Conventional NMR is inherently limited in its extension to applications at very small length scales and on devices with unusual geometric properties. This is because, in conventional NMR, the same inductive coil is used to both encode and detect the NMR signal, which requires a compromise between encoding and detection and prohibits optimization of each process. For instance, the need to use a single large coil to encode all of the information on a microfluidic device compromises the sensitivity with which that signal may be detected. With remote detection these parameters can be chosen with unprecedented flexibility compared to a conventional NMR experiment. An NMR active sensor is used to survey a chemical environment and retains the information in its magnetic properties, to be recovered at a later time and location. The encoding and detection steps are physically separated, thus distancing excitation and evolution from the acquisition of signal in both the time and space. This allows for separate optimization of parameters that influence the quality of the data, such as field strength, coil size and geometry, receiver bandwidth, and even the type of detector(1). Moreover, remote detection permits the flexibility to use more sensitive detectors, such as micropatterned inductive coils, alkali-vapor magnetometers, or NV diamond magnetometers.
Remote detection experiments work by using a sensing medium that can store information as magnetization. For instance, a porous sample may be studied by placing the sample in an NMR magnet equipped with magnetic field gradients and flowing the sensor medium (e.g. 129Xe, H2O, etc) through the sample. As the sensor interacts with the sample, an optimized induction coil is use to apply radiofrequency pulses and gradients to select a region of the sample and encode information in magnetization. The sensing medium then travels to a separately optimized detector where the information can be recovered. A travel curve shows how long it takes for the sensing medium to travel to the detection coil. More complex pulse sequences may be implemented to recover spectral or spatial information about the sample or its environment. For instance, pulse sequences may be implemented to determine the geometry of the fluid’s environment or to look at the flow properties of the fluid itself.
Remote detection NMR is particularly useful is applications which already involve the movement of information from one location in space to another. To this end, remote detection has been essential to studies involving hyperpolarized 129Xe gas flowing through sandstone rock(2), aerogels(3), and microfluidic chips(4,5). We have studied the flow and mixing of liquids, such as water and ethanol, in microfluidic devices(6) and high-pressure liquid chromatography (HPLC) columns(7).
Current work in our lab involves the application of remote detection techniques to the development of small, portable, and inexpensive NMR “lab on a chip” devices.
David Wemmer (UC-Berkeley, Chemistry)
Matthew Francis(UC-Berkeley, Chemistry)
 A.J. Moule, M.M. Spence, S.-I. Han, J.A. Seeley, K.L. Pierce, S. Saxena, A. Pines, “Amplification of Xenon NMR and MRI by Remote Detection”, Proceedings of the National Academy of Sciences 100, 9122-9127 (2003).
 J. Granwehr, E. Harel, S.-I. Han, S. Garcia, A. Pines, “Time-of-Flight Flow Imaging Using NMR Remote Detection”, Physical Review Letters 95, 075503/1-4 (2005).
 E. Harel, J. Granwehr, J.A. Seeley, A. Pines, “Multiphase Imaging of Gas Flow in A Nanoporous Material Using Remote-Detection NMR”, Nature Materials 5, 321-327 (2006).
 C. Hilty, E.E. McDonnell, J. Granwehr, K.L. Pierce, S.-I. Han, A. Pines, “Microfluidic Gas-Flow Profiling Using Remote-Detection NMR”, Proceedings of the National Academy of Sciences 102, 14960-14963 (2005).
 E.E. McDonnell, S.-I. Han, C. Hilty, K.L. Pierce, A. Pines, “NMR Analysis on Microfluidic Devices by Remote Detection”, Analytical Chemistry 77(24), 8109-8114 (2005).
 E. Harel, C. Hilty, K. Koen, E.E. McDonnell, A. Pines, “Time-of-Flight Imaging of Two-Component Flow Inside a Microfluidic Chip”, Physical Review Letters 98, 017601 (2007).
 T.Z. Teisseyre, J. Urban, N.W. Halpern-Manners, S.D. Chambers, V.S. Bajaj, F. Sven, A. Pines, “Remotely Detected NMR for the Characterization of Flow and Fast Chromatagraphic Separations Using Organic Polymer Monoliths”, Analytical Chemistry 83(15), 6004-6010 (2011).