Surface Characterization of NbO Islands Formed on Nb(100) by X-Ray Photoelectron Diffraction

Pancotti, A.; Wang, J.; Rezende, A. C. S. A.; Santos, Dener Pereira; Siervo, Abner de; Landers, Richard; Nascente, P. A. P.

doi:10.1007/s11244-018-0946-x

Cited by 5 publications

(3 citation statements)

References 39 publications

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“…All Nb films are 30 nm thick. The binding energies for all elements and compounds seen within this figure are corroborated by those ascertained in previous works 50 – 58 . …”

Section: Resultssupporting

confidence: 89%

Electron beam evaporation of superconductor-ferromagnet heterostructures

Bromley

Wright

Jones

et al. 2022

Sci Rep

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We report on the electronic and magnetic properties of superconductor-ferromagnet heterostructures fabricated by electron beam evaporation on to unheated thermally oxidised Si substrates. Polycrystalline Nb thin films (5 to 50 nm thick) were shown to possess reliably high superconducting critical temperatures ($$T_{c}$$ T c ), which correlate well with the residual resistivity ratio (RRR) of the film. These properties improved during ex-situ annealing, resulting in $${\Delta }T_{c}$$ Δ T c and $${\Delta }$$ Δ RRR increases of up 2.2 K ($$\sim$$ ∼ 40% of the pre-annealed $$T_{c}$$ T c ) and 0.8 ($$\sim$$ ∼ 60% of the pre-annealed RRR) respectively. Nb/Pt/Co/Pt heterostructures showed substantial perpendicular anisotropy in the ultrathin limit (≤ 2.5 nm), even in the extreme limit of Pt(0.8 nm)/Co(1 nm)/Pt(0.6 nm). These results point to the use of electron beam evaporation as route to line-of-sight deposited, low-thickness, high quality Nb-based superspintronic multilayers.

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“…All Nb films are 30 nm thick. The binding energies for all elements and compounds seen within this figure are corroborated by those ascertained in previous works 50 – 58 . …”

Section: Resultssupporting

confidence: 89%

Electron beam evaporation of superconductor-ferromagnet heterostructures

Bromley

Wright

Jones

et al. 2022

Sci Rep

View full text Add to dashboard Cite

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“…193 And lately, in 2018, the authors found that the Nb(100) surface contained ordered NbO islands with patches of pristine niobium between. 194 In a similar application, Wen et al used USPEX to find new iron titanium oxide structures on the Ti(011) surface. 195 These structures contain ridges of low-coordination Fe(II) cations, some of which appear to match experimental STM images (Figure 11).…”

Section: ■ ML In Chemistrymentioning

confidence: 99%

“…In 2017, the GA was used to explore rhodium islands on a Fe 2 O 3 film on palladium to note that the film is likely Fe-terminated and the islands four layers tall (Figure ). And lately, in 2018, the authors found that the Nb(100) surface contained ordered NbO islands with patches of pristine niobium between …”

Section: Ga For Surface Chemistrymentioning

confidence: 99%

Genetic Algorithms and Machine Learning for Predicting Surface Composition, Structure, and Chemistry: A Historical Perspective and Assessment

2021

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Genetic algorithms (GA) and machine learning (ML) have a long history of development and use in chemistry. Recent algorithmic and computational advances, however, have brought these methods to the forefront of chemical research, and chemistry is experiencing a transformation in the way that machines and humans interact to pursue scientific advances. The field of materials chemistry, in particular, has witnessed a considerable expansion in the maturity of GA and ML approaches, as machine-based materials design ushers in a new era of materials development, discovery, and deployment. In addition to predicting new compositions and properties of bulk materials, GA and ML have also guided new insights into the structure, composition, and chemistry of materials surfaces. In this review, we focus on how GA and ML have been used in conjunction with chemical simulation techniques to advance understanding of surface chemistry, examining the history, recent work, and overall success of these applications.

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