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Tkachenko, Nikolay V.

Publications and source records attributed to Tkachenko, Nikolay V..

3 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

High-temperature carbon dioxide capture in a porous material with terminal zinc hydride sites

Carbon capture can mitigate point-source carbon dioxide (CO 2 ) emissions, but hurdles remain that impede the widespread adoption of amine-based technologies. Capturing CO 2 at temperatures closer to those of many industrial exhaust streams (>200°C) is of interest, although metal oxide absorbents that operate at these temperatures typically exhibit sluggish CO 2 absorption kinetics and instability to cycling. Here, in this study, we report a porous metal–organic framework featuring terminal zinc hydride sites that reversibly bind CO 2 at temperatures above 200°C—conditions that are unprecedented for intrinsically porous materials. Gas adsorption, structural, spectroscopic, and computational analyses elucidate the rapid, reversible nature of this transformation. Extended cycling and breakthrough analyses reveal that the material is capable of deep carbon capture at low CO 2 concentrations and high temperatures relevant to postcombustion capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Quantum Davidson algorithm for excited states

Abstract Excited state properties play a pivotal role in various chemical and physical phenomena, such as charge separation and light emission. However, the primary focus of most existing quantum algorithms has been the ground state, as seen in quantum phase estimation and the variational quantum eigensolver (VQE). Although VQE-type methods have been extended to explore excited states, these methods grapple with optimization challenges. In contrast, the quantum Krylov subspace (QKS) method has been introduced to address both ground and excited states, positioning itself as a cost-effective alternative to quantum phase estimation. However, conventional QKS methodologies depend on a pre-generated subspace through real or imaginary-time evolutions. This subspace is inherently expansive and can be plagued with issues like slow convergence or numerical instabilities, often leading to relatively deep circuits. Our research presents an economic QKS algorithm, which we term the quantum Davidson (QDavidson) algorithm. This innovation hinges on the iterative expansion of the Krylov subspace and the incorporation of a pre-conditioner within the Davidson framework. By using the residues of eigenstates to expand the Krylov subspace, we manage to formulate a compact subspace that aligns closely with the exact solutions. This iterative subspace expansion paves the way for a more rapid convergence in comparison to other QKS techniques, such as the quantum Lanczos. Using quantum simulators, we employ the novel QDavidson algorithm to delve into the excited state properties of various systems, spanning from the Heisenberg spin model to real molecules. Compared to the existing QKS methods, the QDavidson algorithm not only converges swiftly but also demands a significantly shallower circuit. This efficiency establishes the QDavidson method as a pragmatic tool for elucidating both ground and excited state properties on quantum computing platforms.

97 MATHEMATICS AND COMPUTING↗