Nanette N. Jarenwattananon

Thermal Maps of Gases in Heterogeneous Reactions

More than 85 per cent of all chemical industry products are made using catalysts, the overwhelming majority of which are heterogeneous catalysts that function at the gas–solid interface. Consequently, much effort is invested in optimizing the design of catalytic reactors, usually by modelling the coupling between heat transfer, fluid dynamics and surface reaction kinetics. The complexity involved requires a calibration of model approximations against experimental observations, with temperature maps being particularly valuable because temperature control is often essential for optimal operation and because temperature gradients contain information about the energetics of a reaction. However, it is challenging to probe the behaviour of a gas inside a reactor without disturbing its flow, particularly when trying also to map the physical parameters and gradients that dictate heat and mass flow and catalytic efficiency. Although optical techniques and sensors have been used for that purpose, the former perform poorly in opaque media and the latter perturb the flow. NMR thermometry can measure temperature non-invasively, but traditional approaches applied to gases produce signals that depend only weakly on temperature are rapidly attenuated by diffusion or require contrast agents that may interfere with reactions. Here we present a new NMR thermometry technique that circumvents these problems by exploiting the inverse relationship between NMR linewidths and temperature caused by motional averaging in a weak magnetic field gradient. We demonstrate the concept by non-invasively mapping gas temperatures during the hydrogenation of propylene in reactors packed with metal nanoparticles and metal–organic framework catalysts, with measurement errors of less than four per cent of the absolute temperature. These results establish our technique as a non-invasive tool for locating hot and cold spots in catalyst-packed gas–solid reactors, with unprecedented capabilities for testing the approximations used in reactor modelling.

NMR probe of metallic states in nanoscale topological insulators

A 125Te NMR study of bismuth telluride nanoparticles as a function of particle size revealed that the spin-lattice relaxation is enhanced below 33 nm, accompanied by a transition of NMR spectra from the single to the bimodal regime. The satellite peak features a negative Knight shift and higher relaxivity, consistent with core polarization from p-band carriers. Whereas nanocrystals follow a Korringa law in the range 140-420 K, micrometer particles do so only below 200 K. The results reveal increased metallicity of these nanoscale topological insulators in the limit of higher surface-to-volume ratios.

Feature-Preserving Noise Removal

Conventional image restoration algorithms use transform-domain filters, which separate the noise from the sparse signal among the transform components or apply spatial smoothing filters in real space whose design relies on prior assumptions about the noise statistics. These filters also reduce the information content of the image by suppressing spatial frequencies or by recognizing only a limited set of shapes. Here we show that denoising can be efficiently done using a nonlinear filter, which operates along patch neighborhoods and multiple copies of the original image. The use of patches enables the algorithm to account for spatial correlations in the random field whereas the multiple copies are used to recognize the noise statistics. The nonlinear filter, which is implemented by a hierarchical multistage system of multilayer perceptrons, outperforms state-of-the-art denoising algorithms such as those based on collaborative filtering and total variation. Compared to conventional denoising algorithms, our filter can restore images without blurring them, making it attractive for use in medical imaging where the preservation of anatomical details is critical.

Motional averaging of nuclear resonance in a field gradient.

The traditional view of nuclear-spin decoherence in a field gradient due to molecular self-diffusion is challenged on the basis of temperature dependence of the linewidth, which demonstrates different behaviors between liquids and gases. The conventional theory predicts that in a fluid, linewidth should increase with temperature; however, in gases we observed the opposite behavior. This surprising behavior can be explained using a more detailed theoretical description of the dephasing function that accounts for position autocorrelation effects.

Breakdown of Carr-Purcell Meiboom-Gill spin echoes in inhomogeneous fields

The Carr-Purcell Meiboom-Gill (CPMG) experiment has been used for decades to measure nuclear-spin transverse (T2) relaxation times. In the presence of magnetic field inhomogeneities, the limit of short interpulse spacings yields the intrinsic T2 time. Here, we show that the signal decay in such experiments exhibits fundamentally different behaviors between liquids and gases. In gases, the CPMG unexpectedly fails to eliminate the inhomogeneous broadening due to the non-Fickian nature of the motional averaging.

4-D Flow Control in Porous Scaffolds: Toward a Next Generation of Bioreactors

Tissue engineering (TE) approaches that involve seeding cells into predetermined tissue scaffolds ignore the complex environment where the material properties are spatially inhomogeneous and evolve over time. We present a new approach for controlling mechanical forces inside bioreactors, which enables spatiotemporal control of flow fields in real time. Our adaptive approach offers the flexibility of dialing-in arbitrary shear stress distributions and adjusting flow field patterns in a scaffold over time in response to cell growth without needing to alter scaffold structure. This is achieved with a multi-inlet bioreactor and a control algorithm with learning capabilities to dynamically solve the inverse problem of computing the inlet pressure distribution required over the multiple inlets to obtain a target flow field. The new method constitutes a new platform for studies of cellular responses to mechanical forces in complex environments and opens potentially transformative possibilities for TE.