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We study molecular diffusion in linear nanopores with different types of roughness in the so-called Knudsen regime. Knudsen diffusion represents the limiting case of molecular diffusion in pores, where mutual encounters of the molecules…

Disordered Systems and Neural Networks · Physics 2007-05-23 S. Zschiegner , S. Russ , A. Bunde , J. Kärger

Two dimensional nuclear magnetic resonance (NMR) spectroscopy is one of the major tools for analysing the chemical structure of organic molecules and proteins. Despite its power, this technique requires long measurement times, which,…

We propose a novel approach to denoising diffusion magnetic resonance images (dMRI) using convolutional neural networks, that exploits the benefits of data acquired at multiple b-values to offset the need for many redundant observations.…

Image and Video Processing · Electrical Eng. & Systems 2024-10-23 Jakub Jurek , Andrzej Materka , Kamil Ludwisiak , Agata Majos , Filip Szczepankiewicz

We develop a general analytical and numerical framework for estimating intra- and extra-neurite water fractions and diffusion coefficients, as well as neurite orientational dispersion, in each imaging voxel. By employing a set of rotational…

Biological Physics · Physics 2018-04-10 Dmitry S. Novikov , Jelle Veraart , Ileana O. Jelescu , Els Fieremans

Nuclear magnetic resonance is widely used as a probe of pore geometry and fluid composition in well logging. One of the critical assumptions often made is that the diffusion of fluid molecules is sufficiently fast to warrant the condition…

Other Condensed Matter · Physics 2009-06-30 Seungoh Ryu

We study pore nucleation in a model membrane system, a freestanding polymer film. Nucleated pores smaller than a critical size close, while pores larger than the critical size grow. Holes of varying size were purposefully prepared in liquid…

Soft Condensed Matter · Physics 2017-01-04 Mark Ilton , Christian DiMaria , Kari Dalnoki-Veress

In this work we demonstrate the efficacy of neural networks in the characterization of dispersive media. We also develop a neural network to make predictions for input probe pulses which propagate through a nonlinear dispersive medium,…

Optics · Physics 2019-12-02 Sanjaya Lohani , Erin M. Knutson , Wenlei Zhang , Ryan T. Glasser

Diffusion-weighted magnetic resonance imaging (DW-MRI) can be used to characterise the microstructure of the nervous tissue, e.g. to delineate brain white matter connections in a non-invasive manner via fibre tracking. Magnetic Resonance…

Small volume nuclear magnetic resonance spectroscopy (NMR) has recently made considerable progress due to rapid developments in the field of quantum sensing using nitrogen vacancy (NV) centers. These optically active defects in the diamond…

Quantum Physics · Physics 2021-11-19 Fleming Bruckmaier , Karl Briegel , Dominik B. Bucher

Nuclear magnetic resonance (NMR) has enormous applications. Two-dimensional NMR is an essential technique to characterize correlations between nuclei and, hence, molecule structures. Towards the ultimate goal of single-molecule NMR,…

Quantum Physics · Physics 2016-11-30 Wen-Long Ma , Ren-Bao Liu

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a non-invasive way of imaging white matter tracts in the human brain. DW-MRIs are usually acquired using echo-planar imaging (EPI) with high gradient fields, which could introduce…

Image and Video Processing · Electrical Eng. & Systems 2023-04-04 Zhangxing Bian , Muhan Shao , Aaron Carass , Jerry L. Prince

Magnetic resonance imaging, based on the manipulation and detection of nuclear spins, is a powerful imaging technique that typically operates on the scale of millimeters to microns. Using magnetic resonance force microscopy, we have…

Other Condensed Matter · Physics 2007-06-27 H. J. Mamin , M. Poggio , C. L. Degen , D. Rugar

Nuclear Magnetic Resonance (NMR) spans diverse fields from biology to quantum science. Employing NMR on a floating object could unveil novel possibilities beyond conventional operational paradigms. Here, we observe Nuclear Magnetic…

Quantum Physics · Physics 2024-07-30 J. Voisin , A. Durand , T. Copie , M. Perdriat , G. Hétet

The diffusion of particles trapped in long narrow channels occurs predominantly in one dimension. Here, molecular dynamics simulation is used to study the inertial dynamics of two-dimensional hard disks, confined to long, narrow,…

Soft Condensed Matter · Physics 2020-02-05 Mahdi Zarif , Richard K. Bowles

Dynamic nuclear polarization (DNP) is an NMR hyperpolarization technique that mediates polarization transfer from highly polarized unpaired electrons to NMR-active nuclei via microwave (mw) irradiation. The ability to generate arbitrarily…

Diffusion probabilistic models (DPMs) have exhibited significant effectiveness in computer vision tasks, particularly in image generation. However, their notable performance heavily relies on labelled datasets, which limits their…

Computer Vision and Pattern Recognition · Computer Science 2024-05-09 Keqiang Fan , Xiaohao Cai , Mahesan Niranjan

Nanomechanical resonators (NMRs), as the quantum mechanical sensing probers, have played the important roles for various high-precision quantum measurements. Differing from the previous emission spectral probes (i.e., the NMR modified the…

Quantum Physics · Physics 2022-10-25 Haiyan Gao , Lianfu Wei

Recently, diffusion models (DM) have been applied in magnetic resonance imaging (MRI) super-resolution (SR) reconstruction, exhibiting impressive performance, especially with regard to detailed reconstruction. However, the current DM-based…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Guangyuan Li , Chen Rao , Juncheng Mo , Zhanjie Zhang , Wei Xing , Lei Zhao

Diffusion-based image super-resolution (SR) aims to reconstruct high-resolution (HR) images from low-resolution (LR) observations. However, the inherent randomness injected during the reverse diffusion process causes the performance of…

Computer Vision and Pattern Recognition · Computer Science 2026-04-15 Shuwei Huang , Shizhuo Liu , Zijun Wei

The mechanical properties of soft materials can be probed on small length scales by various microrheology methods. A common approach tracks fluctuations of micrometer-sized beads embedded in the medium to be characterized. This approach…

Soft Condensed Matter · Physics 2021-10-13 Kengo Nishi , Fred C. MacKintosh , Christoph F. Schmidt
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