Abstract:
Generic models for the gravitational-wave (GW) signal emitted by binary black hole (BBH) mergers are an open-problem in GW astronomy, mainly due to the lack of numerical relativity simulations, which are numerical solutions of the Einstein field equations.In this project we systematically investigate a subspace of the huge parameter space of a generic BBH with the goal to analyze the phenomenology of these unexplored regions of parameter space, and develop modeling techniques which can be applied to enhance and extend existing waveform models to the most physically complete scenario.

Abstract:
Around 100 gravitational wave (GW) detections have been made to date with the ground-based LVK detector network. Accurate measurements of the properties of the binaries producing these signals are crucial for astrophysical inferences (such as population studies and binary formation mechanisms) and for cosmological studies (such as the measurement of the Hubble constant). Precessing binaries, where the spins of the black holes are not aligned with the orbital angular momentum of the binary, are of particular interest. Hints of a population of such systems have already been identified. We propose an assessment of the reliability and accuracy with which current GW signal models and data analysis techniques can ascertain the properties of these systems and the improvements required to meet the challenges posed by current and future detectors.

Abstract:
With the LIGO-Virgo network operating through its fourth observing run, the number of gravitational-wave detections is bound to grow at a steady pace. Gravitational waveform models are a key element in the analysis of compact binary mergers. In this project, we will thoroughly test several advancements in the field of gravitational waveform modelling that will allow us to reach a better understanding of the properties of coalescing binaries. We will focus on three main aspects that can leave characteristic imprints on gravitational-wave signals: eccentricity, gravitational-wave memory and extreme matter effects. Our new models combine accuracy and efficiency to fully reap the potential of future observations.

Abstract:
The computational activity proposed takes place in the context of the ERC Consolidator project Integrated System Analysis of Urban Vegetation and agriculture(URBAG, 2019-2024). Given the need of cities to increment green areas and local agriculture to promote urban sustainability, URBAG aims to provide the knowledge and tools to evaluate which combinations of agriculture and green spaces result in the best performance in terms of air quality, heat wave and climate change mitigation, as well as ecosystem services provided to urban dwellers. To do so, URBAG uses, develops, and improves atmospheric models at the urban scale with the aim to evaluate 1) biogenic CO2 emissions in urban areas, 2) how agriculture, vegetation and changes in land use will affect local climate and biogenic emissions.

Abstract:
This project focuses on optimizing the detection of eccentric and precessing binary black holes (BBHs) using the unmodeled gravitational wave (GW) search pipeline, pycWB. Building on expertise and resources from prior RES projects, we aim to enhance the pipeline’s sensitivity and explore advanced clustering algorithms to capture multi-burst signatures of eccentric BBHs. Detecting such systems is crucial for understanding BBH formation channels and orbital dynamics, offering insights into GW astronomy. This study also prepares pycWB for integration into LIGO’s standard pipeline and future observatories like LISA and the Einstein Telescope.

Abstract:
The fourth observing run of the LIGO-Virgo-KAGRA network offers unprecedented distance reach and event rates for studying gravitational waves from compact binary coalescences. This also allows finding promising candidates for the never-before detected gravitational lensing of gravitational waves by massive objects in the universe. This can produce both multiple images of the same source or complex waveform deformations. We use RES supercomputers to study such candidates in-depth with massively parallel Bayesian parameter estimation and the latest signal models, in addition to tests on realistic simulated signals. Such detections will provide a new probe of the cosmos, in particular for measuring the cosmic expansion rate, testing the nature of gravity, and studying populations of exotic compact objects.

Abstract:
The Balsinde group is investigating the link between lipin-2, a key regulator of inflammation, and ethanolamine plasmalogens, a type of lipid. 1 Preliminary data suggest that lipin-2 affects plasmalogen levels in mitochondria. This project aims to understand how lipin-2 controls plasmalogen metabolism and how these lipids influence inflammation. Researchers will study immune cells and animal models to uncover new therapeutic targets for inflammatory diseases. Using advanced lipidomics, genomics, and high-performance computing (HPC) resources, they hope to reveal the molecular mechanisms involved and pave the way for future treatments.

Abstract:
This project aims to advance the research of bioactive natural products through the integration of genomics and metabolomics, using cutting-edge bioinformatics tools. The goal is to identify and characterize biosynthetic genes and metabolites of interest by analyzing sequencing and mass spectrometry data to predict chemical structures and metabolic pathways. The results will enable the development of sustainable bioprocesses and the exploitation of biological resources for pharmaceutical and environmental applications, contributing to the advancement of biotechnology and precision medicine.

Abstract:
This Activity will take place as part of the project entitled “Evolution and adaptation of Enterococcus faecium during intestinal colonisation and infection” funded by a “Proyecto de Generación de Conocimiento 2023” grant (reference: PID2023-152061NA-I00) awarded by the Agencia Estatal de Investigación. The aim of this Activity is to identify putative adaptive genetic variation accumulated in the genomes of Enterococcus faecium strains during episodes of colonisation or infection in the same host, using large datasets of sequenced E. faecium strains. To differentiate adaptive from neutral background mutations, we will apply a genome-wide mutation enrichment approach to identify loci in the bacterial genome under parallel and convergent evolution, which represents one of main research objective of this project.

Abstract:
Are there some general principles that developmental networks need to fulfill in order to be able to lead to the development of complex robust morphologies? To answer this, we will simulated morphological evolution using complexity as selection criterion. Evolution will be studied by integrating a realistic computational model of development, with a population genetics model that considers reproduction, mutation, genetic recombination and evaluates fitness of morphologies. Then morphological transitions will be traced and the underlying changes in developmental mechanisms analyzed. We expect to identify how developmental mechanisms (changes in the topology, interaction strengths, and regulated cellular behaviors of gene networks) affect adaptive dynamics in the in silico evolution experiments and lead to complex and robust morphologies.

Abstract:
Observing the exciton dynamics in 2D materials at the attosecond time scale is one of the main current challenges for attosecond experiments. Those experiments require of theoretical modelling for interpreting the measurements and correlate them with the light-driven dynamics. One fundamental aspect on those experiments is the role of the screening effects when the system is driven out of equilibrium. Here we plan to simulate a realistic pump probe experiment and unravel the effects of screening due to the probe interaction.

Abstract:
Heat conduction in low-dimensional materials deviates from Fourier’s law, which governs conventional diffusive transport. This project explores the transition from ballistic (abnormal) to diffusive heat transport in single-molecule contacts, building on our recent work [https://www.nature.com/articles/s41563-025-02195-w], where we observed room-temperature phonon interference—evidence of ballistic heat conduction. We aim to pinpoint the critical length where coherent transport breaks down and a thermal gradient forms. Using all-atom molecular dynamics, we will simulate junctions from 1 nm to 4 µm. The large system sizes and long simulation times require the massive computational power of RES. Our goal is to bridge chemically accurate models with experiments and clarify how thermal conductivity scales in low-dimensional systems.

Abstract:
In this project, we perform extremely efficient ab initio simulations in order to obtain a remarkably accurate description of the diffusion process of the proton and hydroxide ions in heavy and light water, including the IR spectra. This is crucial for understanding a huge number of scientific problems, and for developing and improving many technological and industrial applications, in particular for materials for energy generation and storage in many domains (from electrochemistry to nuclear technology).In addition, the data generated will be used as extremely reliable reference data for the training of machine learning potentials, further extending the number and depth of the possible applications.

Abstract:
This project investigates the catalytic properties of molybdate (AMoO₄) and tungstate (AWO₄) nanostructures, focusing on their ability to generate reactive oxygen species (ROS) and perform selective oxidation. Their wide bandgaps promote efficient charge separation, enabling ROS production under light and dark conditions, making them versatile for environmental and biomedical applications. Structural and electronic tuning, including defect engineering, enhances reactivity by stabilizing polarons and modifying surface properties. Advanced density functional theory (DFT) methods are employed to explore the impact of oxygen vacancies on electronic structures and adsorption dynamics, providing mechanistic insights that drive rational catalyst design.

Abstract:
Gas sensors are critical for detecting disease biomarkers (e.g., acetone) and environmental toxins. This project designs room-temperature CeO₂/WO₃, Ag/WO₃, and Ag/CeO₂/WO₃ nanoheterojunctions via microwave synthesis and femtosecond-laser irradiation (FLI) to address power inefficiency and humidity interference. FLI-engineered defects and Ag clusters enhance charge transfer and VOC adsorption. Structural (XRD/HRTEM) analyses validate heterojunction formation. Density functional theory (DFT) simulations will predict O₂ activation, reactive oxygen species (ROS) generation, and WO₃-CeO₂-Ag synergies. Sensors achieve <0.5 ppm acetone detection, <30 s response, and humidity resilience at <50 mW. This work advances low-energy gas sensing for healthcare, safety, and scalable environmental monitoring.

Abstract:
An alternative catalytic route to the energy-intensive steam reforming of ethane to produce ethylene is investigated in this project. The process consists of two steps, a partial oxidation of ethane to ethanol followed by ethanol dehydration to ethylene. The proposed catalysts are Cu-exchanged zeolites containing both Cu cations acting as redox active sites for the oxidation step and Brønsted acid sites that promote the dehydration step. The periodic DFT study of the reaction mechanism on different catalyst models will allow to predict the relative concentration and distribution of redox and acid sites that maximizes the ethane conversion and the selectivity to ethylene, facilitating the synthesis of optimized catalyst for an efficient transformation of ethane into ethylene.

Abstract:
Noble metals supported on reducible metal oxides, such as Pt/CeO2, are efficient CO oxidation catalysts for gas emissions control. However, the CeO2 support that promotes high catalytic activity tends also to promote catalyst deactivation by turning metallic Pt clusters into less-active PtOx species under reaction conditions. This undesired activity/stability correlation has been broken using a nanostructured CeO2 support that traps small Pt NPs at V-shaped pockets present on CeO2. A thorough computational analysis of the competing CO oxidation to CO2 and Pt oxidation to PtOx mechanisms on Pt/CeO2 models with different CeO2 nanostructure, different degree of reduction of the support and different Pt particle size will help to improve the overall catalytic performance of this promising material.