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RESPACK is a first-principles calculation software for evaluating the interaction parameters of materials and is able to calculate maximally localized Wannier functions, response functions based on the random phase approximation and related…
Molecular transitions -- such as protein folding, allostery, and membrane transport -- are central to biology yet remain notoriously difficult to simulate. Their intrinsic rarity pushes them beyond reach of standard molecular dynamics,…
Machine learning (ML) is increasingly becoming a common tool in computational chemistry. At the same time, the rapid development of ML methods requires a flexible software framework for designing custom workflows. MLatom 3 is a program…
Additive manufacturing at the micro- and nanoscale has seen a recent upsurge to suit the increasing demand for more elaborate structures. However, the integration and precise placement of multiple distinct materials at small scales remain a…
Machine learning (ML) offers a powerful path toward discovering sustainable polymer materials, but progress has been limited by the lack of large, high-quality, and openly accessible polymer datasets. The Open Polymer Challenge (OPC)…
This paper presents OpenAirLink(OAL), an open-source channel emulator for reproducible testing of wireless scenarios. OAL is implemented on off-the-shelf software-defined radios (SDR) and presents a smaller-scale alternative to expensive…
Advanced holographic techniques are increasingly demanded for high-capacity and secure information processing. In this context, orbital angular momentum (OAM) stands out as a powerful resource for optical multiplexing, offering access to an…
In additive manufacturing, the optimal processing conditions need to be determined to fabricate porosity-free parts. For this purpose, the design space for an arbitrary alloy needs to be scoped and analyzed to identify the areas of defects…
Developing generalizable AI for medical imaging requires both access to large, multi-center datasets and standardized, reproducible tooling within research environments. However, leveraging real-world imaging data in clinical research…
Additive manufacturing using light is commonly constrained by serial voxel-by-voxel or layer-by-layer processing, which fundamentally limits fabrication speed and scalability. Here, we introduce a single-exposure holographic…
In this paper, we introduce OpenVSLAM, a visual SLAM framework with high usability and extensibility. Visual SLAM systems are essential for AR devices, autonomous control of robots and drones, etc. However, conventional open-source visual…
The Core Imaging Library (CIL) is an open-source versatile Python framework for solving inverse problems with special emphasis on imaging applications such as computed tomography (CT), using a plug-in architecture for data and operators,…
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating external knowledge, leading to improved accuracy and relevance. However, scaling RAG pipelines remains computationally expensive as retrieval sizes…
With the increased interest in computational sciences, machine learning (ML), pattern recognition (PR) and big data, governmental agencies, academia and manufacturers are overwhelmed by the constant influx of new algorithms and techniques…
Pressure sensors are popular in a large variety of industries. For some applications, it is critical for these sensors to come in a flexible form factor. With the development of new synthetic polymers and novel fabrication techniques,…
We present the Open MatSci ML Toolkit: a flexible, self-contained, and scalable Python-based framework to apply deep learning models and methods on scientific data with a specific focus on materials science and the OpenCatalyst Dataset. Our…
Complementary-label learning (CLL) is a weakly supervised learning paradigm for multiclass classification, where only complementary labels -- indicating classes an instance does not belong to -- are provided to the learning algorithm.…
Advanced manufacturing with new bio-derived materials can be achieved faster and more economically with first-principle-based artificial intelligence and machine learning (AI/ML)-derived models and process optimization. Not only is this…
Additive manufacturing (AM) techniques have been used to enhance the design and fabrication of complex components for various applications in the medical, aerospace, energy, and consumer products industries. A defining feature for many AM…
Three-dimensional (3D) printing is a powerful development tool both in industry, as well as in biomedical research. Additive-lathe 3D printing is an emerging sub-class of 3D printing whereby material is layered outward from the surface of a…