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Materials properties, battery data, semiconductor, alloys, polymers, additive manufacturing
1,305 datasets
20,000 reinforcement learning transitions for IoT device control, focusing on battery management and solar or wind energy harvesting. The dataset was published on Kaggle and is associated with artificial intelligence and deep learning applications. The author, organization, and last update date are not specified.
Kaggle hosts a dataset of electric vehicles in India. The dataset is described as clean and includes information on vehicle price, driving range, and battery. The author, organization, and specific size are unknown.
A dataset likely related to adaptive process control for thermoplastic additive manufacturing using reinforcement learning. The data was sourced from Kaggle and is categorized as research material. The specific volume, authorship, and update history are not provided.
A large-scale time-series dataset tracks the performance of lithium-ion batteries from multiple manufacturers. It contains measurements for state of health (SOH), state of charge (SOC), and fault conditions. The dataset is sourced from Kaggle, but the author, organization, and specific update date are unknown.
A dataset related to enhanced oil recovery (EOR) techniques using biosurfactants and polymers. The dataset is hosted on Kaggle, but its specific size, origin, and creation date are unknown. Columns likely contain measurements related to material properties and recovery performance.
Hailo_dataflow_compiler is a dataset published on Kaggle. Its title suggests it relates to compiler tools or data for optimizing AI workloads on Hailo hardware. The dataset's specific content, size, and provenance are not detailed in the provided metadata.
BatteryLife Raw provides the complete cycle test capacity data from the CALB dataset, originally used for battery life prediction. The dataset was released by the Battery-Life organization on Hugging Face in December 2025. It is intended for battery informatics tasks and serves as a benchmark for predictive modeling.
Kaggle hosts a dataset on additive manufacturing research. The dataset likely contains experimental data on gradient hybrid lattice structures incorporating boron. The author, organization, and temporal coverage are unknown.
Kaggle hosts a dataset for polymer extrusion rheology prediction. The dataset likely contains sensor readings from multiple instruments integrated into a real-time monitoring system. The author, organization, and specific data volume are unknown.
20,000 synthetic records of lithium-ion battery cells designed for quality control analysis in automotive manufacturing. The data incorporates multi-layered physical logic and simulated sensor noise alongside natural language processing components. Creator and publication date are not specified in the source metadata.
This dataset examines the relationship between mobile usage patterns and their direct impact on smartphone battery consumption. It is designed to help researchers and enthusiasts understand how specific user behaviors correlate with power drain. The dataset serves as a resource for exploring mobile hardware efficiency and user habits.
Kaggle hosts this dataset focused on lithium-ion battery performance. The title suggests it contains variables for predicting battery characteristics, though specific columns and volume are unknown. Metadata is minimal; actual content requires verification after download.
This dataset supports replication for a study analyzing Europe's electric vehicle battery rollout and the trade-offs of green industrial policy in a geoeconomic context. The data was authored by Palma Polyak and is hosted by Harvard Dataverse. Specific details on rows, columns, and file formats are unavailable.
Kaggle hosts the Polymer2025 dataset, which likely contains data related to polymer materials. The dataset is associated with a pre-trained model, suggesting it may be used for predictive tasks in materials science. Specific details on its size, origin, and update history are not provided in the available metadata.
A dataset for detecting chickens in battery cage environments, published on Kaggle. The dataset's license is CC BY 4.0, allowing free use with attribution. Specific details on size, collection method, and temporal coverage are not provided in the available metadata.
Mohs hardness is a qualitative scale ranking minerals by scratch resistance. The dataset likely contains values or classifications for materials based on this standard scale. Published on Kaggle, the exact content and scope require verification after download.
A dataset related to electric vehicle batteries, likely for use in AI and machine learning applications. It is hosted on the Kaggle platform. The specific contents, scale, and creation details are not provided in the available metadata.
A dataset likely related to battery performance and prediction. It is hosted on Kaggle, but detailed metadata such as column descriptions, size, and authorship are currently unavailable. The specific data collection method and time period are unknown.
Kaggle hosts a collection of datasets related to batteries. The specific content, size, and origin are unknown from the available metadata. Further details require verification after download.
A dataset titled 'battery dataset' is hosted on the Kaggle platform. The dataset's specific content, size, and origin are not detailed in the provided metadata. Users must download the dataset to verify its actual contents, such as the number of rows, features, and specific battery-related measurements.