BUSCADOR RECOLECTA

Project developed by Giovanni Federico (Università di Pisa) and Antonio Tena Junguito (Universidad Carlos III de Madrid). This data base outlines changes in world trade from 1800 to 2016. Dataset: International Commodity Prices

Project developed by Christopher Absell (University Gothenburg and Instituto Figuerola) Giovanni Federico (New York University Dubai) and Antonio Tena Junguito (Universidad Carlos III de Madrid and Instituto Figuerola). Dataset: Serbia and Montenegro

Software to explore the plasma structure around a cylindrical emissive probe using Orbital Motion Theory (OMT).

Project developed by Christopher Absell (University Gothenburg and Instituto Figuerola) Giovanni Federico (New York University Dubai) and Antonio Tena Junguito (Universidad Carlos III de Madrid and Instituto Figuerola). Dataset: Pakistan

Project developed by Christopher Absell (University Gothenburg and Instituto Figuerola) Giovanni Federico (New York University Dubai) and Antonio Tena Junguito (Universidad Carlos III de Madrid and Instituto Figuerola). Dataset: Cambodia

Conjunto de datos a los que se hace referencia en la monografía: López-Guadalupe Pallarés, Miguel José (2023). Redes y estrategias de ascenso en la Monarquía Hispánica. La familia Malvezzi y el Colegio de España en Bolonia (siglos XV-XVI). Madrid: Universidad Carlos III de Madrid - Dykinson. Colección Historia de las Universidades, 66. http://hdl.handle.net/10016/36487

Project developed by Christopher Absell (University Gothenburg and Instituto Figuerola) Giovanni Federico (New York University Dubai) and Antonio Tena Junguito (Universidad Carlos III de Madrid and Instituto Figuerola). Dataset: Saudi Arabia

Description of the project

This experimental work is part of the "Work Package 4 - Diagnosis of Li-ion cells and modules" of the project "Research and development of a highly automated and safe streamlined process for increased Lithium-ion battery repurposing and recycling". Acronym (REBELION). Project number: 101104241. Program: HORIZON-CL5-2022-D2-01-10, European Climate, Infrastructure and Environment Executive Agency (CINEA), European Commission.

The aim of the project is to develop a diagnosis methodology for lithium‐ion batteries that allows telling apart batteries fitted for second life applications from batteries that have reached the end of their life and need to be disassembled for recycling their components.

The following three novel diagnosis methods will be investigated in this project:

1. Electrochemical noise analysis (ENA): It consists of analyzing the voltage noise signal when the cell is subjected to a constant current. The noise signal is frequency decomposed, obtaining a characteristic pattern of the SoH.
2. Current steps (CS): Application of small current steps when the battery operates at constant current. The dynamic behavior of the voltage allows fitting to the parameters of an equivalent electrical model that will provide information to identify the SoH of the battery.
3. High‐frequency current steps (HF‐CS), which, like the CS technique, apply current steps, but in this case, only high‐frequency current steps are applied to determine the purely ohmic resistance of the battery.

The application of these three novel methods will be contrasted with other methods commonly used for identifying the SoH of batteries, but that do not satisfy the requirements posed in this project concerning diagnosis process time, and equipment. These commonly used methods include Incremental capacity analysis (ICA), Open circuit voltage (OCV), Electric impedance spectroscopy (EIS), and maximum State of charge (SoC).

Description of the dataset

This dataset contains the results obtained from the execution of multiple experiments designed to facilitate the diagnosis of the state of health of Lithium-ion cells. The dataset involves the evaluation of 77 cells of the type Samsung INR21700-50E. The evaluated cells have been previously aged by means of a variable number of charge-discharge cycles (cf. related dataset), in order to obtain a distribution of states of health between 100% and 80%. The dataset is structured as follows. Cells are identified with a name composed of a combination of: group number, cycling strategy and cell ID:

• The group number corresponds to the group defined by the aging experiment (cf. related dataset). Each group was planned to be cycled with a number of cycles.
• The cycling strategy describes the type of charge and discharge procedure used during cycling.
• The cell ID corresponds to A or B, since two cells are used in each cycling run.

Each evaluated cell is contained in a directory, named with the cell name (e.g., "C4-CC-A"), that stores the results of the experiments performed to that cell. These experiments include EIS in OCV and at 0.2C discharge, ENA, HFSTEPS and LFSTEPS. They also include a measure of the room temperature during the experimental run.

Base Datos de la red social Instagram del proyecto COMPREV(P)CANCER

Entrevista a Sara Delgado en Piedras Albas. El ganado. La matanza del cerdo. Animales salvajes y domésticos. La caza., O gado. A matança do porco. Animais selvagens e domésticos. A caça., The cattle. Tha slaughter of the pig. Wild and domestic animals. The hunt.