Thrust I. Machine-learning-accelerated discovery of single atom catalysts
The power of machine learning has just begun to be harnessed in Single‐Atom Catalysts (SACs) research, with much room remaining for advancement. I am using machine learning to (A) accelerate catalyst screening, (B) find structure-property relations in catalysis data, (B) create interatomic potentials for rapid catalyst simulation, and (B) analyse catalytic mechanisms. Perspective and research articles on some of these topics, which we are currently working on, will be uploaded soon. We recently submitted our first article exploring how interpretable machine learning can shed light on the geometric and electronic-structure descriptors of catalysts. More details about this approach will be provided here soon.
Thrust II. Conversion of bio-oil to fuels and chemicals
Our world’s addiction to fossil fuels for transportation is unsustainable and emits huge amounts of greenhouse gases like CO2. The need to supply energy for transportation in a sustainable manner has motivated ongoing efforts to replace fossil fuels with renewable and CO2-neutral transportation fuels. One promising strategy is to produce transportation-grade fuels from biomass waste (e.g., bio-oil consisting of oxygenated aromatic lignin byproducts) through electrocatalytic hydrogenation (ECH) using renewable electricity, with an accompanying oxidation reaction such as water oxidation. My work aims to understand the electrocatalytic conversion of bio-oils at an atomistic level to help design improved catalysts (e.g., For more details, see our recent work where we combined DFT with experimental synthesis -here-)
Thrust III. Fundamental Catalytic Pathways on advanced Materials
This research focuses on understanding the dissociative chemisorption mechanisms of key molecules like water (H2O), hydrocarbon (CH4), and ammonia (NH3) on transition metal nanoalloys (TMN). Its interdisciplinary approach combines computational materials science, materials chemistry, and nanotechnology, targeting energy harvesting through systems relevant for industrial applications. A significant aspect is exploring TMN-based catalysts, a field ripe for discovery, especially in the principles of their design. Our goal is to fundamentally comprehend how TMN materials can be optimized for enhanced hydrogen (H2) production, a critical aspect for clean energy technology. Our aim is to create a comprehensive framework for computational materials design, including developing innovative software and a comprehensive database of nanoalloys.
Thrust IV. Computational modeling and design of materials for rechargeable battery
Fundamental studies of Li/Na-ion storage in electrode materials are critical for the further development of high-performance next generation Li/Na-ion batteries. The complex composition and rough morphology of typical electrodes makes it challenging to gain scientific insights. My research focuses on developing model electrodes with well-controlled chemical composition and morphology in thin-film form. These model systems facilitate advance characterization methods and allow us to achieve mechanistic understanding of Li/Na-ion storage in electrode materials.
Thrust V. Computational design of electrode/electrolyte interfaces battery
The solid–liquid interfacial reactivity and stability govern the efficiency and lifetime of electrochemical energy devices. Probing and improving the electrochemical solid–liquid interface under operating conditions represents frontier challenges in many aspects of energy sciences, including but not limited to electrocatalytic processes, energy storage and conversion, and chemical desing. We recently started research activities to modulate the electrode surface chemistry for enhancing the interfacial reactivity in batteries and electrocatalysis. My recent studies have also found that the high interfacial reactivity triggers undesired reactions with the electrolyte leading to structural changes at the electrode surface and ultimately performance degradation. Understanding the interplay between electrode surface chemistry and electrolyte composition will inform the design of better electrochemical interfaces at the atomic and molecular scales.
- Delft University of Technology
- N.Khossossi@tudelft.nl