Carbon Nanotube Interconnects for End-of-Roadmap Semiconductor Technology Nodes

Advances in semiconductor technology due to aggressive downward scaling of on-chip feature sizes have led to rapid rises in resistivity and current density of interconnect conductors. As a result, current interconnect materials, Cu and W, are subject to performance and reliability constraints approaching or exceeding their physical limits. Therefore, alternative materials such as nanocarbons, metal silicides, and Ag nanowires are actively considered as potential replacements to meet such constraints. Among nanocarbons, carbon nanotube (CNT) is among the leading replacement candidate for on-chip interconnect vias due to its high aspect-ratio nanostructure and superior currentcarrying capacity to those of Cu, W, and other potential candidates. However, contact resistance of CNT with metal is a major bottleneck in device functionalization. To meet the challenge posed by contact resistance, several techniques are designed and implemented. First, the via fabrication and CNT growth processes are developed to increase the CNT packing density inside via and to ensure no CNT growth on via sidewalls. CNT vias with cross-sections down to 40 nm 40 nm are fabricated, which have linewidths similar to those used for on-chip interconnects in current integrated circuit manufacturing technology nodes. Then the via top contact is metallized to increase the total CNT area interfacing with the contact metal and to improve the contact quality and reproducibility. Current-voltage characteristics of individual fabricated CNT vias are measured using a nanoprober and contact resistance is extracted with a first-reported contact resistance extraction scheme for 40 nm linewidth. Based on results for 40 nm and 60 nm top-contact metallized CNT vias, we demonstrate that not only are their current-carrying capacities two orders of magnitude higher than their Cu and W counterparts, they are enhanced by reduced via resistance due to contact engineering. While the current-carrying capacities well exceed those projected for end-of-roadmap technology nodes, the via resistances remain a challenge to replace Cu and W, though our results suggest that further innovations in contact engineering could begin to overcome such challenge

Adsorption properties and third sound propagation in superfluid 4^4He films on carbon nanotubes

We consider the adsorption properties of superfluid $^4$He films on carbon nanotubes. One major factor in the adsorption is the surface tension force arising from the very small diameter of the nanotubes. Calculations show that surface tension keeps the film thickness on the tubes very thin even when the helium vapor is increased to the saturated pressure. The weakened Van der Waals force due to the cylindrical geometry also contributes to this. Both of these effects act to lower the predicted velocity of third sound propagation along the tubes. It does not appear that superfluidity will be possible on single-walled nanotubes of diameter about one nm, since the film thickness is less than 3 atomic layers even at saturation. Superfluidity is possible on larger-diameter nanotube bundles and multi-walled nanotubes, however. We have observed third sound signals on nanotube bundles of average diameter 5 nm which are sprayed onto a Plexiglass surface, forming a network of tubes.Comment: 4 pages, accepted for Journal of Physics: Conference Series (Proceedings of LT25

Amplitude dynamics of charge density wave in LaTe3_3: theoretical description of pump-probe experiments

We formulate a dynamical model to describe a photo-induced charge density wave (CDW) quench transition and apply it to recent multi-probe experiments on LaTe$_3$ [A. Zong et al., Nat. Phys. 15, 27 (2019)]. Our approach relies on coupled time-dependent Ginzburg-Landau equations tracking two order parameters that represent the modulations of the electronic density and the ionic positions. We aim at describing the amplitude of the order parameters under the assumption that they are homogeneous in space. This description is supplemented by a three-temperature model, which treats separately the electronic temperature, temperature of the lattice phonons with stronger couplings to the electronic subsystem, and temperature of all other phonons. The broad scope of available data for LaTe$_3$ and similar materials as well as the synergy between different time-resolved spectroscopies allow us to extract model parameters. The resulting calculations are in good agreement with ultra-fast electron diffraction experiments, reproducing qualitative and quantitative features of the CDW amplitude evolution during the initial few picoseconds after photoexcitation.Comment: 21 pages, 14 figures; this version is almost identical to the published version; comparing to the earlier arXiv submission, current version contains a new figure (Fig.10), and a broader discussion of theoretical results and approximation

Electrical and Structural Analysis of CNT-Metal Contacts in Via Interconnects

Vertically aligned carbon nanotubes grown by plasmaenhanced chemical vapor deposition offer a potentially suitable material for via interconnects in next-generation integrated circuits. Key performance-limiting factors include high contact resistance and low carbon nanotube packing density, which fall short of meeting the requirements delineated in the ITRS roadmap for interconnects. For individual carbon nanotube s, contact resistance is a major performance hurdle since it is the dominant component of carbon nanotube interconnect resistance, even in the case of vertically aligned carbon nanotube arrays. In this study, we correlate the carbon nanotube-metal interface nanostructure to their electrical properties in order to elucidate growth parameters that can lead to high density and low contact resistance and resistivity

Spherical void expansion in rubber-like materials: The stabilizing effects of viscosity and inertia

Dynamic cavitation is known to be a typical failure mechanism in rubber-like solids. While the mechanical behaviour of these materials is generally rate-dependent, the number of theoretical and numerical works addressing the problem of cavitation using nonlinear viscoelastic constitutive models is scarce. It has been only in recent years when some authors have suggested that cavitation in rubber-like materials is a dynamic fracture process strongly affected by the rate-dependent behaviour of the material because of the large strains and strain rates that develop near the cavity. In the present work we further investigate previous idea and perform finite element simulations to model the dynamic expansion of a spherical cavity embedded into a rubber-like ball and subjected to internal pressure. To describe the mechanical behaviour of the rubber-like material we have used an experimentally calibrated constitutive model which includes rate-dependent effects and material failure. The numerical results demonstrate that inertia and viscosity play a fundamental role in the cavitation process since they stabilize the material behaviour and thus delay failure

Self-aware SGD: reliable incremental adaptation framework for clinical AI models

Healthcare is dynamic as demographics, diseases, and therapeutics constantly evolve. This dynamic nature induces inevitable distribution shifts in populations targeted by clinical AI models, often rendering them ineffective. Incremental learning provides an effective method of adapting deployed clinical models to accommodate these contemporary distribution shifts. However, since incremental learning involves modifying a deployed or in-use model, it can be considered unreliable as any adverse modification due to maliciously compromised or incorrectly labelled data can make the model unsuitable for the targeted application. This paper introduces self-aware stochastic gradient descent (SGD) , an incremental deep learning algorithm that utilises a contextual bandit-like sanity check to only allow reliable modifications to a model. The contextual bandit analyses incremental gradient updates to isolate and filter unreliable gradients. This behaviour allows self-aware SGD to balance incremental training and integrity of a deployed model. Experimental evaluations on the Oxford University Hospital datasets highlight that self-aware SGD can provide reliable incremental updates for overcoming distribution shifts in challenging conditions induced by label noise

Gorlin Goltz syndrome: a rare case report

Gorlin-Goltz syndrome is uncommon multisystemic disease with an autosomal dominant trait, with complete penetrance and variable expressivity, though sporadic cases have been described. We report a case of 18 years old male patient having features of Gorlin Goltz syndrome. Gorlin-Goltz syndrome is characterized by multiple basal cell nevi or carcinomas, odontogenic keratocysts, palmar and/or plantar pits, calcification of the falx cerebri, and is associated with internal malignancies. It is important to know the major and minor criteria for the diagnosis and early preventive treatment of this syndrome

Measurement of the dynamic charge response of materials using low-energy, momentum-resolved electron energy-loss spectroscopy (M-EELS)

One of the most fundamental properties of an interacting electron system is its frequency- and wave-vector-dependent density response function, $\chi({\bf q},\omega)$. The imaginary part, $\chi''({\bf q},\omega)$, defines the fundamental bosonic charge excitations of the system, exhibiting peaks wherever collective modes are present. $\chi$ quantifies the electronic compressibility of a material, its response to external fields, its ability to screen charge, and its tendency to form charge density waves. Unfortunately, there has never been a fully momentum-resolved means to measure $\chi({\bf q},\omega)$ at the meV energy scale relevant to modern elecronic materials. Here, we demonstrate a way to measure $\chi$ with quantitative momentum resolution by applying alignment techniques from x-ray and neutron scattering to surface high-resolution electron energy-loss spectroscopy (HR-EELS). This approach, which we refer to here as "M-EELS," allows direct measurement of $\chi''({\bf q},\omega)$ with meV resolution while controlling the momentum with an accuracy better than a percent of a typical Brillouin zone. We apply this technique to finite-q excitations in the optimally-doped high temperature superconductor, Bi$_2$Sr$_2$CaCu$_2$O$_{8+x}$ (Bi2212), which exhibits several phonons potentially relevant to dispersion anomalies observed in ARPES and STM experiments. Our study defines a path to studying the long-sought collective charge modes in quantum materials at the meV scale and with full momentum control.Comment: 26 pages, 10 sections, 7 figures, and an appendi

Continuous patient state attention models

Irregular time-series (ITS) are prevalent in the electronic health records (EHR) as the data is recorded in EHR system as per the clinical guidelines/requirements but not for research and also depends on the patient health status. ITS present challenges in training of machine learning algorithms, which are mostly built on assumption of coherent fixed dimensional feature space. In this paper, we propose a computationally efficient variant of the transformer based on the idea of cross-attention, called Perceiver, for time-series in healthcare. We further develop continuous patient state attention models, using the Perceiver and the transformer to deal with ITS in EHR. The continuous patient state models utilise neural ordinary differential equations to learn the patient health dynamics, i.e., patient health trajectory from the observed irregular time-steps, which enables them to sample any number of time-steps at any time. The performance of the proposed models is evaluated on in-hospital-mortality prediction task on Physionet-2012 challenge and MIMIC-III datasets. The Perceiver model significantly outperforms the baselines and reduces the computational complexity, as compared with the transformer model, without significant loss of performance. The carefully designed experiments to study irregularity in healthcare also show that the continuous patient state models outperform the baselines. The code is publicly released and verified at https://codeocean.com/capsule/4587224