Adsorption of Polar Species at Crude Oil-Water Interfaces: the Chemoelastic Behavior.

We investigate the formation and properties of crude oil/water interfacial films. The time evolution of interfacial tension suggests the presence of short and long timescale processes reflecting the competition between different populations of surface-active molecules. We measure both the time-dependent shear and extensional interfacial rheology moduli. Late-time interface rheology is dominated by elasticity, which results in visible wrinkles on the crude oil drop surface upon interface disturbance. We also find that the chemical composition of the interfacial films is affected by the composition of the aqueous phase that it has contacted. For example, sulfate ions promote films enriched with carboxylic groups and condensed aromatics. Finally, we perform solution exchange experiments and monitor the late-time film composition upon the exchange. We detect the film composition change upon replacing chloride solutions with sulfate-enriched ones. To the best of our knowledge, we are the first to report the composition alteration of aged crude oil films. This finding might foreshadow an essential crude oil recovery mechanism.

Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact.

Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped with a 300 mT/m whole-body gradient system was installed at the Massachusetts General Hospital in 2011 and was specifically constructed as part of the Human Connectome Project. Since that time, numerous technological advances have been made to enable the broader use of the Connectom high gradient system for diffusion tractography and tissue microstructure studies and leverage its unique advantages and sensitivity to resolving macroscopic and microscopic structural information in neural tissue for clinical and neuroscientific studies. The goal of this review article is to summarize the technical developments that have emerged in the last decade to support and promote large-scale and scientific studies of the human brain using the Connectom scanner. We provide a brief historical perspective on the development of Connectom gradient technology and the efforts that led to the installation of three other Connectom 3T MRI scanners worldwide - one in the United Kingdom in Cardiff, Wales, another in continental Europe in Leipzig, Germany, and the latest in Asia in Shanghai, China. We summarize the key developments in gradient hardware and image acquisition technology that have formed the backbone of Connectom-related research efforts, including the rich array of high-sensitivity receiver coils, pulse sequences, image artifact correction strategies and data preprocessing methods needed to optimize the quality of high-gradient strength diffusion MRI data for subsequent analyses. Finally, we review the scientific impact of the Connectom MRI scanner, including advances in diffusion tractography, tissue microstructural imaging, ex vivo validation, and clinical investigations that have been enabled by Connectom technology. We conclude with brief insights into the unique value of strong gradients for diffusion MRI and where the field is headed in the coming years.

Inside-out NMR with two concentric ring magnets.

We report the design and the implementation of an inside-out NMR sensor that produces a large sensitive region with substantially uniform magnetic field at a remote location. The construction using a pair of ring magnets is simple yet provides multiple benefits, including large sample volume, operation with low RF power, and the ability to measure samples with long T2 and high diffusivity. A palm-size inside-out NMR sensor (57 mm OD × 29 mm height, 420 g including the housing and the coil PCB) was built with inexpensive magnets. The sweet spot is located ∼5 mm above the magnet surface with ∼4 mm width and ∼5 mm height assuming t180 = 18 µs. The field strength at that point is 0.16 T and achieved SNR ∼23 per two scans when operated with ∼10 W peak RF power. Its quasi-uniform B0 around the saddle point allows the measurement of T2 = 1.5 s with a 100 µs echo time.

Analytical models of probe dynamics effects on NMR measurements.

This paper provides a detailed analysis of three common NMR probe circuits (untuned, tuned, and impedance-matched) and studies their effects on multi-pulse experiments, such as those based on the Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence. The magnitude of probe dynamics effects on broadband refocusing pulses are studied as a function of normalized RF bandwidth. Finally, the probe circuit models are integrated with spin dynamics simulations to design hardware-specific RF excitation and refocusing pulses for optimizing user-specified metrics such as signal-to-noise ratio (SNR) in grossly inhomogeneous fields. Preliminary experimental results on untuned probes are also presented.

Multiphysics NMR correlation spectroscopy.

One hallmark of modern nuclear magnetic resonance spectroscopy is the use of multi-dimensional correlation experiments typically with only spin Hamiltonians. However, spin systems may be affected by interactions and processes that are not controlled through the spin degree of freedom. This paper demonstrates a correlation spectroscopy between two different physical processes, one is NMR spin dynamics, and the other capillary drainage for the study of porous materials. We show that such a correlation experiment produces a joint capillary pressure (Pc) and NMR relaxation (T2) correlation function, Pc-T2 map that probes how pores are connected, an insight not available in conventional NMR or capillary experiments.

Optimization of multidimensional MR data acquisition for relaxation and diffusion.

Multidimensional MR experiments of relaxation and diffusion have been successful for material characterization and have attracted attention recently for biomedical applications. However, such experiments typically require many scans of data acquisition and are time-consuming. This work discusses a method for systematic optimization of the pulse-sequence parameters to obtain optimal resolution within the experimental conditions, such as the number of acquisitions. Other optimization goals can also be incorporated in this framework.

Portable NMR with Parallelism.

Portable NMR combining a permanent magnet and a complementary metal-oxide-semiconductor (CMOS) integrated circuit has recently emerged to offer the long desired online, on-demand, or in situ NMR analysis of small molecules for chemistry and biology. Here we take this cutting-edge technology to the next level by introducing parallelism to a state-of-the-art portable NMR platform to accelerate its experimental throughput, where NMR is notorious for inherently low throughput. With multiple (N) samples inside a single magnet, we perform simultaneous NMR analyses using a single silicon electronic chip, going beyond the traditional single-sample-per-magnet paradigm. We execute the parallel analyses via either time-interleaving or magnetic resonance imaging (MRI). In the time-interleaving method, the N samples occupy N separate NMR coils: we connect these N NMR coils to the single silicon chip one after another and repeat these sequential NMR scans. This time-interleaving is an effective parallelization, given a long recovery time of a single NMR scan. To demonstrate this time-interleaved parallelism, we use N = 2 for high-resolution multidimensional spectroscopy such as J-coupling resolved free induction decay spectroscopy and correlation spectroscopy (COSY) with the field homogeneity carefully optimized (<0.16 ppm) and N = 4 for multidimensional relaxometry such as diffusion-edited T2 mapping and T1-T2 correlation mapping, expediting the throughput by 2-4 times. In the MRI technique, the N samples (N = 18 in our demonstration) share 1 NMR coil connected to the single silicon chip and are imaged all at once multiple times, which reveals the relaxation time of all N samples simultaneously. This imaging-based approach accelerates the relaxation time measurement by 4.5 times, and it could be by 18 times if the signal-to-noise were not limited. Overall, this work demonstrates the first portable high-resolution multidimensional NMR with throughput-accelerating parallelism.

Realtime optimization of multidimensional NMR spectroscopy on embedded sensing devices.

The increasingly ubiquitous use of embedded devices calls for autonomous optimizations of sensor performance with meager computing resources. Due to the heavy computing needs, such optimization is rarely performed, and almost never carried out on-the-fly, resulting in a vast underutilization of deployed assets. Aiming at improving the measurement efficiency, we show an OED (Optimal Experimental Design) routine where quantities of interest of probable samples are partitioned into distinctive classes, with the corresponding sensor signals learned by supervised learning models. The trained models, digesting the compressed live data, are subsequently executed at the constrained device for continuous classification and optimization of measurements. We demonstrate the closed-loop method with multidimensional NMR (Nuclear Magnetic Resonance) relaxometry, an analytical technique seeing a substantial growth of field applications in recent years, on a wide range of complex fluids. The realtime portion of the procedure demands minimal computing load, and is ideally suited for instruments that are widely used in remote sensing and IoT networks.

NMR application in unconventional shale reservoirs - A new porous media research frontier.

Unconventional shale reservoirs have greatly contributed to the recent surge in petroleum production in the United States and are expected to lead the US oil production to a historical high in 2018. The complexity of the rocks and fluids in these reservoirs presents a significant challenge to the traditional approaches to the evaluation of geological formations due to the low porosity, permeability, complex lithology and fluid composition. NMR has emerged as the key measurement for evaluating these reservoirs, for quantifying their petrophysical parameters, fluid properties, and determining productivity. Measurement of the T1/T2 ratio by 2D NMR has been found to be critical for identifying the fluid composition of kerogen, bitumen, light/heavy oils, gases and brine in these formations. This paper will first provide a brief review of the theories of relaxation, measurement methods, and data inversion techniques and then will discuss several examples of applications of these NMR methods for understanding various aspects of the unconventional reservoirs. At the end, we will briefly discuss a few other topics, which are still in their developmental stages, such as solid state NMR, and their potential applications for shale rock evaluation.

A miniaturized spectrometer for NMR relaxometry under extreme conditions.

With the advent of integrated electronics, microfabrication and novel chemistry, NMR (Nuclear Magnetic Resonance) methods, embodied in miniaturized spectrometers, have found profound uses in recent years that are beyond their conventional niche. In this work, we extend NMR relaxometry on a minute sample below 20 µL to challenging environment of 150 °C in temperature and 900 bar in pressure. Combined with a single-board NMR spectrometer, we further demonstrate multidimensional NMR relaxometries capable of resolving compositions of complex fluids. The confluence of HTHP (high-pressure high-temperature) capability, minimal sample volume, and reduced sensor envelop and power budget creates a new class of mobile NMR platforms, bringing the powerful analytical toolkit in a miniaturized footprint to extreme operating conditions.

Low fields but high impact: Ex-situ NMR and MRI.

"There's plenty of room at the bottom". This was the title of Richard Feynman's well-known lecture in 1959, often considered a seminal event in the history of nano-sciences and technologies. For magnetic resonance (MR), we borrow the statement to suggest a plethora of opportunities in low-field NMR/MRI with miniaturized apparatus, particularly the ex-situ type. We argue that a widespread use of MR technology is only possible at low fields.

In vivo microscopic diffusional kurtosis imaging with symmetrized double diffusion encoding EPI.

PURPOSE: Diffusional kurtosis imaging (DKI) measures the deviation of the displacement probability from a normal distribution, complementing the data commonly acquired by diffusion MRI. It is important to elucidate the sources of kurtosis contrast, particularly in biological tissues where microscopic kurtosis (intrinsic kurtosis) and diffusional heterogeneity may co-exist. METHODS: We have developed a technique for microscopic kurtosis MRI, dubbed microscopic diffusional kurtosis imaging (µDKI), using a symmetrized double diffusion encoding (s-DDE) EPI sequence. We compared this newly developed µDKI to conventional DKI methods in both a triple compartment phantom and in vivo. RESULTS: Our results showed that whereas conventional DKI and µDKI provided similar measurements in a compartment of monosphere beads, kurtosis measured by µDKI was significantly less than that measured by conventional DKI in a compartment of mixed Gaussian pools. For in vivo brain imaging, µDKI showed small yet significantly lower kurtosis measurement in regions of the cortex, CSF, and internal capsule compared to the conventional DKI approach. CONCLUSIONS: Our study showed that µDKI is less susceptible than conventional DKI to sub-voxel diffusional heterogeneity. Our study also provided important preliminary demonstration of our technique in vivo, warranting future studies to investigate its diagnostic use in examining neurological disorders.

Preliminary evaluation of accelerated microscopic diffusional kurtosis imaging (µDKI) in a rodent model of epilepsy.

PURPOSE: Our study aimed to develop accelerated microscopic diffusional kurtosis imaging (µDKI) and preliminarily evaluated it in a rodent model of chronic epilepsy. METHODS: We investigated two µDKI acceleration schemes of reduced sampling density and angular range in a phantom and wild-type rats, and further tested µDKI method in pilocarpine-induced epilepsy rats using a 4.7 Tesla MRI. Single slice average µDapp and µKapp maps were derived, and Nissl staining was obtained. RESULTS: The kurtosis maps from two accelerated µDKI sampling schemes (sampling density and range) are very similar to that using fully sampled data (SSIM > 0.95). For the epileptic models, µDKI showed noticeably different contrast from those obtained with conventional DKI. Specifically, the average µKapp was significantly less than that of the average of Kapp (0.15 ±â€¯0.01 vs. 0.47 ±â€¯0.02) in the ventricle. CONCLUSIONS: Our study demonstrated the feasibility of accelerated in vivo µDKI. Our work revealed that µDKI provides complementary information to conventional DKI method, suggesting that advanced DKI sequences are promising to elucidate tissue microstructure in neurological diseases.

Effect of off-resonance on T1 saturation recovery measurement in inhomogeneous fields.

Saturation-recovery measurements with Carr-Purcell-Meiboom-Gill sequences are commonly employed to measure the longitudinal relaxation time constant, T1, in grossly inhomogeneous fields. We show that in general the off-resonant effect generates unexpected extra signals in the T1 measurement. In the present study, we derive a modified T1 kernel that accounts for this off-resonance effect quantitatively. The new kernel has been tested with numerical simulations and experiments, and excellent agreement is found.

Direct correlation of diffusion and pore size distributions with low field NMR.

The time-dependent diffusion coefficient (D) is a powerful tool to probe microstructure in porous media, and can be obtained by the NMR method. In a real porous sample, molecular diffusion is very complex. Here we present a new method which directly measures the relationship between effective diffusion coefficients and pore size distributions without knowing surface relaxivity. This method is used to extract structural information and explore the relationship between D and a in porous media having broad pore size distributions. The diffusion information is encoded by the Pulsed Field Gradient (PFG) method and the pore size distributions are acquired by the Decay due to Diffusion in the Internal Field (DDIF) method. Two model samples were measured to verify this method. Restricted diffusion was analyzed, and shows that most fluid molecules experience pore wall. The D(a) curves obtained from correlation maps were fitted to the Padé approximant equation and a good agreement was found between the fitting lines and the measured data. Then a sandstone sample with unknown structure was measured. The state of confined fluids was analyzed and structural information, such as pore size distributions, were extracted. The D - T1 correlation maps were also obtained using the same method, which yielded surface relaxivities for different samples. All the experiments were conducted on 2MHz NMR equipment to obtain accurate diffusion information, where internal gradients can be neglected. This method is expected to have useful applications in the oil industry, particularly for NMR logging in the future.

The robust identification of exchange from T2-T2 time-domain features.

Two-dimensional spin-spin relaxation (T2-T2) techniques have been developed to probe coupling between different environments such as diffusive coupling between small and large pores or chemical exchange with clays. In these studies, Numerical Laplace Inversion (NLI) is used to obtain two-dimensional T2-T2 relaxation distribution spectrum from the T2-T2 signal decays, and the off-diagonal peaks characterize coupling. Often, these coupling peaks are both weak and close to the diagonal and combined with the inherently ill-conditioned nature of the inversion, their presence is difficult to differentiate from inversion related artifacts and blurring. This manuscript presents a time domain based analysis to identify the presence of coupling that avoids the ambiguities present in T2-T2 spectra. The approach utilizes the symmetric nature of the two-dimensional time domain data, where the presence of curvature along one of these symmetries gives an unambiguous indicator of coupling. Measurements on porous glass beads are used to verify the technique.

Detecting compartmental non-Gaussian diffusion with symmetrized double-PFG MRI.

Diffusion in tissue and porous media is known to be non-Gaussian and has been used for clinical indications of stroke and other tissue pathologies. However, when conventional NMR techniques are applied to biological tissues and other heterogeneous materials, the presence of multiple compartments (pores) with different Gaussian diffusivities will also contribute to the measurement of non-Gaussian behavior. Here we present symmetrized double PFG (sd-PFG), which can separate these two contributions to non-Gaussian signal decay as having distinct angular modulation frequencies. In contrast to prior angular d-PFG methods, sd-PFG can unambiguously extract kurtosis as an oscillation from samples with isotropic or uniformly oriented anisotropic pores, and can generally extract a combination of compartmental anisotropy and kurtosis. The method further fixes its sensitivity with respect to the time dependence of the apparent diffusion coefficient. We experimentally demonstrate the measurement of the fourth cumulant (kurtosis) of diffusion and find it consistent with theoretical predictions. By enabling the unambiguous identification of contributions of compartmental kurtosis to the signal, sd-PFG has the potential to help identify the underlying micro-structural changes corresponding to current kurtosis based diagnostics, and act as a novel source of contrast to better resolve tissue micro-structure.

Robust determination of surface relaxivity from nuclear magnetic resonance DT(2) measurements.

Nuclear magnetic resonance (NMR) is a powerful tool to probe into geological materials such as hydrocarbon reservoir rocks and groundwater aquifers. It is unique in its ability to obtain in situ the fluid type and the pore size distributions (PSD). The T1 and T2 relaxation times are closely related to the pore geometry through the parameter called surface relaxivity. This parameter is critical for converting the relaxation time distribution into the PSD and so is key to accurately predicting permeability. The conventional way to determine the surface relaxivity ρ2 had required independent laboratory measurements of the pore size. Recently Zielinski et al. proposed a restricted diffusion model to extract the surface relaxivity from the NMR diffusion-T2 relaxation (DT2) measurement. Although this method significantly improved the ability to directly extract surface relaxivity from a pure NMR measurement, there are inconsistencies with their model and it relies on a number of preset parameters. Here we propose an improved signal model to incorporate a scalable LT and extend their method to extract the surface relaxivity based on analyzing multiple DT2 maps with varied diffusion observation time. With multiple diffusion observation times, the apparent diffusion coefficient correctly describes the restricted diffusion behavior in samples with wide PSDs, and the new method does not require predetermined parameters, such as the bulk diffusion coefficient and tortuosity. Laboratory experiments on glass beads packs with the beads diameter ranging from 50 µm to 500 µm are used to validate the new method. The extracted diffusion parameters are consistent with their known values and the determined surface relaxivity ρ2 agrees with the expected value within ±7%. This method is further successfully applied on a Berea sandstone core and yields surface relaxivity ρ2 consistent with the literature.

Pressure-driven suspension flow near jamming.

We report here magnetic resonance imaging measurements performed on suspensions with a bulk solid volume fraction (ϕ_{0}) up to 0.55 flowing in a pipe. We visualize and quantify spatial distributions of ϕ and velocity across the pipe at different axial positions. For dense suspensions (ϕ_{0}>0.5), we found a different behavior compared to the known cases of lower ϕ_{0}. Our experimental results demonstrate compaction within the jammed region (characterized by a zero macroscopic shear rate) from the jamming limit ϕ_{m}≈0.58 at its outer boundary to the random close packing limit ϕ_{rcp}≈0.64 at the center. Additionally, we show that ϕ and velocity profiles can be fairly well captured by a frictional rheology accounting for both further compaction of jammed regions as well as normal stress differences.

In situ measurement and simulation of nano-magnetite mobility in porous media subject to transient salinity.

Nanotechnologies have been proposed for a variety of environmental applications, including subsurface characterization, enhanced oil recovery, and in situ contaminant remediation. For such applications, quantitative predictive models will be of great utility for system design and implementation. Electrolyte chemistry, which can vary substantially within subsurface pore waters, has been shown to strongly influence nanoparticle aggregation and deposition in porous media. Thus, it is essential that mathematical models be capable of tracking changes in electrolyte chemistry and predicting its influence on nanoparticle mobility. In this work, a modified version of a multi-dimensional multispecies transport simulator (SEAWAT) was employed to model nanoparticle transport under transient electrolyte conditions. The modeling effort was supported by experimental measurements of paramagnetic magnetite (Fe3O4) nanoparticle, coated with polyacrylamide-methylpropane sulfonic acid - lauryl acrylate (nMag-PAMPS), mobility in columns packed with 40-50 mesh Ottawa sand. Column effluent analyses and magnetic resonance imaging (MRI) were used to quantify nanoparticle breakthrough and in situ aqueous phase concentrations, respectively. Experimental observations revealed that introduction of de-ionized water into the brine saturated column (80 g L(-1) NaCl + 20 g L(-1) CaCl2) promoted release and remobilization of deposited nanoparticles along a diagonal front, coincident with the variable density flow field. This behavior was accurately captured by the simulation results, which indicated that a two-site deposition-release model provided the best fit to experimental observations, suggesting that heterogeneous nanoparticle-surface interactions governed nanoparticle attachment. These findings illustrate the importance of accounting for both physical and chemical processes associated with changes in electrolyte chemistry when predicting nanoparticle transport behavior in subsurface formations.