1,049 research outputs found

    Revolutionizing Pharmaceuticals: Generative Artificial Intelligence as a bibliographic assistant

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    [EN]Artificial Generative Intelligence (AGI) has exploded into biomedical and pharmaceutical research, fundamentally transforming the way scientists approach literature review, experiment design, and reagent and antibody selection. This article explores how IAG, supported by advanced machine learning and natural language processing models, has revolutionized these processes. The IAG streamlines literature review, extracting relevant information, identifying emerging patterns and trends in the scientific literature, and generating innovative hypotheses. It also acts as an advanced search tool, allowing researchers to quickly access accurate information in an ocean of data. A prominent example of this application is BenchSci, a platform that uses the IAG to recommend reagents and antibodies based on real experimental data and scientific literature. This integration of IAG into experimental design promises to accelerate research, reduce costs, and improve the precision of experiments. Together, the IAG is presented as a catalyst for discoveries in pharmaceutical and biomedical research, offering unprecedented potential to advance the understanding and treatment of diseases, and improve decision-making in the industry

    New Perspectives for Electrodialytic Remediation

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    Electrodialytic remediation has been widely used for the recovery of different contaminants from numerous matrices, such as, for example, polluted soils, wastewater sludge, fly ash, mine tailing or harbour sediments. The electrodialytic remediation is an enhancement of the electrokinetic remediation technique, and it consists of the use of ion-exchange membranes for the control of the acid and the alkaline fronts generated in the electrochemical processes. While the standard electrodialytic cell is usually built with three-compartment configuration, it has been shown that for the remediation of matrices that require acid environment, a two-compartment cell has given satisfactory removal efficiencies with reduced energy costs. Recycling secondary batteries, with growing demand, has an increasing economic and environmental interest. This work focusses on the proposal of the electrodialytic remediation technique as a possible application for the recycling of lithium-ion cells and other secondary batteries. The recovery of valuable components, such as lithium, manganese, cobalt of phosphorous, based on current recycling processes and the characterization of solid waste is addressed.This work has received funding from the European Union‚Äôs Horizon 2020 research and innovation programme under the Marie SkŇāodowska-Curie grant agreement No. 778045. Paz-Garcia acknowledges the financial support from the University of Malaga, project: PPIT.UMA.B5.2018/17. Villen-Guzman acknowledges the funding from the University of Malaga for the postdoctoral fellowship PPIT.UMA.A.3.2.2018. Universidad de M√°laga. Campus de Excelencia Internacional Andaluc√≠a Tec

    Electrodialytic Recovery of Cobalt from Spent Lithium-Ion Batteries

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    Contribuci√≥n en congreso cient√≠ficoRecycling lithium-ion batteries has an increasing interest for economic and environmental reasons. Disposal of lithium-ion batteries imposes high risk to the environment due to the toxicity of some of their essential components. In addition to this, some of these components, such as cobalt, natural graphite and phosphorus, are included in the list of critical raw materials for the European Union due to their strategic importance in the manufacturing industry. Therefore, in the recent years, numerous research studies have been focused on the development of efficient processes for battery recycling and the selective recuperation of these key components. LiCoO2 is the most common material use in current lithium-ion batteries cathodes. In the current work, an electrodialytic method is proposed for the recovery of cobalt from this kind of electrode. In a standard electrodialytic cell, the treated matrix is separated from the anode and the cathode compartments by means of ion-exchange membranes. A cation-exchange membrane (CEM) allows the passage of cations and hinders the passage of anions, while the behaviour of anion-exchange membrane (AEM) does the opposite. A three-compartment electrodialytic cell has been designed and assembled, as depicted in the figure. In the central compartment, a suspension of LiCoO2 is added. Different extracting agents, such as EDTA, HCl and HNO3, are tested to enhanced the dissolution and the selective extraction of the target metal. Dissolved cobalt-containing complexes migrate towards the cathode or the anode compartments depending on the ionic charge of the complexes. While cobalt extraction via extracting agents is an expensive treatment, as it requires the constant addition of chemicals, an efficient electrodialytic cell could allow the recirculation of the extracting agents and the economical optimization of the process.This work has received funding from the European Union‚Äôs Horizon 2020 research and innovation programme under the Marie SkŇāodowska-Curie grant agreement No. 778045. Paz-Garcia acknowledges the financial support from the University of Malaga, project: PPIT.UMA.B5.2018/17. Villen-Guzman acknowledges the funding from the University of Malaga for the postdoctoral fellowship PPIT.UMA.A.3.2.2018. Universidad de M√°laga. Campus de Excelencia Internacional Andaluc√≠a Tec

    The relationship between R&D subsidy and R&D cooperation in eco-innovative companies. An analysis taking a complementarity approach

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    We analyze whether eco-innovation has a positive or negative influence on the business performance of companies and, through the complementarity approach, whether the joint implementation of R&D subsidy and R&D cooperation increases or decreases the sum of their respective individual impacts on the business performance. If the joint implementation is substitutive, business performance will be lower than potentially possible, so granting R&D subsidies under the condition of establishing R&D cooperation would not be an adequate policy to promote eco-innovation. The analyses were performed using data from the Technological Innovation Panel (PITEC) of 2013 for Spanish manufacturing companies. Our findings indicate that an eco-innovation-oriented strategy positively affects the labor productivity of companies and that receiving public aid as a consequence of establishing R&D cooperation agreements has a lower effect on labor productivity (non-eco-innovative companies), or the same effect (eco-innovative companies), compared to the sum of the individual impacts of R&D cooperation and R&D subsidy. Consequently, in non-eco-innovative companies the use of subsidized R&D cooperation is inadvisable, while their use in eco-innovative companies is neutral

    Geometric documentation of the main refectory of the Monastery of Yuso (San Mill√°n de la Cogolla, La Rioja, Spain)

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    [ES] Se trata de una estancia de 35 x 9 metros de planta que se organiza con un banco corrido en tres de sus lados con un respaldo a modo de friso y una serie de mesas de madera, cuenta adem√°s con varias ventanas y tres l√°mparas que aportan la iluminaci√≥n, una puerta de acceso destacada en madera con cancel, p√ļlpito para la lectura y varios cuadros.El volum√©trico general al√°mbrico se ha realizado mediante topograf√≠a cl√°sica con estaci√≥n total. Para la documentaci√≥n del friso de madera y los cuadros se ha recurrido a fotograf√≠a que posteriormente se ha rectificado. Como resultados se presenta el modelo 3D y una colecci√≥n de planos.[EN] The refectory is a room of about 35x9 metres (plan) arranged with a continuous wooden bench in thee of the sides (all except the entrance) with a wooden frieze as the back of the bench, a series of tables, a pulpit, a detached door with chancel screen and some pictures.A general wireframe model in 3D was obtained by means of total station. The decoration of the back of the bench is drawing from rectified photographs and the same methodology was used to represent the pictures. As results, as well as the 3D model, a series of plans was generated.[ES] Memoria del proyecto (10 p√°ginas en formato PDF) y 7 fotograf√≠as de documentaci√≥n (formato JPEG)[EN] Report of the proyect (10 pages in Spanish in PDF format) and 7 photographs for documentation purposes (JPEG)

    Alternative reducing agents for Lithium-Ion batteries recycling via hydrometallurgical process

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    Lithium-ion batteries (LIB) are a key factor in the transition to a decarbonised and clean energy system due to their application in the power sector and electric transport. However, a growing demand of these batteries involves two direct problems: an increase in the generation of spent LIBs as well as in the demand of raw materials. Hence, the development of efficient recycling treatment of LIBs is crucial to make them a true enabler of the green transition. Currently, the LIBs recycling process can be divided into pyrometallurgical and hydrometallurgical. The first one is based on the treatment of LIBs at high temperatures to produces metal pyrolysis and metal reduction, while the second method consists in the recovery of metals via acidic leaching. Although pyrometallurgical method is the most used in the industry, hydrometallurgical process presents a series of advantages, such as low energy consumption, high metal recovery and high product purity, that make it more promising in the search of more effective recycling method. In the hydrometallurgical process, the addition of acids and reducing agents is required to dissolve the solid particles and extract the valuable metals. The purpose of this work was to evaluate the effect of alternative reducing agent in the leaching process to maximize the amount of metal (Mn, Li, Ni, Co) recovered from a real LIBs waste. With this aim, the leaching processes were carried out using as reducing agent H2O2, Fe and NH4Cl. According to the experimental results, Fe and NH4Cl enhance the extraction yield as well as the reaction time comparing with the results obtain using H2O2.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

    Acid leaching of LiCoO2 enhanced by reducing agent. Model formulation and validation.

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    In this work, a model has been formulated to describe the complex process of LiCoO2 leaching through the participation of competing reactions in acid media including the effect of H2O2 as reducing agent. The model presented here describes the extraction of Li and Co in the presence and absence of H2O2, and it takes into account the different phenomena affecting the controlling mechanisms. In this context, the model predicts the swift from kinetic control to diffusion control. The model has been implemented and solved to simulate the leaching process. To validate the model and to estimate the model parameters, a set of 12 (in triplicate) extraction experiments were carried out varying the concentration of hydrochloric acid (within the range of 0.5‚Äď2.5 M) and hydrogen peroxide (range 0‚Äď0.6%v/v). The simulation results match fairly well with the experimental data for a wide range of conditions. Furthermore, the model can be used to predict results with different solid-liquid ratios as well as different acid and oxygen peroxide concentrations. This model could be used to design or optimize a LiCoO2 extraction process facilitating the corresponding economical balance of the treatment.This work has received funding from the European Union‚Äôs Horizon 2020 research and innovation programme under the Marie SkŇāodowska- Curie grant agreement No. 778045 and the ‚ÄúProyectos I+D+i en el marco del Programa Operativo FEDER Andaluc√≠a 2014‚Äď2020‚ÄĚ, Project no. UMA18-FEDERJA-279. Cerrillo-Gonzalez acknowledges the FPU grant (FPU18/04295) obtained from the Spanish Ministry of Education. Funding for open access charge: Universidad de M√°laga / CBUA

    Predicci√≥n de vol√ļmenes comerciales de Eucalyptus grandis a trav√©s de modelos de volumen total y de raz√≥n

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    Eight total volume and four volume-ratio models were evaluated for use in a system for predicting marketable volumes in¬†Eucalyptusgrandis¬†plantations. Data were collected from 101 trees in stands at harvest age, located in Salento, Quindio. Weighted regression was used to avoid problems of heteroscedasticity in the fit of total volume models. An autoregressive error structure was used to reduce autocorrelation of longitudinal data used in the fit of the volume-ratio models. After evaluation of goodness of fit and prediction, the models of¬†Schumacher & Hall (1993)¬†as total volume model and¬†Cao¬†etal.¬†(1980)¬†as volume-ratio model were selected. The bias and average error in the prediction of marketable volumes to variable-top diameter limits of 0, 5 and 10 cm were always below 4.4% and 11.5%, respectively. The functionality of the system to quantify marketable volumes during the construction of stand and stocks tables was demonstrated.Ocho ecuaciones de volumen total y cuatro modelos de volumen de raz√≥n fueron evaluados con el objetivo de seleccionar el mejor modelo de volumen total y de raz√≥n de volumen, a fin de ser utilizados en un sistema para la predicci√≥n de vol√ļmenes comerciales en plantaciones de¬†Eucalyptus grandis. Los datos usados en el estudio corresponden a 101 √°rboles colectados en rodales a la edad de cosecha, ubicados en el municipio de Salento, Quind√≠o. T√©cnicas de regresi√≥n ponderada fue utilizada para evitar problemas de heterocedasticidad en el ajuste de modelos de volumen total. Una estructura autorregresiva del error se emple√≥ para disminuir la autocorrelaci√≥n, propia de los datos longitudinales utilizados en el ajuste de los modelos de volumen de raz√≥n. A partir de la evaluaci√≥n de la bondad de ajuste y predicci√≥n fueron seleccionados los modelos de:¬†Schumacher & Hall (1993), como modelo de volumen total, y¬†Cao¬†etal.¬†(1980)¬†como modelo de volumen de raz√≥n. El sesgo y el error promedio en la predicci√≥n de vol√ļmenes comerciales hasta los √≠ndices de utilizaci√≥n 0, 5 y 10 cm estuvieron siempre por debajo de 4.4% y 11.5%, respectivamente. Finalmente, se demuestra la funcionalidad del sistema de cuantificaci√≥n de vol√ļmenes comerciales en la construcci√≥n de tablas de rodal y existencias

    Inteligencia Artificial Generativa en Farmacología: Revolucionando la Interacción Fármaco-Proteína

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    [ES]En la era moderna de la medicina, la inteligencia artificial (IA) est√° desempe√Īando un papel cada vez m√°s prominente en la farmacolog√≠a. Este art√≠culo destaca la influencia transformadora de la IA generativa en el estudio y optimizaci√≥n de interacciones f√°rmacoprote√≠na. A trav√©s del an√°lisis detallado de modelos como las Redes Generativas Adversariales (GANs) y los Transformers, se ilustra c√≥mo la IA puede predecir y refinar las interacciones entre medicamentos y prote√≠nas, llevando a terapias m√°s eficientes y seguras. Adem√°s, se discute la capacidad de la IA generativa para prever interacciones cruzadas entre f√°rmacos, reduciendo as√≠ el potencial de efectos secundarios y complicaciones relacionadas con la polifarmacia. La conclusi√≥n subraya la sinergia entre la investigaci√≥n farmacol√≥gica tradicional y la IA, delineando un futuro optimista para el dise√Īo y optimizaci√≥n de medicamentos en la medicina del siglo XXI

    Characterization and modeling of lithium-polymer commercial batteries

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    Lithium-ion batteries are key for the modern society as they are present in many energy storage devices and have promising future perspectives in the field of electric cars and energy accumulators from renewable sources. Herein, we present results from charge and discharge cycles on batteries with controlled conditions. The cyclability of commercial lithium-polymer ‚Äúpouch‚ÄĚ batteries, has been studied under different charge/discharge rate and temperatures. The relationship between the state of charge and the cell voltage has been obtained, and the degradation of the cell energy capacity after a number of cycles has been measured. Furthermore, the experimental results have been compared with simulations based on Newman‚Äôs model for Lithium Ion Batteries, carried out using COMSOL Multiphysics software. The results show the correlation between temperature, C-rate and degradation in lithium ion batteries. It is especially remarkable the decrease of the apparent capacity of batteries at low temperatures, and the increase of the degradation at higher temperatures. These results are essential for the design of control mechanisms that can prevent battery failure.Universidad de M√°laga. Campus de Excelencia Internacional Andaluc√≠a Tech. Plan Propio de Investigaci√≥n y Transferencia de la Universidad de M√°laga, Proyecto Puente B.5, c√≥digo: PPIT.UMA.B5.2018/1
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