Publicaciones en colaboración con investigadores/as de Universidad de León (378)

2024

  1. Analysis of gaseous emission and particle number size distributions in metal casting processes with binder jetting moulds

    Building and Environment, Vol. 252, pp. 111297

  2. Custard apple crop residues combustion: an overall study of their energy behaviour under different fertilisation conditions

    Biomass Conversion and Biorefinery, Vol. 14, Núm. 9, pp. 10459-10473

  3. Design of Mixtures and Manufacture of Self-Compacting Concretes with Recycled Aggregates (Eco-Concretes): Prediction of Compressive Strength Using Machine Learning Models

    Lecture Notes in Mechanical Engineering

  4. Detection and characterization of hailstorms over France using DPR data onboard the GPM Core Observatory

    Atmospheric Research, Vol. 302

  5. EUSO-SPB1 mission and science

    Astroparticle Physics, Vol. 154

  6. Identifying key environmental factors to model Alt a 1 airborne allergen presence and variation

    Science of the Total Environment, Vol. 917

  7. Indoor PM from residential coal combustion: Levels, chemical composition, and toxicity

    Science of the Total Environment, Vol. 918

  8. Microstructural, durability and colorimetric properties of concrete coated with a controlled application of graphene oxide

    Journal of Building Engineering, Vol. 86

  9. Performance of graphene oxide as a water-repellent coating nanomaterial to extend the service life of concrete structures

    Heliyon, Vol. 10, Núm. 1

  10. Progress and challenges in valorisation of biomass waste from ornamental trees pruning through pyrolysis processes. Prospects in the bioenergy sector

    Environmental Research, Vol. 249

  11. Real-Time Evaluation of the Uncertainty in Weather Forecasts Through Machine Learning-Based Models

    Water Resources Management, Vol. 38, Núm. 7, pp. 2455-2470

  12. The role of snow in scavenging aerosol particles: A physical-chemical characterization

    Science of the Total Environment, Vol. 906

  13. To determine the compressive strength of self-compacting recycled aggregate concrete using artificial neural network (ANN)

    Ain Shams Engineering Journal, Vol. 15, Núm. 2