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Li, Ying

Publications and source records attributed to Li, Ying.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Error statistics and scalability of quantum error mitigation formulas

Quantum computing promises advantages over classical computing in many problems. Nevertheless, noise in quantum devices prevents most quantum algorithms from achieving the quantum advantage. Quantum error mitigation provides a variety of protocols to handle such noise using minimal qubit resources. While some of those protocols have been implemented in experiments for a few qubits, it remains unclear whether error mitigation will be effective in quantum circuits with tens to hundreds of qubits. In this paper, we apply statistics principles to quantum error mitigation and analyse the scaling behaviour of its intrinsic error. We find that the error increases linearly O(ϵN) with the gate number N before mitigation and sublinearly O(ϵ'N γ ) after mitigation, where γ ≈ 0.5, ϵ is the error rate of a quantum gate, and ϵ' is a protocol-dependent factor. The $\sqrt{N}$ scaling is a consequence of the law of large numbers, and it indicates that error mitigation can suppress the error by a larger factor in larger circuits. We propose the importance Clifford sampling as a key technique for error mitigation in large circuits to obtain this result.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Molecular mechanisms of thickness-dependent water desalination in polyamide reverse-osmosis membranes

Here, using non-equilibrium molecular simulations, we systematically elaborate the relationships among synthesis (membrane's thickness and morphology), atomic-scale transport mechanism, and separation performance (permeability and selectivity) for 3D-printed polyamide (PA) membranes. Results indicated that water diffusion, swelling ratio, water flux, and water permeance proportionally decrease with increasing membrane thickness (4.0–32.5 nm). PA membranes with different thicknesses can achieve almost 100% salt rejection over the simulation time. Importantly, water permeability exponentially decreases with increasing thickness, and 15 nm is identified as the critical membrane thickness for efficient water transport. The discontinuous water-available space spreads all over PA membranes with thicknesses greater than 5 nm, allowing water molecules to jump by way of the temporary open-and-close pores. However, the connected water-useable space exists in PA membranes with thicknesses below 5 nm, offering the continuous channels to dominate water transport. More significantly, pore distribution is more homogeneous as the thickness increases. The applied high pressures can lead to membrane compaction during reverse osmosis and the thicker membranes show a lower compression ratio. In short, these investigations provide molecular insights for effectively designing and manufacturing PA membranes for water desalination and treatment at the molecular level.

42 ENGINEERING↗
DOE OSTI2023

Effect of Diphenyl Content on Viscoelasticity of Poly(dimethyl- co -diphenyl)siloxane Melt and Network

Polydimethylsiloxane (PDMS) is one of the most widely used polymeric materials for sealants, adhesives, lubricants, and thermal as well as electrical insulation. At low temperatures, however, PDMS is subject to crystallization that can cause deterioration in mechanical function. A common way to suppress such crystallization is through the incorporation of phenylsiloxane into the backbone of polysiloxane. Nevertheless, the introduction of phenyl components, even in small quantities, could potentially change the properties of the siloxane in a significant way. In this work, a series of mechanical tests and finite element simulations were performed to study the macroscale viscoelasticity of two poly(dimethyl-co-diphenyl)siloxane formulations in order to understand the effects of a few percent diphenyl contents on the viscoelasticity of the polysiloxane material. Here, we utilized the small-angle X-ray scattering to investigate the microscopic structures of the copolymers and broadband dielectric spectroscopy and rheology to probe the chain dynamics at the microscale. The results of these characterizations were used to inform the finite element simulations. We found that the degree of cross-linking does not significantly alter the microstructure but can profoundly affect the viscoelastic response of the copolymer networks. The corresponding hysteretic behavior is interpreted in terms of reptation-like motion and relaxation of the effective free chains in the cured polymer network. The relaxation of the copolymer chains is slowed significantly by even a small increase in the molar ratio of the diphenyl component.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Modulating Electronic Structure of Atomically Dispersed Nickel Sites through Boron and Nitrogen Dual Coordination Boosts Oxygen Reduction

Abstract Atomically dispersed 3D transitional metal active sites with nitrogen coordination anchored on carbon support have emerged as a kind of promising electrocatalyst toward oxygen reduction reaction (ORR) in the field of fuel cells and metal–air cells. However, it is still a challenge to accurately modulate the coordination structure of single‐atom metal sites, especially first‐shell coordination, as well as identify the relationship between the geometric/electronic structure and ORR performance. Herein, a carbon‐supported single‐atom nickel catalyst is fabricated with boron and nitrogen dual coordination (denoted as Ni‐B/N‐C). The hard X‐ray absorption spectrum result reveals that atomically dispersed Ni active sites are coordinated with one B atom and three N atoms in the first shell (denoted as Ni‐B 1 N 3 ). The Ni‐B/N‐C catalyst exhibits a half‐wave potential ( E 1/2 ) of 0.87 V versus RHE, along with a distinguished long‐term durability in alkaline media, which is superior to commercial Pt/C. Density functional theory calculations indicate that the Ni‐B 1 N 3 active sites are more favorable for the adsorption of ORR intermediates relative to Ni‐N 4 , leading to the reduction of thermodynamic barrier and the acceleration of reaction kinetics, which accounts for the increased intrinsic activity.

Chemistry↗
DOE OSTI2022

Activating Single‐Atom Ni Site via First‐Shell Si Modulation Boosts Oxygen Reduction Reaction

Abstract Atomically dispersed nitrogen‐coordinated 3d transition‐metal site on carbon support (M‐NC) are promising alternatives to Pt group metal‐based catalysts toward oxygen reduction reaction (ORR). However, despite the excellent activities of most of M‐NC catalysts, such as Fe‐NC, Co‐NC et al., their durability is far from satisfactory due to Fenton reaction. Herein, this work reports a novel Si‐doped Ni‐NC catalyst (Ni‐SiNC) that possesses high activity and excellent stability. X‐ray absorption fine structure and aberration‐corrected transmission electron microscopy uncover that the single‐atom Ni site is coordinated with one Si atom and three N atoms, constructing Ni‐Si 1 N 3 moiety. The Ni‐SiNC catalyst exhibits a half‐wave potential (E 1/2 ) of 0.866 V versus RHE, with a distinguished long‐term durability in alkaline media of only 10 mV negative shift in E 1/2 after 35 000 cycles, which is also validated in Zn‐air battery. Density functional theory calculations reveal that the Ni‐Si 1 N 3 moiety facilitates ORR kinetics through optimizing the adsorption of intermediates.

Chemistry↗
DOE OSTI2022

Opening twisted polymer chains for simultaneously high printability and battery fast-charge

Fast-charging is key to the widespread adoption of battery-based electric vehicles. However, improving fast-charging through architecture optimization is expensive. To reduce costs and expand to commercialization, we applied roll-to-roll screen printing technology to create channels and decrease the tortuosity of electrodes. For the first time, this work successfully opened twisted polymer chains within high-solid-content inks to improve their screen printability and battery performance of as-printed electrodes. With LiNi 0.6 Mn 0.2 Co 0.2 O 2 as active materials, the 60% solid content ink presents superior screen printability after opening the twisted binder chains. As-printed electrode exhibits 33% higher charge capacity at 6 C than printed electrode with chains twisted ink at mass loading of 6.5 mg/cm 2 . Furthermore, coarse-grained molecular dynamics simulations are performed to study the underlying mechanism systematically. In conclusion, the new ink preparation procedure provides a scalable, effective strategy for manufacturing screen-printable battery ink and promotes screen-printed electrode technology.

25 ENERGY STORAGE↗
DOE OSTI2022

Super‐Hydrophilic Microporous Ni(OH) x /Ni 3 S 2 Heterostructure Electrocatalyst for Large‐Current‐Density Hydrogen Evolution

Abstract Exploiting active and stable non‐precious metal electrocatalysts for alkaline hydrogen evolution reaction (HER) at large current density plays a key role in realizing large‐scale industrial hydrogen generation. Herein, a self‐supported microporous Ni(OH) x /Ni 3 S 2 heterostructure electrocatalyst on nickel foam (Ni(OH) x /Ni 3 S 2 /NF) that possesses super‐hydrophilic property through an electrochemical process is rationally designed and fabricated. Benefiting from the super‐hydrophilic property, microporous feature, and self‐supported structure, the electrocatalyst exhibits an exceptional HER performance at large current density in 1.0 M KOH, only requiring low overpotential of 126, 193, and 238 mV to reach a current density of 100, 500, and 1000 mA cm −2 , respectively, and displaying a long‐term durability up to 1000 h, which is among the state‐of‐the‐art non‐precious metal electrocatalysts. Combining hard X‐rays absorption spectroscopy and first‐principles calculation, it also reveals that the strong electronic coupling at the interface of the heterostructure facilitates the dissociation of H 2 O molecular, accelerating the HER kinetics in alkaline electrolyte. This work sheds a light on developing advanced non‐precious metal electrocatalysts for industrial hydrogen production by means of constructing a super‐hydrophilic microporous heterostructure.

Chemistry↗
DOE OSTI2022

Effect of different manufacturing methods on polyamide reverse-osmosis membranes for desalination: Insights from molecular dynamics simulations

Membranes are a key technology platform for a broad application of energy-efficient separations. To best serve the separation demands of industry, the manufacturing processes for these membranes are garnering increasing attention. In particular, for water desalination, the industry leading polyamide (PA) reverse osmosis (RO) membranes can be manufactured via molecular layer-by-layer (mLBL) deposition, interfacial polymerization (IP), and 3D-printing technique. However, the influence of different manufacturing methods on PA membrane’s properties is far from understood. Here, in this study, we present the high-pressure transport behavior of water and salt ions for PA membranes formed with IP, mLBL, and 3D-printing through non-equilibrium molecular dynamics simulations. Studies show that membranes fabricated with 3D-printing have similar performances to those manufactured using mLBL, quantified by water permeability, rejection of salt ions, structural integrity, and porosity features. However, the membranes formed with IP exhibit faster water transport, lower rejection, worse structural integrity, and more inhomogeneous network pores than those constructed using mLBL and 3D-printing. The unconnected water-accessible space governs water transport for PA membranes formed with mLBL and 3D-printing, which offers the impermanent open-closed pores that enable water to jump through PA membranes. In contrast, the permeated water-enterable space plays a prominent role in water movement across the PA membrane formed with IP, providing a continuous transport channel at high pressure. Importantly, we observe the more significant compaction features at high pressure for PA membranes formed with IP than mLBL and 3D printing. In short, these findings provide a comprehensive understanding of existing membrane preparation technologies. It also provides a guide for developing the new membrane preparation process at the molecular level.

3D-printing↗
DOE OSTI2022

Machine learning prediction on the fractional free volume of polymer membranes

Fractional free volume (FFV) characterizes the microstructural level features of polymers and affects their properties including thermal, mechanical, and separation performance. Experimental measurements and theoretical analyses have been used to quantify the FFV of polymers, but challenges remain because of their limitations. Experimental measurements are laborious and based on semi empirical equations, while Bondi’s group contribution theory involves ambiguities like the determination of van der Waals volume and the choice of factor values in the theoretical equation. To efficiently evaluate the FFV of polymers, this study utilizes high-throughput molecular dynamics (MD) simulations to build a large dataset regarding polymer’s FFV. Based on this large dataset, we further build machine learning (ML) models to establish the composition-structure relation. Inspired by group contribution theory which correlates polymer’s functional groups to FFV, our ML models correlate polymer’s substructures or physico-chemical indexes to FFV. Here, our study first benchmarks the MD simulation protocol to obtain reliable FFV of polymers and then carries out high-throughput MD simulations for more than 6,500 homopolymers and 1,400 polyamides. Such a large and diverse dataset makes the well-trained ML models more generalizable, compared with the group contribution theory. The efficiency of a feed forward neural network model is further demonstrated by applying it to a hypothetical polyimide dataset of more than 8 million chemical structures. The predicted FFVs of hypothetical polyimides are further validated by MD simulations. The obtained FFVs of the 8 million polymers, plus their previously reported gas separation performances, demonstrate the promising capability of ML virtual screening for the discovery of polymer membranes with exceptional permeability/selectivity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electronic and magnetic properties of the RuX3 (X = Cl, Br, I) family: two siblings—and a cousin?

Abstract Motivated by reports of metallic behavior in the recently synthesized RuI 3 , in contrast to the Mott-insulating nature of the actively discussed α -RuCl 3 , as well as RuBr 3 , we present a detailed comparative analysis of the electronic and magnetic properties of this family of trihalides. Using a combination of first-principles calculations and effective-model considerations, we conclude that RuI 3 , similarly to the other two members, is most probably on the verge of a Mott insulator, but with much smaller magnetic moments and strong magnetic frustration. We predict the ideal pristine crystal of RuI 3 to have a nearly vanishing conventional nearest-neighbor Heisenberg interaction and to be a quantum spin liquid candidate of a possibly different kind than the Kitaev spin liquid. In order to understand the apparent contradiction to the reported resistivity ρ , we analyze the experimental evidence for all three compounds and propose a scenario for the observed metallicity in existing samples of RuI 3 . Furthermore, for the Mott insulator RuBr 3, we obtain a magnetic Hamiltonian of a similar form to that in the much-discussed α -RuCl 3 and show that this Hamiltonian is in agreement with experimental evidence in RuBr 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2022

Discovery of Innovative Polymers for Next-Generation Gas-Separation Membranes using Interpretable Machine Learning

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research on membrane technologies, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine-learning (ML) implementation for the discovery of innovative polymers with ideal separation performance. Specifically, multitask ML models are trained on available experimental data to link polymer chemistry to gas permeabilities of He, H2, O2, N2, CO2, and CH4. Here, we interpret the ML models and extract chemical heuristics for membrane design, through Shapley Additive exPlanations (SHAP) analysis. We then screen over nine million hypothetical polymers through our models and identify thousands of candidates that lie well above current performance upper bounds. Notably, we discover hundreds of never-before-seen ultrapermeable polymer membranes with O2 and CO2 permeability greater than 104 and 105 Barrer, respectively. These hypothetical polymers are capable of overcoming undesirable trade-off relationship between permeability and selectivity, thus significantly expanding the currently limited library of polymer membranes for highly efficient gas separations. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

Yang, Jason↗
DOE OSTI2022

Machine learning enables interpretable discovery of innovative polymers for gas separation membranes

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine learning (ML) implementation for the discovery of innovative polymers with ideal performance. Specifically, multitask ML models are trained on experimental data to link polymer chemistry to gas permeabilities of He, H 2 , O 2 , N 2 , CO 2 , and CH 4 . We interpret the ML models and extract valuable insights into the contributions of different chemical moieties to permeability and selectivity. We then screen over 9 million hypothetical polymers and identify thousands that lie well above current performance upper bounds, including hundreds of never-before-seen ultrapermeable polymer membranes with O 2 and CO 2 permeability greater than 10 4 and 10 5 Barrers, respectively. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Lactiplantibacillus plantarum 0111 Protects Against Influenza Virus by Modulating Intestinal Microbial-Mediated Immune Responses

There are some limitations of traditional influenza vaccines concerning novel mutant strains. Therefore, it is particularly important to develop preventive means for antigen-unrelated types of influenza viruses. Recent studies have shown that probiotics can modulate the immune system and reduce the severity of viral infections. In this study, we investigated the potential of Lactiplantibacillus plantarum 0111 against influenza virus H9N2. Challenge experiments showed that L. plantarum 0111 pretreatments could effectively improve mice’s survival rate and weight loss and reduce the inflammatory cytokines IL-6 and TNF-α in the lungs and bronchoalveolar lavage fluid (BALF) along with the degree of lung and intestinal injury. FMT experiment demonstrates that the protective effect produced by L. plantarum 0111 is associated with gut microorganisms. In addition, 16S high-throughput sequencing of the mouse intestinal microbiota showed that L. plantarum 0111 remodeled the intestinal microbiota after H9N2 infection and maintained the gut microbiota balance. In a mouse model, the oral administration of L. plantarum 0111 increased IFN-β expression in the serum and BALF. At the same time, the transcript levels of IFN-β and related ISGs in the intestine and lungs of mice were also increased. In addition, the activation and polarization of T cells in mesenteric lymph nodes (MLNs) and the spleen were detected by flow cytometry, and the results showed that L. plantarum 0111 modulated cytokines in T cells and increased IgA expression in B cells in the MLNs and spleen. Thus, L. plantarum 0111 may improve gut microbiota-mediated immune responses and thus, resist infection by the influenza virus, and it could be used as an effective preventive measure against the influenza virus.

Xing, Jun-Hong↗
DOE OSTI2022

Molecular insights into the structure-property relationships of 3D printed polyamide reverse-osmosis membrane for desalination

3D-printing is an emerging method for manufacturing polyamide (PA) reserve osmosis (RO) membranes for water treatment and desalination, which can precisely control membrane structural properties, such as thickness, roughness, and resolution. However, the synthesis-structure (i.e., degree of cross-linking (DC), m-phenylenediamine/trimesoyl chloride (MPD/TMC) ratio, and membrane thickness) to property (permeability and water-salt selectivity) relationships for these membranes has not been well understood. At the same time, a microscopic understanding of the physical mechanism of water and salt transport is needed to guide the design of high-performance 3D-printed membranes and improve the printing efficiency. Furthermore, the atomic-scale transport features and energetics of water and salt ions are studied at high pressure for the 3D-printed PA RO membranes with the different DCs and MPD/TMC ratios through non-equilibrium molecular dynamics (NEMD) simulations. Factoring in membrane structure properties, rejection ratio of salt ions and pressure-dependent water flux, 3D-printed PA membranes having an MPD/TMC ratio of 3.0:2.0 and a DC between 80%~90% attains ideal performance: high water flux, high rejection of salt ions, and excellent structural integrity. Mechanistically, water permeability for highly cross-linked PA RO membranes depends on the temporary on-and-off channels that allow water molecules to jump from one cavity to another at high pressure. In addition, higher pressures cause rapid compaction of PA membranes’ free volume and membrane thickness. Membrane failure at high pressure is determined by the DC and MPD/TMC ratios-dependent compressive yield strength. In short, these findings provide physical insights for optimizing existing PA membranes and designing next-generation desalination membranes at the molecular level.

3D-printed PA RO membrane↗