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The phase change compound Ge$_2$Sb$_2$Te$_5$ (GST225) is exploited in advanced non-volatile electronic memories and in neuromorphic devices which both rely on a fast and reversible transition between the crystalline and amorphous phases…
Metal atoms and small clusters introduced into superfluid helium (He II) concentrate there in quantized vortices to form (by further coagulation) the thin nanowires. The nanowires' thickness and structure are well predicted by a…
In this communication,we propose a sustainable way to produce high entropy alloys from alloy scraps called Alloy mixing.We successfully demonstrate this method using a near equimolar CrCuFeMnNi HEA. Alloy scraps (304L stainless steel,…
Composite joints with high-performance close to the parent materials of aluminum matrix composites were fabricated by a new joining technology assisted by ultrasonic vibration. We found both the microstructure and the mechanical performance…
We present a room-temperature Extreme High Vacuum (XHV) system engineered to support the long-duration operation of a trapped-ion quantum processor. Background-gas collisions impose limitations on trapped-ion performance and scalability by…
Decades accumulation of theory simulations lead to boom in material database, which combined with machine learning methods has been a valuable driver for the data-intensive material discovery, i.e., the fourth research paradigm. However,…
We present a general-purpose machine learning (ML) interatomic potential for carbon and hydrogen which is capable of simulating various materials and molecules composed of these elements. This ML interatomic potential is trained using the…
Uranium mononitride (UN) is a promising accident-tolerant fuel because of its high fissile density and high thermal conductivity. In this study, we developed the first machine learning interatomic potentials for reliable atomic-scale…
Methane (CH4) and nitrous oxide (N2O) are potent greenhouse gases that represent substantial chemical energy. Conversion of these abundant waste gases to high-value chemicals typically requires high temperatures up to 1000 C, producing…
Two-dimensional superconductors attract great interest both for their fundamental physics and for their potential applications, especially in the rapidly growing field of quantum computing. Despite intense theoretical and experimental…
Two-dimensional semiconducting transition metal dichalcogenides embedded in optical microcavities in the strong exciton-photon coupling regime may lead to promising applications in spin and valley addressable polaritonic logic gates and…
High-entropy alloys, near-equiatomic solid solutions of five or more elements, represent a new strategy for the design of materials with properties superior to those of conventional alloys. However, their phase space remains constrained,…
In Inertial Confinement Fusion (ICF) process, roughly a 2mm spherical shell made of high density carbon is used as target for laser beams, which compress and heat it to energy levels needed for high fusion yield. These shells are polished…
Here we demonstrate the selective bulk scale synthesis of delaminated graphene sheets by a proper choice of magnetic field modulating an electric-arc. An ultra-high purity glassy graphite anode was sublimated in an argon atmosphere. Carbon…
Icy interstellar dust grains are a source of complex organic molecule (COM) production, although their formation mechanisms are debated. Laboratory experiments show that atomic C deposited onto interstellar ice analogs can react with…
Efficient synthesis recipes are needed both to streamline the manufacturing of complex materials and to accelerate the realization of theoretically predicted materials. Oftentimes the solid-state synthesis of multicomponent oxides is…
We propose a simple scheme to construct composition-dependent interatomic potentials for multicomponent systems that when superposed onto the potentials for the pure elements can reproduce not only the heat of mixing of the solid solution…
We propose an approach to materials prediction that uses a machine-learning interatomic potential to approximate quantum-mechanical energies and an active learning algorithm for the automatic selection of an optimal training dataset. Our…
Constant ingress of impurities in Muon Campus g-2 experiment at Fermilab has resulted in reduction of efficiency of cryogenic expanders and occasional undesired downtime to flush the impurities. Due to insufficiency of current 60 g/s mobile…
High-pressure powder x-ray diffraction experiments have revealed that sodium and gold react at room temperature and form new Na-Au intermetallic compounds under high pressure. We have identified four intermetallic phases up to 60 GPa. The…