Welcome to the PROCODA DATABASE website, an integrated platform developed to provide detailed technical access to our chemical kinetics modeling framework and to serve as a centralized repository of simulated astrophysical ice chemistry.
This platform enables users to explore published models, retrieve Effective Rate Coefficients (ERCs; also named k-value)) derived from radiation-driven chemical simulations, and access quantitative datasets describing the chemical equilibrium states of irradiated ice analogs. Users can also perform targeted searches and download numerical outputs for further analysis and model validation.

What is PROCODA?

PROCODA (PROgram for solving COupled Differential equations set for Astrochemistry) is a computational tool developed by Dr. Sergio Pilling and his collaborators (notably introduced in Pilling et al. 2022, ApJ, 925, 147 with thermochemistry upgrades at Pilling et al. 2023, ApJ, 952, 17 and Pilling et al. 2023, ASR, 71, 5466 ). It is specifically designed to simulate and interpret the chemical evolution of astrophysical ices (such as H₂O, CO₂, CO, CH₄, CH₃CN, HCOOH and several ice mixtures) when they are exposed to ionizing radiation in space-analog environments.

The code bridges the gap between laboratory experiments, where infrared spectroscopy (FTIR) monitors the destruction of parent molecules and the formation of new species, and theoretical models that describe the kinetics of these processes. The original version of the code can be download by clicking here: PROCODA_v3.zip (not available yet).

How it works: the mechanism

The core functioning of PROCODA is based on the following principles:

• System of coupled differential equations:
  The chemical network is treated as a set of interconnected differential equations that describe the rate of change of the column density (abundance) of each molecular species over time. The model accounts for:
  • Direct dissociation: destruction of parent molecules by radiation.
  • Bimolecular and termolecular reactions: formation of daughter and granddaughter species via recombination of fragments or reactions between molecules.
  • Desorption processes: radiation-induced transition of molecules from the solid (ice) phase to the gas phase.

• Fitting and optimization:
  PROCODA uses experimental data—typically obtained via FTIR spectroscopy—as input. It employs minimization algorithms (such as L-BFGS-B) together with a score function to find the best agreement between experimental measurements and the theoretical model. This procedure allows the determination of:
  • Effective rate coefficients (ERCs), describing the speed of individual reactions.
  • Cross sections, quantifying the probability of molecular destruction or formation induced by a given radiation field.

• Prediction of non-observed species:
  One of the most powerful features of PROCODA is its ability to predict the presence of chemical species that may lie below the detection limits of laboratory instrumentation. While experiments often detect only a handful of dominant molecules, the code can simulate networks involving hundreds of reactions, revealing a much richer and more complex ice chemistry.

• Chemical equilibrium phase (CE):
  PROCODA can extrapolate experimental results to long timescales (high radiation fluences), identifying the chemical equilibrium stage at which formation and destruction rates balance. This provides insight into the final chemical composition of ices in evolved astrophysical environments such as molecular clouds and protoplanetary disks.

Relevance to astrochemistry

By providing precise reaction rates and enabling the identification of complex organic molecules (COMs) formed in astrophysical ices, PROCODA contributes directly to our understanding of how prebiotic molecules may be synthesized on dust-grain surfaces in space, prior to their incorporation into comets, planetesimals, and planets.

Citation Guidelines

When using data or results from the PROCODA DATABASE in scientific publications, please cite the database (www.univap.br/procoda) together with the primary methodological references: Pilling et al. 2022, ApJ, 925, 147 , Pilling et al. 2023, ApJ, 952, 17 , Pilling et al. 2023, ASR, 71, 5466 and the specific ice's publication obtained from the list below.

DATABASE INFO

The list of all molecules in the models is (125):
H, H2, H3, C, CH, N, CH2, CH3, O, CH4, OH, NH3, H2O, NH4, H3O, C2, CC, CCH, CHCH, CH2CH, C2H3, CO, CO, N2, CH2CH2, C2H4, HCO, C2H5, CH3CH2, NO, H2CO, N2H2, CH3CH3, HNO, CH3O, CH2OH, O2, O2, CH3OH, HO2, H2O2, C3, C3H, H2CCC, C3H2, CH2CCH, C3H3, C2O, C3H4, CH3CCH, C2OH, CH2CHCH2, C3H5, CH3CHCH, N3, HCCOH, H2CCO, CH3CHCH2, CH2CH2CH2, CH2CHCH3, CH3CH2CH2, CO2, N2O, CH3CHO, CH2OCH2, CH2CHOH, CH3CH2CH3, HOCO, HOCHCH3, NO2, H2CO2, CH2OO, HCOOH, CH3OCH3, CH3CH2OH, HNO2, O3, CH3OOH, CH2OHOH, HO3, C4H, H2CCCC, HCCCCH, C3O, CH2CHCCH, C3OH, C2O2, CH2CCH3CH3, CH2CHCH2CH3, CH2CH2CH2CH2, CH3CHCHCH3, CH3COCH2, CH3COCH3, C2H3O2, CO3, N2O2, CH3COOH, OHCH2CHO, OHCHCHOH, HCOOCH3, CH3CH2CH2OH, CH3OCH2CH3, CH3CHOHCH3, HCO3, CH3OCHOH, NO3, H2CO3, CH3OOCH3, HOCH2CH2OH, CH3OCH2OH, CH3CHOHOH, C3HCCH, HNO3, C4O, CH3C4H, C3O2, C2O3, OHCCOOH, N2O3, C5O, CH3CH2CHOHOH, C4O2, N2O4, C5O2, N2O5.

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