Observation of 
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 and 
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Lu, P.-C.; Wang, M.-Z.; Chistov, R.; Chang, P.; Adachi, I.; Ahn, J. K.; Aihara, H.; Said, S. Al; Asner, D. M.; Atmacan, H.; Aulchenko, V.; Aushev, T.; Ayad, R.; Babu, V.; Badhrees, I.; Bakich, A. M.; Bansal, V.; Behera, P. K.; Beleño, C.; Berger, Martin; Bhardwaj, V.; Bhuyan, B.; Bilka, T.; Biswal, Jyoti Prakash; Bonvicini, G.; Bożek, A.; Bračko, M.; Browder, T. E.; Cao, L.; Červenkov, D.; Chang, M.-C.; Chekelian, V.; Chen, A.; Cheon, B. G.; Chilikin, K.; Cho, K.; Choi, S.; Choi, Y.; Choudhury, S.; Cinabro, D.; Cunliffe, S.; Dash, N.; Carlo, S. Di; Doležal, Z.; Dong, T. V.; Drásal, Z.; Eidelman, S.; Epifanov, D.; Fast, J. E.; Ferber, T.; Fulsom, B. G.; Garg, R. B.; Gaur, V.; Gabyshev, N.; Garmash, A.; Gelb, M.; Giri, A.; Goldenzweig, P.; Guido, E.; Haba, J.; Hayasaka, K.; Hayashii, H.; Hirose, S.; Hou, W.-S.; Hsu, C.-L.; Iijima, T.; Inami, K.; Inguglia, G.; Ishikawa, A.; Itoh, R.; Iwasaki, M.; Iwasaki, Y.; Jacobs, W. W.; Jeon, H. B.; Jia, S.; Jin, Y.; Joffe, D.; Joo, K. K.; Julius, T.; Kaliyar, A. B.; Kawasaki, T.; Kichimi, H.; Kiesling, C.; Kim, D. Y.; Kim, H. J.; Kim, J. B.; Kim, K. T.; Kim, S. H.; Kinoshita, K.; Kodyš, P.; Korpar, S.; Kotchetkov, D.; Križan, P.; Kroeger, R.; Krokovny, P.; Kuhr, T.; Kulasiri, R.; Kuzmin, A.; Kwon, Y.; Lai, Y.-T.; Lange, J. S.; Lee, I. S.; Lee, S. C.; Li, L. K.; Li, Y. B.; Gioi, L. Li; Libby, J.; Liventsev, D.; Lubej, M.; Luo, T.; Masuda, M.; Matsuda, T.; Matvienko, D.; Merola, M.; Miyabayashi, K.; Miyata, H.; Mizuk, R.; Mohanty, G. B.; Moon, H. K.; Mori, Takashi; Mussa, R.; Nakao, M.; Nanut, T.; Nath, K. J.; Natkaniec, Z.; Nayak, M.; Nisar, N. K.; Nishida, S.; Ogawa, S.; Okuno, S.; Ono, H.; Ozaki, H.; Pakhlov, P.; Pakhlova, G.; Pal, B. K.; Pardi, S.; Park, H.; Paul, S.; Pedlar, T. K.; Pestotnik, R.; Piilonen, L. E.; Popov, V.; Prencipe, E.; Rabusov, A.; Ritter, M.; Rostomyan, A.; Russo, G.; Sakai, Y.; Salehi, M.; Sandilya, S.; Šantelj, L.; Sanuki, T.; Savinov, V.; Schneider, O.; Schnell, G.; Schwanda, C.; Seino, Y.; Senyo, K.; Sevior, M. E.; Shebalin, V.; Shen, C. P.; Shibata, T. A.; Shiu, J. G.; Shwartz, B.; Simon, F.; Singh, Jagbir; Sokolov, A.; Solovieva, E.; Starič, M.; Strube, J.; Sumihama, M.; Sumiyoshi, T.; Sutcliffe, W.; Takizawa, M.; Tamponi, U.; Tanida, K.; Tenchini, F.; Uchida, M.; Uglov, T.; Unno, Y.; Uno, S.; Urquijo, P.; Usov, Y.; Vahsen, S. E.; Hulse, C. Van; Tonder, R. Van; Varner, G.; Vinokurova, A.; Vorobyev, V.; Vossen, A.; Wang, B.; Wang, C. H.; Wang, X. L.; Watanabe, M.; Watanuki, S.; Widmann, E.; Won, E.; Ye, H.; Yin, J. H.; Yuan, C. Z.; Zhang, Z. P.; Zhilich, V.; Zhukova, V.; Zhulanov, V.; Zupanc, A.

doi:10.1103/physrevd.99.032003

Cited by 35 publications

(60 citation statements)

References 24 publications

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“…This is broadly consistent with experiment: electropositive sodium promotes hydrogen-deuterium exchange, [52] whereas electronegative chlorine disfavors H 2 adsorption. [53] Figure 6 summarizes these results, showing the Sabatier plots computed for both hydrogen-deuterium scrambling pathways. Again, both pathways predict that turnover is optimized for electropositive promoters that reduce the catalyst work function and promote electron donation to H 2 and D 2 .…”

Section: Promoter Effects On Hydrogen Scramblingmentioning

confidence: 93%

“…[52] Electronegative chlorine, in catalysts prepared from RuCl 3 , raises the activation energies for irreversible hydrogen adsorption onto alumina-supported ruthenium catalysts. [53] Figure 3 shows our computed potential energy surfaces for the unpromoted catalyst. We find two pathways for hydrogendeuterium scrambling, denoted as A and B.…”

Section: Promoter Effects On Hydrogen Scramblingmentioning

confidence: 99%

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Tunable model promoters in DFT simulations of catalysts

et al. 2019

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Promoter atoms can tune a catalyst's activity and selectivity by transferring charge to and from the active site. Rational design of promoted catalysts, using density functional theory calculations, is today limited by the need to simulate many catalyst and promoter configurations. We present a simple approximation that rapidly captures some trends in promoter effects, at a cost of complexity comparable with simulating unpromoted catalysts. Negative (positive) noninteger point charges introduced into the catalyst simulate how electropositive (electronegative) promoters might affect each predicted intermediate. Calculations return Sabatier plots, relating promoters' predicted efficacy to readily measured properties such as catalyst work functions. We illustrate our approach for two reactions associated with the Fischer–Tropsch process, hydrogen–deuterium scrambling, and carbon monoxide dissociation over ruthenium. Consistent with experiment, electropositive promoters are predicted to accelerate hydrogen scrambling and unassisted CO dissociation. Simulations also provide a new prediction: electronegative promoters accelerate hydrogen‐assisted CO dissociation over hydrogen‐precovered surfaces by stabilizing the initial CO adsorption. © 2019 Wiley Periodicals, Inc.

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Section: Promoter Effects On Hydrogen Scramblingmentioning

confidence: 93%

Section: Promoter Effects On Hydrogen Scramblingmentioning

confidence: 99%

Tunable model promoters in DFT simulations of catalysts

et al. 2019

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“…[142] The improvement of the energy solution can extend the detectable modes from the infrared to the visible-ultraviolet. EELS-TEM has been widely used to excite ultraviolet plasmonic modes in various traditional 2D materials, such as high energy plasmon in graphene, [34,[143][144][145][146] black phosphorous, [147] topological insulators, [37,148] a recently discovered new class of 2D crystals-MXenes, [39,149] and the bandgap excitation in h-BN. [36,150] For example, Eberlein and co-workers [34] observed π and π + σ-surface plasmon modes in a few layers of free-standing graphene sheets, where the EEL spectra is shown in Figure 8c.…”

Section: Electron Energy Loss Spectroscopymentioning

confidence: 99%

Probing Polaritons in 2D Materials

Luo

Guo

et al. 2020

Advanced Optical Materials

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Polaritons in 2D materials exhibit extensive optical phenomena, such as an ultrahigh field confinement and tunability and, thus, have been attracting increasing attentions. Many different methods have been developed to characterize and manipulate polaritons, which in turn has promoted a steady booming of this field. Here, the significant progress made in probing polaritons in 2D materials based on the characterization method, i.e., optical far‐field, optical near‐field, and (opto)electronic methods is reviewed. Perspectives on the potential development and applications of these methods are also discussed.

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“…Furthermore, two models based on simple deformation geometries were derived following Barlow's formula. Studies on the failure mechanism of compressed spherical microcapsules had shown that the highest membrane stress exists in the equatorial plane and leads to rupture perpendicular to the equator [9,26]. Thus, in the following, only the equatorial stress and strain are taken into account.…”

Section: Simple Deformation Geometry Modelsmentioning

confidence: 99%

Compression Testing and Modeling of Spherical Cells – Comparison of Yeast and Algae

et al. 2017

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The yeast Saccharomyces cerevisiae and the microalga Chlorella vulgaris were mechanically characterized using single‐cell compression experiments. Micromechanical cell characteristics could be calculated directly from the force displacement data. The mechanical properties of the cell wall were determined with different analytical models because the intrinsic parameters of the cell wall cannot be measured directly. As expected, the Young's moduli obtained from the cellular model and the cell wall model differ by two orders of magnitude. Although yeast and algal cells need similar forces to get disrupted, the bursting deformation and bursting energy of the algal cells are about two times smaller. Based on the dry biomass, the energy for cell breakage of C. vulgaris is about six times higher than that of S. cerevisiae. Finally, the tensile strength of the cell wall was calculated.

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Observation of B+→pΛ¯K+K− and
P.-C. Lu¹,
M.-Z. Wang²,
R. Chistov³
et al.

Cited by 35 publications

References 24 publications

Tunable model promoters in DFT simulations of catalysts

Tunable model promoters in DFT simulations of catalysts

Probing Polaritons in 2D Materials

Compression Testing and Modeling of Spherical Cells – Comparison of Yeast and Algae

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Observation of B+→pΛ¯K+K− and P.-C. Lu1, M.-Z. Wang2, R. Chistov3 et al.

Cited by 35 publications

References 24 publications

Tunable model promoters in DFT simulations of catalysts

Tunable model promoters in DFT simulations of catalysts

Probing Polaritons in 2D Materials

Compression Testing and Modeling of Spherical Cells – Comparison of Yeast and Algae

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Resources

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Observation of B+→pΛ¯K+K− and
P.-C. Lu¹,
M.-Z. Wang²,
R. Chistov³
et al.