Surface roughness dependence of the electrical resistivity of W(001) layers

Zheng, Pengyuan; Zhou, Tianji; Engler, Brent; Chawla, J. S.; Hull, R.; Gall, Daniel

doi:10.1063/1.4994001

Cited by 38 publications

(25 citation statements)

References 67 publications

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“…The surface roughness of narrow conductors contributes to the resistivity increase associated with electron scattering and may be the cause for the incorrect resistivity prediction by the FS model for narrow conductors. More specifically, the reported measured resistivity of thin films <20 nm is consistently higher than the prediction from the FS model, 30,34,[37][38][39] suggesting that a single parameter p may be insufficient to correctly describe the resistivity vs thickness dependence. As a consequence, multiple models have been developed which explicitly treat surface roughness as a contributor to the resistivity.…”

Section: Introductionmentioning

confidence: 90%

“…We have chosen as an experimental model system epitaxial W(001) films, primarily because the high melting point facilitates epitaxial (single-crystal) growth of thin continuous layers on insulating substrates down to thicknesses of 4 nm, 62,63 and we have previously developed in situ annealing procedures that allow variations in the surface roughness with negligible changes in the crystalline quality. 39 4.5-52 nm thick W(001) films were deposited on MgO(001) substrates in a three chamber ultrahigh vacuum DC magnetron sputter deposition system with a base pressure <10 À9 Torr following the procedure in Ref. 62.…”

Section: Experimental Validationmentioning

confidence: 99%

“…The RMS surface roughness x and the lateral correlation length n are then obtained by fitting of the H(r) data assuming a self-affine surface morphology 68 using eight micrographs for each sample, as previously reported in Ref. 39. A total of nine W(001) layers with thickness d ¼ 4.5-52 nm are investigated, yielding a range of surface morphologies with x ¼ 0.25-1.07 nm and n ¼ 10.5-21.9 nm.…”

Section: Experimental Validationmentioning

confidence: 99%

“…That is, annealing considerably reduces x (by a factor of 2-4) without affecting n (which increases by 6%-14%). 39 This provides the ideal sample set to test the presented model, which predicts a resistivity change as a function of the ratio x/n.…”

Section: Experimental Validationmentioning

confidence: 99%

“…However, this roughness effect is secondary and the model typically underestimates the measured resistivity increase. 13,30,39 Kuan et al 27,34 extended the approximate version of the FS model with an empirical factor S that accounts for surface roughness effects and linearly increases the surface scattering contribution to the resistivity. This model has been successfully employed to describe sub-20 nm measured resistivity data, 13 yet the physical meaning of the empirical parameter S is not completely clear, since expressing S as a function of x involves two additional parameters (S ¼ ax b ) and the fitting is not unique.…”

Section: Introductionmentioning

confidence: 99%

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The electrical resistivity of rough thin films: A model based on electron reflection at discrete step edges

Zhou

Zheng

Pandey

et al. 2018

Journal of Applied Physics

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The effect of the surface roughness on the electrical resistivity of metallic thin films is described by electron reflection at discrete step edges. A Landauer formalism for incoherent scattering leads to a parameter-free expression for the resistivity contribution from surface mound-valley undulations that is additive to the resistivity associated with bulk and surface scattering. In the classical limit where the electron reflection probability matches the ratio of the step height h divided by the film thickness d, the additional resistivity Dq ¼ ffiffiffiffiffiffiffi ffi 3=2 p /(g 0 d) Â x/n, where g 0 is the specific ballistic conductance and x/n is the ratio of the root-mean-square surface roughness divided by the lateral correlation length of the surface morphology. First-principles non-equilibrium Green's function density functional theory transport simulations on 1-nm-thick Cu(001) layers validate the model, confirming that the electron reflection probability is equal to h/d and that the incoherent formalism matches the coherent scattering simulations for surface step separations !2 nm. Experimental confirmation is done using 4.5-52 nm thick epitaxial W(001) layers, where x ¼ 0.25-1.07 nm and n ¼ 10.5-21.9 nm are varied by in situ annealing. Electron transport measurements at 77 and 295 K indicate a linear relationship between Dq and x/(nd), confirming the model predictions. The model suggests a stronger resistivity size effect than predictions of existing models by Fuchs [Math. ]. It provides a quantitative explanation for the empirical parameters in these models and may explain the recently reported deviations of experimental resistivity values from these models. Published by AIP Publishing. https://doi.

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Section: Introductionmentioning

confidence: 90%

Section: Experimental Validationmentioning

confidence: 99%

Section: Experimental Validationmentioning

confidence: 99%

Section: Experimental Validationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

The electrical resistivity of rough thin films: A model based on electron reflection at discrete step edges

Zhou

Zheng

Pandey

et al. 2018

Journal of Applied Physics

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Materials Quest for Advanced Interconnect Metallization in Integrated Circuits

et al. 2023

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Integrated circuits (ICs) are challenged to deliver historically anticipated performance improvements while increasing the cost and complexity of the technology with each generation. Front‐end‐of‐line (FEOL) processes have provided various solutions to this predicament, whereas the back‐end‐of‐line (BEOL) processes have taken a step back. With continuous IC scaling, the speed of the entire chip has reached a point where its performance is determined by the performance of the interconnect that bridges billions of transistors and other devices. Consequently, the demand for advanced interconnect metallization rises again, and various aspects must be considered. This review explores the quest for new materials for successfully routing nanoscale interconnects. The challenges in the interconnect structures as physical dimensions shrink are first explored. Then, various problem‐solving options are considered based on the properties of materials. New materials are also introduced for barriers, such as 2D materials, self‐assembled molecular layers, high‐entropy alloys, and conductors, such as Co and Ru, intermetallic compounds, and MAX phases. The comprehensive discussion of each material includes state‐of‐the‐art studies ranging from the characteristics of materials by theoretical calculation to process applications to the current interconnect structures. This review intends to provide a materials‐based implementation strategy to bridge the gap between academia and industry.

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