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The symmetry-broken correlated states in twisted double bilayer graphene (TDBG) can be tuned via several external knobs, including twist angle, displacement field, and carrier density. However, a direct, momentum-resolved characterization…
We demonstrate a photonic analog of twisted bilayer graphene that has ultra-flat photonic bands and exhibits extreme slow light behavior. Our twisted bilayer photonic device, which has an operating wavelength in C-band of the telecom…
Atomic defects underpin the properties of van der Waals materials, and their understanding is essential for advancing quantum and energy technologies. Scanning transmission electron microscopy is a powerful tool for defect identification in…
Accurately determining fluid viscosity is crucial for various industrial and scientific applications. Traditional methods of viscosity measurement, though reliable, often require manual intervention and cannot easily adapt to real-time…
Moir\'e superlattices (MSL) formed in angle-aligned bilayers of van der Waals materials have become a promising platform to realize novel two-dimensional electronic states. Angle-aligned trilayer structures can form two sets of MSLs which…
In a groundbreaking experimental advance it was recently shown that by stacking two sheets of graphene atop of each other at a twist angle close to one of the so called "magic angles", an effective two-dimensional correlated system emerges.…
We present a novel interpretable machine learning model to accurately predict complex rippling deformations of Multi-Walled Carbon Nanotubes(MWCNTs) made of millions of atoms. Atomistic-physics-based models are accurate but computationally…
The observation of flat energy bands in transition metal dichalcogenide bilayers such as twisted WSe${}_2$ makes those materials interesting prospects for reproducing the behavior observed in graphene-based systems. We use an effective…
Homogenization is a technique commonly used in multiscale computational science and engineering for predicting collective response of heterogeneous materials and extracting effective mechanical properties. In this paper, a three-dimensional…
Experimental demonstrations of tunable correlation effects in magic-angle twisted bilayer graphene have put two-dimensional moir\'e quantum materials at the forefront of condensed-matter research. Other twisted few-layer graphitic…
A galaxy's morphological features encode details about its gas content, star formation history, and feedback processes, which play important roles in regulating its growth and evolution. We use deep convolutional neural networks (CNNs) to…
The ability in experiments to control the relative twist angle between successive layers in two-dimensional (2D) materials offers a new approach to manipulating their electronic properties; we refer to this approach as "twistronics". A…
Semiconducting transition metal dichalcogenides (TMDs) combine strong light-matter interaction with good chemical stability and scalable fabrication techniques, and are thus excellent prospects for optoelectronic, photonic and…
The study of twisted two-dimensional (2D) materials, where twisting layers create moir\'e superlattices, has opened new opportunities for investigating topological phases and strongly correlated physics. While systems such as twisted…
Imaging through scattering is an important, yet challenging problem. Tremendous progress has been made by exploiting the deterministic input-output "transmission matrix" for a fixed medium. However, this "one-to-one" mapping is highly…
Twisted bilayer graphene exhibits electronic properties that are highly correlated with the size and arrangement of moir\'e patterns. While rigid rotation of two layers creates the topology of moir\'e patterns, local rearrangements of the…
Deep learning algorithms offer a powerful means to automatically analyze the content of medical images. However, many biological samples of interest are primarily transparent to visible light and contain features that are difficult to…
In Bragg Coherent Diffraction Imaging (BCDI), Phase Retrieval of highly strained crystals is often challenging with standard iterative algorithms. This computational obstacle limits the potential of the technique as it precludes the…
Two-dimensional (2D) atomic crystals, such as graphene and transition-metal dichalcogenides, have emerged as a new class of materials with remarkable physical properties. In contrast to graphene, monolayer MoS2 is a non-centrosymmetric…
Tiered graph autoencoders provide the architecture and mechanisms for learning tiered latent representations and latent spaces for molecular graphs that explicitly represent and utilize groups (e.g., functional groups). This enables the…