arXiv subjects

Emanuele Marsili

Publications and source records attributed to Emanuele Marsili.

7 recordsLinked to original sources

arXiv2026

The Future of Computing for Materials Science Challenges

Materials discovery increasingly relies on the coordinated use of theory, computation, experiment, data-driven methods, and emerging quantum technologies, yet the full potential of these tools is realised only when they operate within workflows that reflect the complexity of real systems. This perspective summarises current capabilities, limitations, and opportunities across these domains, drawing on contributions from academia, industry, and national laboratories to identify the scientific and structural requirements for more reliable and efficient discovery. Classical simulations provide broad coverage across design spaces, while experimental measurements reveal degradation, heterogeneity, and kinetic processes that determine performance under realistic conditions. Machine learning accelerates exploration when supported by well-curated datasets with clear provenance and uncertainty quantification, and quantum computing offers promising routes into correlated electronic behaviour when aligned with properties that influence engineering decisions. Collectively, these insights highlight the need for reproducible workflows, shared data standards, realistic benchmarks, and a research culture that prepares scientists to work across paradigms. By integrating these methodological and organisational elements, the community can move toward discovery processes that deliver robust predictions, support confident decision making, and shorten the path from conceptual design to deployable materials.

cond-mat.mtrl-sci↗

arXiv2025

Simulating non-trivial incompressible flows with a quantum lattice Boltzmann algorithm

Quantum algorithms have been identified as a potential means to accelerate computational fluid dynamics (CFD) simulations, with the lattice Boltzmann method (LBM) being a promising candidate for realizing quantum speedups. Here, we extend the recent quantum algorithm for the incompressible LBM to account for realistic fluid dynamics setups by incorporating walls, inlets, outlets, and external forcing. We analyze the associated complexity cost and show that these modifications preserve the asymptotic scaling, and potential quantum advantage, of the original algorithm. Moreover, to support our theoretical analysis, we provide a classical numerical study illustrating the accuracy, complexity, and convergence of the algorithm for representative incompressible-flow cases, including the driven Taylor-Green vortex, the lid-driven cavity flow, and the flow past a cylinder. Our results provide a pathway to accurate quantum simulation of nonlinear fluid dynamics, and a framework for extending quantum LBM to more challenging flow configurations.

physics.flu-dyn↗

arXiv2025

An end-to-end quantum algorithm for nonlinear fluid dynamics with bounded quantum advantage

Computational fluid dynamics (CFD) is a cornerstone of classical scientific computing, and there is growing interest in whether quantum computers can accelerate such simulations. To date, the existing proposals for fault-tolerant quantum algorithms for CFD have almost exclusively been based on the Carleman embedding method, used to encode nonlinearities on a quantum computer. In this work, we begin by showing that these proposals suffer from a range of severe bottlenecks that negate conjectured quantum advantages: lack of convergence of the Carleman method, prohibitive time-stepping requirements, unfavorable condition number scaling, and inefficient data extraction. With these roadblocks clearly identified, we develop a novel algorithm for the incompressible lattice Boltzmann equation that circumvents these obstacles, and then provide a detailed analysis of our algorithm, including all potential sources of algorithmic complexity, as well as gate count estimates. We find that for an end-to-end problem, a modest quantum advantage may be preserved for selected observables in the high-error-tolerance regime. We lower bound the Reynolds number scaling of our quantum algorithm in dimension $D$ at Kolmogorov microscale resolution with $O(\mathrm{Re}^{\frac{3}{4}(1+\frac{D}{2})} \times q_M)$, where $q_M$ is a multiplicative overhead for data extraction with $q_M = O(\mathrm{Re}^{\frac{3}{8}})$ for the drag force. This upper bounds the scaling improvement over classical algorithms by $O(\mathrm{Re}^{\frac{3D}{8}})$. However, our numerical investigations suggest a lower speedup, with a scaling estimate of $O(\mathrm{Re}^{1.936} \times q_M)$ for $D=2$. Our results give robust evidence that small, but nontrivial, quantum advantages can be achieved in the context of CFD, and motivate the need for additional rigorous end-to-end quantum algorithm development.

quant-ph↗

arXiv2025

Quantum Dynamics Predicts Coherent Oscillatory Behavior in the Early-times of a Photoisomerization Reaction

In this work, we study the quantum dynamics of a photoisomerization reaction employing a two-electronic-state three-vibrational-mode model of the 2-cis-penta-2,4-dieniminium cation (cis-PSB3). In particular, we address two main issues: the challenges encountered in properly converging quantum dynamics calculations, even when a reduced-dimensionality molecular model is used; the emergence of a coherent oscillatory behavior in the formation of the trans isomer upon photoexcitation of cis-PSB3. The two issues are strictly related, since only upon reliable convergence, the simulated dynamics is able to capture the large amplitude motion associated to the torsion around the reactive bond, typical of photoisomerizations, which is due to the large amount of kinetic energy acquired by the vibrational modes after light excitation.

physics.chem-ph↗

arXiv2025

Quantum Computing in Corrosion Modeling: Bridging Research and Industry

Corrosion presents a major challenge to the longevity and reliability of products across various industries, particularly in the aerospace sector. Corrosion arises from chemical processes occurring on an atomistic scale, which lead to macroscopic degradation. Addressing this issue requires multi-scale modeling approaches, which rely on microscopic parameters that are challenging to measure experimentally or model with conventional quantum chemistry techniques. In this work, we develop and demonstrate a hybrid quantum-classical workflow tailored for atomistic simulations of corrosion processes, with a specific focus on the initial step of the oxygen reduction reaction -- a critical trigger for the corrosion of aluminum alloys widely used in modern aircraft. Using a combination of classical quantum chemistry methods and quantum computing frameworks, we identify reaction geometries characterized by multi-configurational electronic structures that are ideal for exploring with quantum algorithms. For the first time in this context, we explore both noisy intermediate-scale quantum and fault-tolerant quantum algorithms for these multi-configurational system, integrating them within a workflow designed to bridge atomistic simulations with macroscopic modeling approaches, such as finite element methods. Furthermore, we conduct a detailed quantum resource estimation to assess when and how quantum computers may play a meaningful role in tackling these problems. Our results demonstrate that significant advancements in quantum hardware but also in algorithms and error correction techniques are needed to make quantum computation practically viable for this class of problems. Nevertheless, this work establishes a critical foundation for applying quantum computation to corrosion modeling and highlights its potential to address complex, business-relevant challenges in materials science.

quant-ph↗

arXiv2024

Platinum-based Catalysts for Oxygen Reduction Reaction simulated with a Quantum Computer

Hydrogen has emerged as a promising energy source, holding the key to achieve low-carbon and sustainable mobility. However, its applications are still limited by modest conversion efficiency in the electrocatalytic oxygen reduction reaction (ORR) within fuel cells. Consequently, the development of novel catalysts and a profound understanding of the underlying reactions have become of paramount importance. The complex nature of the ORR potential energy landscape and the presence of strong electronic correlations present challenges to atomistic modelling using classical computers. This scenario opens new avenues for the implementation of novel quantum computing workflows to address these molecular systems. Here, we present a pioneering study that combines classical and quantum computational approaches to investigate the ORR on pure platinum and platinum/cobalt surfaces. Our research demonstrates, for the first time, the feasibility of implementing this workflow on the H1-series trapped-ion quantum computer and identify the challenges of the quantum chemistry modelling of this reaction. The results highlight the involvement of strongly correlated species in the cobalt-containing catalyst, suggesting their potential as ideal candidates for showcasing quantum advantage in future applications.

quant-ph↗

arXiv2023

A Theoretical Perspective on the Photochemistry of Boron-Nitrogen Lewis Adducts

Boron-Nitrogen (B-N) Lewis adducts form a versatile family of compounds with numerous applications in functional molecules. Despite the growing interest in this family of compounds for optoelectronic applications, little is currently known about their photophysics and photochemistry. Even the electronic absorption spectrum of ammonia borane, the textbook example of a B-N Lewis adduct, is unavailable. Given the versatility of the light-induced processes exhibited by these molecules, we propose in this work a detailed theoretical study of the photochemistry and photophysics of simple B-N Lewis adducts. We used advanced techniques in computational photochemistry to identify and characterize the possible photochemical pathways followed by ammonia borane, and extended this knowledge to the substituted B-N Lewis adducts pyridine-borane and pyridine-boric acid. The photochemistry observed for this series of molecules allows us to extract qualitative rules to rationalize the light-induced behavior of more complex B-N containing molecules.

physics.chem-ph↗