suitable exams, the diagnosis of bone diseases, such as osteoporosis, and the associated fracture risk estimation is based on the assessment of bone mineral density (BMD), obtained by the dual-energy X-ray absorptiometry (DXA). However, integrating the information about the structure of the bone with the bone mineral density has been shown to improve fracture risk estimation related to osteoporosis. Portable NMR, based on low-field single-sided NMR devices, is a promising and appealing approach to assess NMR properties of biological tissues with the aim of medical applications. Since these scanners detect the signal from a sensitive volume external to the magnet, they can be used to perform NMR measurement without the need to fit a sample inside a bore of a magnet, allowing, in principle, in vivo application. Techniques based on NMR single-sided devices have the potential to provide a high impact on the clinical routine because of low purchasing and running costs and low maintenance of such scanners. In this review, the development of new methodologies to investigate structural properties of trabecular bone exploiting single-sided NMR devices is reviewed, and current limitations and future perspectives are discussed.

This work is focused on the effects of drying/re-saturation cycles on the structure and components of White Portland Cement (WPC) samples. In particular, WPC of 0.5 water-to-cement ratio was studied by 1H Nuclear Magnetic Resonance (NMR) Relaxometry. A number of NMR sequences and different data processing methods were applied. Short (14 days of re-saturation) and long (6 months for the whole cycle) sorption cycles were investigated, using two drying methods: oven drying and drying under controlled relative humidity. The evolution during drying/re-saturation processes of interlayer space, gel pores, and bigger pores was followed by both the transverse relaxation times and the intensities of the nuclear magnetization. As a result of drying, reversible and irreversible changes in the pore structure, especially concerning the smaller porosity (interlayer and gel pores), were seen. Likewise, 1H signals in the crystalline phases of the cement were investigated by the standard Quadrature Echo method and by a more informative analysis based and a proper acquisition and processing of the longitudinal relaxation data. This analysis allowed the signal separation of 1H nuclei with higher and lower mobility (“solid” components). The NMR signal from this last component was analyzed on the basis of the Pake-Doublet theory in the time domain and two components were clearly detected, and assigned to 1H nuclei of crystalline water in Ettringite and OH groups in Portlandite. Reversible changes of the solid components of the cement samples were observed. This is a new method to deeply investigate the changes of solid components during sorption cycles.

Summary This paper presents preliminary results of a new T2Well version, coupled with modified ECO2M equation of state, able to simulate three-phase flow in the wellbore with the coexistence of liquid and gaseous CO2, with the final aim to be able to detect possible operational problems caused by phase changes during transient flow periods.

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.

Geologists and Reservoir Engineers routinely use time-domain nuclear magnetic resonance (NMR) to learn about the porous structure of rocks that hold underground fluids. In particular, two-dimensional NMR (2DNMR) technique is now gaining importance in a wide variety of applications. Crucial issue in 2DNMR analysis are the speed, robustness and accuracy of the data inversion process. This paper proposes a multi-penalty method with locally adapted regularization parameters for fast and accurate inversion of 2DNMR data. The method solves an unconstrained optimization problem whose objective function contains a data-fitting term, a single L1 penalty parameter and a multiple parameter L2 penalty. We propose an adaptation of the Fast Iterative Shrinkage and Thresholding (FISTA) method to solve the multi-penalty minimization problem, and an automatic procedure to compute all the penalty parameters. This procedure generalizes the Uniform Penalty principle introduced in [Bortolotti et al., Inverse Problems, 33(1), 2016]. The proposed approach allows us to obtain accurate 2D relaxation time distributions while keeping short the computation time. Results of numerical experiments on synthetic and real data prove that the proposed method is efficient and effective in reconstructing the peaks and the flat regions that usually characterize 2DNMR relaxation time distributions.

Pathline or streamline computation is used today to improve the understanding of fluid flow behavior in groundwater modelling. In particular, pathline computation on unstructured grids requires an accurate velocity interpolation method when the flow velocity field is given by numerical simulators only at the faces of the grid blocks; as for example in the case of the Integral Finite Difference method is used for spatial discretization. In the case of 3D Voronoi unstructured grids, a corner velocity interpolation (CVI) method allows continuous velocity field interpolation while preserving the mass conservation principle. We have developed a computer code, named TOUGH2Path, able to compute the velocity field based on the CVI method and generalized barycentric coordinates for 3D Voronoi polytope grid blocks tailored for the TOUGH family of codes. Results for the classical quarter five spot problem show that the coded algorithm correctly reproduces the pathlines computed with semi-analytical methods.

Purpose: Reduced bone strength is associated with a loss of bone mass, usually evaluated by dual-energy X-ray absorptiometry, although it is known that the bone microstructure also affects the bone strength. Here, a method is proposed to measure (in laboratory) the bone volume-to-total volume ratio by single-sided NMR scanners, which is related to the microstructure of the trabecular bone. Methods: Three single-sided scanners were used on animal bone samples. These low-field, mobile, low-cost devices are able to detect the NMR signal, regardless of the sample sizes, without the use of ionizing radiations, with the further advantage of signal localization offered by their intrinsic magnetic field gradients. Results: The performance of the different single-sided scanners have been discussed. The results have been compared with bone volume-to-total volume ratio by micro CT and MRI, obtaining consistent values. Conclusions: Our results demonstrate the feasibility of the method for laboratory analyses, which are useful for measurements like porosity on bone specimens. This can be considered as the first step to develop an NMR method based on the use of a mobile single-sided device, for the diagnosis of osteoporosis, through the acquisition of the signal from the appendicular skeleton, allowing for low-cost, wide screening campaigns. © 2017 International Society for Magnetic Resonance in Medicine.

In this paper we present an improvement of the 2DUPEN algorithm (I2DUPEN) obtained by applying data windowing and Singular Value Decomposition (SVD) filtering. The presented I2DUPEN method solves a regularized weighted least squares problem where the weights are related to the statistics of the data. The SVD filtering is applied to reduce the problem size. The preliminary results on real 2D Nuclear Magnetic Resonance data show the potentiality of this strategy to improve the performance of the algorithm preserving reconstructions of good quality. Just as the original 2DUPEN algorithm, I2DUPEN can be used on a wide range of NMR data obtained from different kinds of samples, from multi-scale length porous materials to biological samples.

Fast-field-cycling nuclear magnetic resonance (FFC-NMR) is a powerful technique for non-destructively probing the properties of fluids contained within the pores of porous materials. FFC-NMR measures the spin&ndash, lattice relaxation rate R 1 ( f ) as a function of NMR frequency f over the kHz to MHz range. The shape and magnitude of the R 1 ( f ) dispersion curve is exquisitely sensitive to the relative motion of pairs of spins over time scales of picoseconds to microseconds. To extract information on the nano-scale dynamics of spins, it is necessary to identify a model that describes the relative motion of pairs of spins, to translate the model dynamics to a prediction of R 1 ( f ) and then to fit to the experimental dispersion. The principles underpinning one such model, the 3 &tau, model, are described here. We present a new fitting package using the 3 &tau, model, called 3TM, that allows users to achieve excellent fits to experimental relaxation rates over the full frequency range to yield five material properties and much additional derived information. 3TM is demonstrated on historic data for mortar and plaster paste samples.

How to estimate the risk of the occurrence of non-hydrocarbon components (nonHC) such as carbon dioxide (CO2), hydrogen sulfide (H2S) or nitrogen (N2), is one of the main issues in the field of petroleum exploration. Numerical models can provide valuable tools to predict the occurrence and distribution of such components. Different approaches exists to this end, starting from the simplest ones, relying onto geometrical considerations, up to those based on a fully physical description of the migration and accumulation processes.In this work, a procedure for efficient coupling of petroleum system analysis withmultiphase Darcy flow simulations is developed to obtain 3D time dependent representation of the migration paths and accumulation volumes of nonHC at basin scale on a geological timescale. We focus on the tests carried out to prove that is technically feasible to run simulations of very deep geological formations (high P, T, salinity) even if considering a very detailed picture of the transport phenomena (buoyant, viscous and capillary forces). The challenge is to find the right compromise between the needs to honor fine-scale hydrostratigraphic details of the structure and the size of the numerical model in its discretized form.

The inversion of two-dimensional Nuclear Magnetic Resonance (NMR) data requires the solution of a rst kind Fredholm integral equation with a two-dimensional tensor product kernel and lower bound constraints. For the solution of this ill-posed inverse problem, the recently presented 2DUPEN algorithm [V. Bortolotti et al., Inverse Problems , 33(1), 2016] uses multi- parameter Tikhonov regularization with automatic choice of the regularization parameters. In this work, I2DUPEN, an improved version of 2DUPEN that implements Mean Windowing and Singular Value Decomposition filters, is deeply tested. The reconstruction problem with filtered data is formulated as a compressed weighted least squares problem with multi-parameter Tikhonov regularization. Results on synthetic and real 2D NMR data are presented with the main purpose to deeper analyze the separate and combined e effects of these filtering techniques on the reconstructed 2D distribution.