Related papers: Artificial Intelligence-Enabled Holistic Design of…
Density functional calculations were performed to systematically study a series of finite and infinite cluster-assembled silicon nanotubes (SiNTs). One-dimensional SiNTs can be prepared by proper assembly of hydrogenated cage-like silicon…
We present a general approach to the computational design of nanostructured chemical sensors. The scheme is based on identification and calculation of microscopic descriptors (design parameters) which are used as input to a thermodynamic…
Elucidating the catalytic descriptor that accurately characterizes the structure-activity relationships of typical catalysts for various important heterogeneous catalytic reactions is pivotal for designing high-efficient catalytic systems.…
Random networks of single-walled carbon nanotubes (CNTs) usually contain both metallic (m-CNTs) and semiconducting (s-CNTs) nanotubes with an approximate ratio of 1:2, which leads to a trade-off between on-conductance and on/off ratio. We…
Carbon nanotubes (CNTs) are currently considered a successor to silicon in future nanoelectronic devices. To realize this, controlled growth of defect-free nanotubes is required. Until now, the understanding of atomic-scale CNT growth…
Understanding structure-property relationships in complex materials requires integrating complementary measurements across multiple length scales. Here we propose an interpretable "multimodal" machine learning framework that unifies…
Recent advances in structural control during the synthesis of SWCNTs have in common the use of bimetallic nanoparticles as catalysts, despite the fact that their exact role is not fully understood. We therefore analyze the effect of the…
We report strategies of achieving both high assembly yield of carbon nanotubes at selected position of the circuit via dielectrophoresis (DEP) and field effect transistor (FET) yield using semiconducting enriched single walled carbon…
Single-walled carbon nanotubes have been a candidate for outperforming silicon in ultrascaled transistors, but the realization of nanotube-based integrated circuits requires dense arrays of purely semiconducting species. Control over…
Carbon fiber and graphene-based nanostructures such as carbon nanotubes (CNTs) and defective structures have extraordinary potential as strong and lightweight materials. A longstanding bottleneck has been lack of understanding and…
CO2 reduction requires efficient catalysts, yet materials discovery remains bottlenecked by 10-20 year development cycles requiring deep domain expertise. This paper demonstrates how large language models can assist the catalyst discovery…
Advanced electronic device technologies require a faster operation and smaller average power consumption, which are the most important parameters in very large scale integrated circuit design. The conventional Complementary Metal-Oxide…
In the pursuit of novel catalyst development to address pressing environmental concerns and energy demand, conventional design and optimization methods often fall short due to the complexity and vastness of the catalyst parameter space. The…
The sustainable production of many bulk chemicals relies on heterogeneous catalysis. The rational design or improvement of the required catalysts critically depends on insights into the underlying mechanisms at the atomic scale. In recent…
High performance nanocomposites require well dispersion and high alignment of the nanometer-sized components, at a high mass or volume fraction as well. However, the road towards such composite structure is severely hindered due to the easy…
The inability to synthesize single-wall carbon nanotubes (SWCNTs) possessing uniform electronic properties and chirality represents the major impediment to their widespread applications. Recently, there is growing interest to explore and…
The accelerating adoption of Large Language Models (LLMs) in software engineering (SE) has brought with it a silent crisis: unsustainable computational cost. While these models demonstrate remarkable capabilities in different SE tasks, they…
The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided computational screening framework unifying linguistic…
Carbon Nanotubes have shown to be an attractive option in the race to find a replacement to silicon-based transistors, due to its high electrical conductivity, extraordinary mechanical strength, and thermal conductivity. However, challenges…
We report a process to fabricate carbon nanotubes (CNT) by chemical vapor deposition at predetermined location. This process was enabled by patterning catalyst nanoparticles directly on silicon substrates with nanometer-scale precision…