State of the art

Aim of the workshop is gathering together an interdisciplinary group of leading researchers exchanging ideas and strategies on modelling charge (electronic, ionic) and proton transfer mechanisms in materials and complex systems for energy-conversion, -storage and catalysis applications [1,2,3]. The workshop will cover a wide range of transfer theories, computational methods (e.g., first-principles, molecular dynamics, ML/AI approaches), as well as software developments. The workshop will offer the opportunity to report the status of the art and establish new collaborative networks among different communities.

Detailed description

Charge and proton transfer are key processes underlying energy conversion and storage [4]. Modelling their static and time-dependent evolution allows for the design of new energy materials for applications in catalysis [5], opto-electronics [6], photovoltaics [7], electrochemical
energy storage devices [8] and biomimetic [9] systems.

Challenges in modelling transfer processes in energy materials are multiple, as related to the type of material (e.g., organic, inorganic, hybrid), the description of the materials’ structure over a broad range of scale-lengths (from the atomic up to the microscopic scale), and the ability to model time-dependent processes ranging from femto-seconds up to steady-state conditions. Electronic charge transfer events across materials are intrinsically complex phenomena, and a variety of theories and methods for their modelling in condensed phases have been proposed over the last decades [10], following the seminal contributions of Landau [11], Fröhlich [12], and Marcus [13].

Depending on the materials electronic structure and the strength of the electron-nuclei interactions, transport regimes can be generally classified as localized (e.g., non-adiabatic,
hopping/tunneling), intermediate (e.g., polaron) or delocalized (e.g., adiabatic, band transport). A fundamental role in determining the nature of the charge transfer regimes is however played by disorder effects [14]. Disorder can manifest as structural (e.g., vacations, dislocations, amorphous
phases), energetic (e.g., electrostatic and polarization effects) and thermal (e.g., nuclear oscillations) effects [15], and its atomistic description often requires multi-scale approaches
ranging from full quantum [16], mixed and classical [17] methods, recently coupled also to machine-learning and artificial intelligence approaches [18].

Besides electronic (e.g., hole, electron) transfer, ionic transport is another fundamental process occurring in condensed phases [19]. Developing theories and methods for understanding ion
transport would pave the way for the design of future energy materials and complex systems for electrochemical and biomimetic applications. While ion transport has been largely investigated for poly-electrolites and inorganic materials
[20] via ab-initio molecular dynamics (AIMD), classical (atomistic force field (FF) based) MD and ML/AI FF-MD, the mixed electronic-ionic transport, that is the spatial- and time-
dependent coupling between the electronic and ionic charges, is still underexplored [21]. Seminal contributions are present in the literature for organic semiconductors and poly-electrolites [22], however a fundamental understanding is absent.
Proton transfer represents a key process in many materials relevant to energy conversion, catalysis, and bio-inspired systems. Unlike heavier ions, protons exhibit pronounced quantum-mechanical behavior, such as tunneling and zero-point energy effects, which can strongly influence transport efficiency and mechanism [23]. In solid-state materials, such as metal–organic frameworks, perovskites, and proton-conducting ceramics, modeling proton transfer is essential for designing next-generation fuel cells and electrolytes [24]. In catalytic systems — including enzymatic mimics, metal–organic clusters, and heterogeneous surfaces — proton-coupled electron transfer (PCET) plays a critical role in reaction mechanisms underlying hydrogen evolution, CO₂ reduction, water splitting and, in general, dehydrogenation/hydrogenation reactions [25]. Accurately capturing these processes requires multi-scale approaches combining electronic structure methods (e.g., DFT, multistate PCET models) with molecular dynamics (e.g.,
ab initio MD, reactive force fields), and increasingly, machine learning tools for predicting free energy surfaces and kinetic barriers [26].

Despite advances, challenges remain in bridging time
and length scales, and in treating proton delocalization and solvation in realistic environments, especially under operando conditions [27]. 

In the workshop leading experts will gather together to provide a comprehensive overview of the current state-of-the-art approaches to describe both charge (electronic and ionic) and proton transfer at condensed phases. The workshop aims at covering a large variety of materials and complex systems, including the development of new theoretical approaches, computational methods and softwares.

Themes treated during the workshop will be:
- charge transport in organic materials (e.g., small molecules and polymers);
- charge transport in inorganic materials (e.g., oxides, perovskites, etc.);
- mixed ionic-electronic transport in energy materials and complex systems;
- proton transfer in energy materials and complex systems;
- methods and software development.