Modeling and optimizing stoichiometry-dependent resistivity of composite metals used in semiconductor devices, involves identifying dominant carrier scattering mechanism affecting resistivity of composite metal material and developing stoichiometry-dependent resistivity model
	PANDEY R K
	2024-12-18
专利权人	VELLORE INST TECHNOLOGY (VELL-Non-standard)
申请日期	2024-12-18
专利号	IN202441100582-A
成果简介	NOVELTY - Modeling and optimizing stoichiometry-dependent resistivity of composite metals used in semiconductor devices, involves identifying dominant carrier scattering mechanism affecting resistivity of composite metal material in semiconductor gate stack; developing stoichiometry-dependent resistivity model incorporating dominant scattering mechanism and dependency of resistivity on material stoichiometry; configuring and running density functional theory-based simulations to determine composition-dependent parameters comprising deformation potential (D), density of states (DOS) at fermi level, unit cell volume, mass density (pm), phonon velocity (vs), effective mass (m), and carrier density (n), incorporating extracted composition-dependent parameters into resistivity model to compute composition-specific resistivity values; generating analytical expression or look-up table correlating composition-specific resistivity values with stoichiometric composition to enable predictive modeling. USE - Method for modeling and optimizing stoichiometry-dependent resistivity of composite metals used in semiconductor devices, for evaluating and optimizing gate stack materials, such as TiAlC, tantalum aluminum carbide (TaAlC), and niobium aluminum carbide (NbAlC), with targeted aluminum compositions for minimizing gate resistance in fin field-effect transistors (FinFETs) and metal-oxide semiconductor (MOS) devices. ADVANTAGE - The temperature dependence is incorporated into the resistivity model with composition dependence to enable the simulations for devices operating under extreme conditions. The method facilitates enhanced performance in scaled semiconductor devices. DETAILED DESCRIPTION - Modeling and optimizing stoichiometry-dependent resistivity of composite metals used in semiconductor devices, involves identifying dominant carrier scattering mechanism affecting the resistivity of a composite metal material in a semiconductor gate stack; developing a Stoichiometry-dependent resistivity model incorporating the dominant scattering mechanism and dependency of the resistivity on material stoichiometry; configuring and running density functional theory (DFT)-based simulations to determine composition-dependent parameters comprising deformation potential (D), density of states (DOS) at the fermi level, unit cell volume, mass density (pm), phonon velocity (vs), effective mass (m), and carrier density (n), incorporating the extracted composition-dependent parameters into the resistivity model to compute composition-specific resistivity values; generating an analytical expression or look-up table correlating the composition-specific resistivity values with stoichiometric composition to enable predictive modeling; integrating the resistivity model into a device simulation environment, wherein the resistivity model incorporates variations in stoichiometry, temperature dependence, and self-heating effects in scaled devices; evaluate and optimize gate stack materials, comprising titanium aluminum carbide (TiAlC), TaAlC with the integrated simulation framework for reduced gate resistance and enhanced device performance.
IPC 分类号	F16F-015/14 ; G06F-030/20 ; G06F-030/367 ; H01L-029/423 ; H01L-029/49
国家	印度
专业领域	材料科学
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/13979
专题	中国科学院新疆生态与地理研究所
作者单位	VELLORE INST TECHNOLOGY (VELL-Non-standard)
推荐引用方式 GB/T 7714	PANDEY R K. Modeling and optimizing stoichiometry-dependent resistivity of composite metals used in semiconductor devices, involves identifying dominant carrier scattering mechanism affecting resistivity of composite metal material and developing stoichiometry-dependent resistivity model. IN202441100582-A[P]. 2024.

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