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Zhang, Feng

Publications and source records attributed to Zhang, Feng.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The widespread IS200/IS605 transposon family encodes diverse programmable RNA-guided endonucleases

Tracing the origin of CRISPR-Cas CRISPR-Cas systems have transformed genome editing and other biotechnologies; however, the broader origins and diversity of RNA-guided nucleases have largely remained unexplored. Altae-Tran et al . show that three distinct transposon-encoded proteins, IscB, IsrB, and TnpB, are naturally occurring, reprogrammable RNA-guided DNA nucleases (see the Perspective by Rousset and Sorek). In addition to identifying diverse guide-encoding mechanisms, the authors elucidate the evolutionary relationship between IsrB, IscB, and CRISPR-Cas9. Overall, these newly characterized systems, called OMEGA (for obligate mobile element–guided activity) systems, are found in all domains of life and may be harnessed for biotechnology development. —DJ

Science & Technology - Other Topics↗
DOE OSTI2021

Adaptive variational quantum eigensolvers for highly excited states

Highly excited states of quantum many-body systems are central objects in the study of quantum dynamics and thermalization that challenge classical computational methods due to their volume-law entanglement content. In this work, we explore the potential of variational quantum algorithms to approximate such states. We propose an adaptive variational quantum eigensolver (VQE) for excited states (X) that self-generates a variational ansatz for arbitrary eigenstates of a many-body Hamiltonian H by attempting to minimize the energy variance with respect to H. We benchmark the method by applying it to an Ising spin chain with integrable and nonintegrable regimes, where we calculate various quantities of interest, including the total energy, magnetization density, and entanglement entropy. We also compare the performance of adaptive VQE-X to an adaptive variant of the folded-spectrum method. For both methods, we find a strong dependence of the algorithm's performance on the choice of operator pool used for the adaptive construction of the ansatz. In particular, an operator pool including long-range two-body gates accelerates the convergence of both algorithms in the nonintegrable regime. Here, we also study the scaling of the number of variational parameters with system size, finding that an exponentially large number of parameters may be necessary to approximate individual highly excited states. Nevertheless, we argue that these methods lay a foundation for the use of quantum algorithms to study finite-energy-density properties of many-body systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Unveiling the mechanism of phase and morphology selections during the devitrification of Al-Sm amorphous ribbon

The complex interplay between energetic and kinetic factors that governs the phase and morphology selections can originate at the earliest stage of crystallization in the amorphous parent phases. Because of the extreme difficulties in capturing the microscopic nucleation process, a detailed picture of how initial disordered structures affect the transformation pathway remains unclear. Here, we report the experimental observation of widely varying phase selection and grain size evolution during the devitrification of a homogeneous melt-spun glassy ribbon. Two different crystalline phases, θ-Al 5 Sm and ε-Al 60 Sm 11 , are found to form in the different regions of the same metallic glass ribbon during the devitrification. The grain size of ε-Al 60 Sm 11 phase shows a strong spatial heterogeneity. Coarse-grained ε-Al 60 Sm 11 phase coupled with the small volume fraction of θ-Al 5 Sm phase is preferably formed close to wheel side of the melt-spun ribbon. Combining experimental characterization and computational simulations, we show that phase selection and microstructure evolution can be traced back to different types and populations of atomic clusters that serve as precursors for the nucleation of different crystalline phases. Inhomogeneous cooling rates cause different structure orders across the glass sample during the quenching process. Our findings provide direct insight into the effect of structural order on the crystallization pathways during the devitrification of metallic glass. It also opens an avenue to study the detailed nucleation process at the atomic level using the metallic glass as a platform and suggests the opportunity of microstructure and property design via controlling the cooling process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Effect of Ni particle size on the production of renewable methane from CO 2 over Ni/CeO 2 catalyst

Production of ‘renewable Methane’ has attracted renewed research interest as a fundamental probe reaction and process for CO 2 utilization through potential use in C1 fuel production and even for future space exploration technologies. CO 2 methanation is a structure sensitive reaction on Ni/CeO 2 catalysts. To precisely elucidate the size effect of the Ni metal center on the CO 2 methanation performance, we prepared 2%Ni/CeO 2 catalysts with pre-synthesized uniform Ni particles (2, 4 and 8 nm) on a high surface area CeO 2 support. Transmission electron microscopy (TEM) and ambient pressure X-ray photo spectroscopy (AP-XPS) characterization have confirmed that the catalyst structure and chemical state was uniform and stable under reaction conditions. The 8 nm sized catalyst showed superior methanation selectivity over the 4 and 2 nm counterparts, and the methanation activity in term of TOF is 10 times and 70 times higher than for the 4 and 2 nm counterparts, respectively. Here, the DRIFTS studies revealed that the larger Ni (8 nm particles) over CeO 2 efficiently facilitated the hydrogenation of the surface formate intermediates, which is proposed as the rate determining step accounting for the excellent CO 2 methanation performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Gutzwiller hybrid quantum-classical computing approach for correlated materials

Rapid progress in noisy intermediate-scale quantum (NISQ) computing technology has led to the development of novel resource-efficient hybrid quantum-classical algorithms, such as the variational quantum eigensolver (VQE), that can address open challenges in quantum chemistry, physics, and material science. Proof-of-principle quantum chemistry simulations for small molecules have been demonstrated on NISQ devices. While several approaches have been theoretically proposed for correlated materials, NISQ simulations of interacting periodic models on current quantum devices have not yet been demonstrated. Here, we develop a hybrid quantum-classical simulation framework for correlated electron systems based on the Gutzwiller variational embedding approach. We implement this framework on Rigetti quantum processing units (QPUs) and apply it to the periodic Anderson model, which describes a correlated heavy electron band hybridizing with noninteracting conduction electrons. Our simulation results quantitatively reproduce the known ground state quantum phase diagram including metallic, Kondo and Mott insulating phases. This is the first fully self-consistent hybrid quantum-classical simulation of an infinite correlated lattice model executed on QPUs, demonstrating that the Gutzwiller hybrid quantum-classical embedding framework is a powerful approach to simulate correlated materials on NISQ hardware. This benchmark study also puts forth a concrete pathway towards practical quantum advantage on NISQ devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Crystallization of the P 3 Sn 4 Phase upon Cooling P 2 Sn 5 Liquid by Molecular Dynamics Simulation Using a Machine Learning Interatomic Potential

We performed molecular dynamics simulations to study the crystallization of the P3Sn4 phase from P 2 Sn 5 liquid using a machine learning (ML) interatomic potential with desirable efficiency and accuracy. Our results capture the liquid properties of P 2 Sn 5 at 1300 K, which is well above the melting temperature. The phase separation and crystallization are observed when P 2 Sn 5 liquid is cooled down below 832 and 505 K, respectively. The simulation results are in good agreement with the experimentally observed phase transformation behaviors and provide useful insights into the complex nucleation and crystallization process at the details of atomistic scale. Our work also demonstrated that ML interatomic potentials based on neural network deep learning are robust and capable of accurately describing the energetics and kinetics of complex materials through molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Modulation of the Effective Metal-Support Interactions for the Selectivity of Ceria Supported Noble Metal Nanoclusters in Atmospheric CO 2 Hydrogenation

Ever-increasing attention is given to the sustainable utilization of CO 2 in the atmosphere out of environmental and economic considerations. The deep-going clarification of the effective and ineffective metal-support interactions (MSI) in the supported catalysts for the catalytic performance of CO 2 hydrogenation is particularly needed to design highly active nanocatalysts. How to tune the MSI to be effective for the selectivity of goal hydrogenation products is a significant but rather challenging subject. In this work, we demonstrate that the selectivity in CO 2 hydrogenation can be regulated from preferential CH 4 production to preferential CO production by varying the nature of the electronic MSI for ceria supported noble metal nanoclusters, and the effective MSI play a pivotal role for the catalytic systems with opposite hydrogenation selectivity. The modulation of the effective MSI for the selectivity in CO 2 hydrogenation sheds new light on the comprehensive understanding of the MSI and interfacial effects in terms of tailoring and controlling the performance of supported heterogeneous catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Inverse ZrO 2 /Cu as a highly efficient methanol synthesis catalyst from CO 2 hydrogenation

Enhancing the intrinsic activity and space time yield of Cu based heterogeneous methanol synthesis catalysts through CO 2 hydrogenation is one of the major topics in CO 2 conversion into value-added liquid fuels and chemicals. Here we report inverse ZrO 2 /Cu catalysts with a tunable Zr/Cu ratio have been prepared via an oxalate co-precipitation method, showing excellent performance for CO 2 hydrogenation to methanol. Under optimal condition, the catalyst composed by 10% of ZrO 2 supported over 90% of Cu exhibits the highest mass-specific methanol formation rate of 524 g MeOH kg cat -1 h -1 at 220°C, 3.3 times higher than the activity of traditional Cu/ZrO 2 catalysts (159 g MeOH kg cat -1 h -1 ). In situ XRD-PDF, XAFS and AP-XPS structural studies reveal that the inverse ZrO 2 /Cu catalysts are composed of islands of partially reduced 1–2 nm amorphous ZrO 2 supported over metallic Cu particles. The ZrO 2 islands are highly active for the CO 2 activation. Meanwhile, an intermediate of formate adsorbed on the Cu at 1350 cm -1 is discovered by the in situ DRIFTS. This formate intermediate exhibits fast hydrogenation conversion to methoxy. The activation of CO 2 and hydrogenation of all the surface oxygenate intermediates are significantly accelerated over the inverse ZrO 2 /Cu configuration, accounting for the excellent methanol formation activity observed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Breaking Simple Scaling Relations through Metal–Oxide Interactions: Understanding Room-Temperature Activation of Methane on M/CeO 2 (M = Pt, Ni, or Co) Interfaces

The clean activation of methane at low temperatures remains an eminent challenge and a field of competitive research. In particular, on late transition metal surfaces such as Pt(111) or Ni(111), higher temperatures are necessary to activate the hydrocarbon molecule, but a massive deposition of carbon makes the metal surface useless for catalytic activity. However, on very low-loaded M/CeO 2 (M = Pt, Ni, or Co) surfaces, the dissociation of methane occurs at room temperature, which is unexpected considering simple linear scaling relationships. This intriguing phenomenon has been studied using a combination of experimental techniques (ambient-pressure X-ray photoelectron spectroscopy, time-resolved X-ray diffraction, and X-ray absorption spectroscopy) and density functional theory-based calculations. The experimental and theoretical studies show that the size and morphology of the supported nanoparticles together with strong metal–support interactions are behind the deviations from the scaling relations. These findings point toward a possible strategy for circumventing scaling relations, producing active and stable catalysts that can be employed for methane activation and conversion.

03 NATURAL GAS↗
DOE OSTI2020

Efficient Step-Merged Quantum Imaginary Time Evolution Algorithm for Quantum Chemistry

In this work, we develop a resource-efficient step-merged quantum imaginary time evolution approach (smQITE) to solve for the ground state of a Hamiltonian on quantum computers. This heuristic method features a fixed shallow quantum circuit depth along the state evolution path. We use this algorithm to determine the binding energy curves of a set of molecules, including H 2 , H 4 , H 6 , LiH, HF, H 2 O, and BeH 2 , and find highly accurate results. The required quantum resources of smQITE calculations can be further reduced by adopting the circuit form of the variational quantum eigensolver (VQE) technique, such as the unitary coupled cluster ansatz. We demonstrate that smQITE achieves a similar computational accuracy as VQE at the same fixed-circuit ansatz, without requiring a generally complicated high-dimensional nonconvex optimization. Finally, smQITE calculations are carried out on Rigetti quantum processing units, demonstrating that the approach is readily applicable on current noisy intermediate-scale quantum devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

An efficient random-sampling method for calculating double occupancy of Gutzwiller wave function in single-band 1D and 2D lattices

In this paper, we report a random sampling method for computing the expectation value of physical quantities based on the Gutzwiler variational wave function. As the first application, we calculated the double occupancy, which is a critical quantity for under- standing the correlation effects in many-body systems, for single-band 1D and 2D lattices. We demonstrated that the random sampling scheme is more efficient than an existing Metropolis Monte-Carlo algorithm. For the 1D Hubbard model with only nearest-neighbor hopping, our results are almost identical to the exact analytic solution. We have also studied systems to which analytic solutions are not available, including the 1D lattices with next-nearest-neighbor hopping and 2D lattices. In addition, constraints on real-space con gurations can be easily implemented in the current scheme to further improve the Gutzwiller wave function. As an example, we calculated the double occupancy for 1D Hubbard model by applying the constraint that all double-occupied sites are paired with an empty site. With enhanced correlation between double-occupied and empty sites, the constraint results in much improved ground-state energy for 1D Hubbard model with strong on-site repulsion.

74 ATOMIC AND MOLECULAR PHYSICS↗