Related papers: Diffusion modeling for Dip-pen Nanolithography

This paper describes a lattice Boltzmann-based binary fluid model for inkjet printing. In this model, a time-dependent driving force is applied to actuate the droplet ejection. As a result, the actuation can be accurately controlled by…

We report an in situ transmission electron microscopy observation of an indium droplet flowing on a silicon nitride membrane with a coating layer of hydrogenated amorphous silicon (a-Si:H), with the production of in-plane c-Si nanowire in…

Pinning of liquid droplets on solid substrates is ubiquitous and plays an essential role in many applications, especially in various areas, such as microfluidics and biology. Although pinning can often reduce the efficiency of various…

Diffusion Models are popular generative modeling methods in various vision tasks, attracting significant attention. They can be considered a unique instance of self-supervised learning methods due to their independence from label…

This handbook offers a unified perspective on diffusion models, encompassing diffusion probabilistic models, score-based generative models, consistency models, rectified flow, and related methods. By standardizing notations and aligning…

The spontaneous spreading of non-volatile liquid droplets on solid substrates poses a classic problem in the context of wetting phenomena. It is well known that the spreading of a macroscopic droplet is in many cases accompanied by a thin…

Diffusion-based generative models are machine learning models that use diffusion processes to learn the probability distribution of high-dimensional data. In recent years, they have become extremely successful in generating multimedia…

This paper proposes a height profile model for drop-on-demand printing of UV curable ink. Existing models includesuperposition of single drops, numerical models, and graphic-based model. They are either too complicated or over…

Diffusion models have emerged as a leading framework in generative modeling, poised to transform the traditionally slow and costly process of drug discovery. This review provides a systematic comparison of their application in designing two…

Diffusion models have achieved remarkable progress in generative modelling, particularly in enhancing image quality to conform to human preferences. Recently, these models have also been applied to low-level computer vision for…

A direct electronics printing technique through atomized spraying for patterning room temperature liquid metal droplets on desired substrate surfaces is proposed and experimentally demonstrated for the first time. This method has…

In spite of significant advances in replication technologies, methods to produce well-defined three dimensional structures are still at its infancy. Such a limitation would be evident if we were to produce a large array of simple and,…

The use of nanoparticles for targeted drug delivery, especially in diseased arteries, is a novel procedure. We are incorporating nanoparticles into blood vessels using a catheter, which could potentially deliver drugs precisely to affected…

In this paper, we generate conceptual engineering designs of electric vertical take-off and landing (eVTOL) aircraft. We follow the paradigm of simulation-based inference (SBI), whereby we look to learn a posterior distribution over the…

These are lecture notes for various Summer and Winter schools that I have given. The notes describe the methodology called Variational Modelling, and focus on the application to the modelling of gradient-flow systems. I describe the…

Monocular depth estimation is a challenging task that predicts the pixel-wise depth from a single 2D image. Current methods typically model this problem as a regression or classification task. We propose DiffusionDepth, a new approach that…

As the need for miniaturized structural and functional materials has increased,the need for precise materials characterizaton has also expanded. Nanoindentation is a popular method that can be used to measure material mechanical behavior…

We propose a laser interference nano-lithography technique for fabrication of nano-structures. This is inspired by a 2pi-illumination system that consists of two cylindrical lens arranged face-to-face at a distance 2f with a common…

Due to the high complexity and technical requirements of industrial production processes, surface defects will inevitably appear, which seriously affects the quality of products. Although existing lightweight detection networks are highly…

Denoising Diffusion models are gaining increasing popularity in the field of generative modeling for several reasons, including the simple and stable training, the excellent generative quality, and the solid probabilistic foundation. In…