Related papers: Microstructural Geometry Revealed by NMR Lineshape…
Understanding the grain morphology, orientation distribution, and crystal structure of nanocrystals is essential for optimizing the mechanical and physical properties of functional materials. Synchrotron X-ray Laue microdiffraction is a…
We demonstrate insights into the three-dimensional structure of defects in graphene, in particular grain boundaries, obtained via a new approach from two transmission electron microscopy images recorded at different angles. The structure is…
We apply a deep convolutional neural network segmentation model to enable novel automated microstructure segmentation applications for complex microstructures typically evaluated manually and subjectively. We explore two microstructure…
Materials characterization remains a significant, time-consuming undertaking. Generally speaking, spectroscopic techniques are used in conjunction with empirical and ab-initio calculations in order to elucidate structure. These experimental…
The practical realization of nano-scale electronics faces two major challenges: the precise engineering of the building blocks and their assembly into functional circuits. In spite of the exceptional electronic properties of carbon…
This paper outlines the science case for line-intensity mapping with a space-borne instrument targeting the sub-millimeter (microwaves) to the far-infrared (FIR) wavelength range. Our goal is to observe and characterize the large-scale…
Deep neural networks can learn powerful prior probability models for images, as evidenced by the high-quality generations obtained with recent score-based diffusion methods. But the means by which these networks capture complex global…
In recent years, diffusion models, and more generally score-based deep generative models, have achieved remarkable success in various applications, including image and audio generation. In this paper, we view diffusion models as an implicit…
We demonstrate a neutron tomography technique with sub-micrometer spatial resolution. Our method consists of measuring neutron diffraction spectra using a double crystal diffractometer as a function of sample rotation and then using a phase…
We introduce the Linearized Diffusion Map (LDM), a novel linear dimensionality reduction method constructed via a linear approximation of the diffusion-map kernel. LDM integrates the geometric intuition of diffusion-based nonlinear methods…
Suspended graphene membrane presents a particular structure with fundamental interests and applications in nanomechanics, thermal transport and optoelectronics. Till now, the commonly used geometries are still quite simple and limited to…
Devices made from two-dimensional (2D) materials such as graphene or transition metal dichalcogenides possess interesting electronic properties that can become accessible to experimental probes when the samples are protected from…
Neutron reflectometry (NR) has emerged as a unique technique for the investigation of structure and magnetism of thin films of both biologically relevant and magnetic materials. The advantage of NR with respect to many other…
We propose a physics-informed machine learning framework called P-DivGNN to reconstruct local stress fields at the micro-scale, in the context of multi-scale simulation given a periodic micro-structure mesh and mean, macro-scale, stress…
Hierarchical biomaterials embody nature's intricate design principles, offering advanced functionalities through the complex, multi-level organization of their molecular and nanosized building blocks. However, the comprehensive…
Properties of crystalline materials are closely linked to microstructure arising from the spatial arrangement, orientation, and phase of nanocrystals. Rapid characterization of crystalline microstructure can accelerate the identification of…
We have extended the utility of NMR as a technique to probe porous media structure over length scales of ~ 100 - 2000 micron by using the spin 1/2 noble gas 129Xe imbibed into the system's pore space. Such length scales are much greater…
We introduce a novel framework that integrates Neural Radiance Fields (NeRF) with Material Point Method (MPM) simulation to infer granular material properties from visual observations. Our approach begins by generating synthetic…
Diffusion magnetic resonance imaging (dMRI) provides a unique tool for noninvasively probing the microstructure of the neuronal tissue. The NODDI model has been a popular approach to the estimation of tissue microstructure in many…
We investigated the atomic structures, Raman spectroscopic and electrical transport properties of individual graphene nanoribbons (GNRs, widths ~10-30 nm) derived from sonochemical unzipping of multi-walled carbon nanotubes (MWNTs).…