arXiv subjects

Martina Stella

Publications and source records attributed to Martina Stella.

9 recordsLinked to original sources

arXiv2026

AEGISS -- Atomic orbital and Entropy-based Guided Inference for Space Selection -- A novel semi-automated active space selection workflow for quantum chemistry and quantum computing applications

The selection of a balanced active space is a critical step in multi-reference quantum chemistry calculations, particularly for systems with strong electron correlation. Likewise, active space selection is a key to unlock the potential of contemporary quantum computing in quantum chemistry. Albeit recent progress, there remains a lack of a unified, robust, and fully automated framework for active space selection that performs reliably across a wide range of molecular systems. In this work, we present a novel approach inspired by both the AVAS (Atomic Valence Active Space) and AutoCAS methods. Our method unifies orbital entropy analysis with atomic orbital projections to guide the construction of chemically and physically meaningful active spaces. This integrated scheme enables a more consistent and flexible selection of active orbitals while retaining automation and scalability. We validate our approach on a set of molecular systems relevant to photodynamic therapy, in particular a set of Ru(II)-complexes, selected to span increasing levels of electron correlation and structural complexity. These molecules serve as challenging test cases due to the presence of strong static correlation and the need for highly accurate electronic structure descriptions. Our results demonstrate that the method can reliably identify compact, chemically intuitive active spaces that capture the essential physics, making it suitable for both classical and quantum computational frameworks. Furthermore, we have developed this approach in a package that is intuitive to use for users and can be interfaced with both standard quantum chemistry and quantum computing applications, making it accessible to a broad research community.

physics.chem-ph↗

arXiv2026

Scalable quantum circuit generation for iterative ground state approximation using Majorana Propagation

We introduce the Adaptive Derivative-Assembled Pseudo-Trotter ansatz Variational Majorana Propagation Eigensolver (ADAPT-VMPE), a quantum-inspired classical algorithm that exploits Majorana Propagation (MP) to produce circuits for approximating the ground state of molecular Hamiltonians. Equipped with the theoretical guarantees of MP, which provide controllable bounds on the approximation error, ADAPT-VMPE offers an efficient and scalable approach for iterative ansatz construction. A theoretical analysis of the computational complexity demonstrates that it is polynomial in both the number of qubits and the number of iterations. We present an in-depth analysis of circuit construction strategies, analyzing their impact on convergence and provide practical guidance for efficient ansatz generation. Using ADAPT-VMPE, we construct up to 100-qubit ansätze for a strongly correlated photosensitizer currently undergoing human clinical trials for cancer treatment. Our results demonstrate that constant overlap with the ground state across system sizes can be reached in polynomial time with polynomially sized circuits.

quant-ph↗

arXiv2026

Data-Efficient Active Learning Discovery of Transition Metal Photosensitizers for Type I Photodynamic Therapy

Transition-metal complexes (TMCs) are promising photosensitizers for Type~I photodynamic therapy (PDT), where electron-transfer processes can generate reactive oxygen species under hypoxic conditions. Yet identifying candidates with the required ground- and excited-state redox energetics remains challenging across the vast chemical space of TMCs. Here, we develop a data-efficient active learning (AL) framework for the discovery of Type~I active TMC photosensitizers by combining a chemically structured design space of over 2.1 million Ru(II), Os(II), and Ir(III) complexes with targeted DFT calculations and pretrained atomistic representations. With only 300 quantum-chemical evaluations, the approach efficiently enriches candidates within a mechanistically defined optimal redox region. Analysis of the viable complexes reveals chemical design principles linking metal identity, ligand framework, substituent pattern, and physicochemical properties to Type~I photoreactivity, including a pronounced preference for Os(II)-based complexes and electronically asymmetric ligand environments along with combination of electronic donating and accepting substituents. More broadly, the strategy presented herein provides a scalable, mechanism-guided route for the rational design of transition-metal photocatalysts for applications spanning biomedicine, solar energy conversion, and photoredox chemistry.

physics.chem-ph↗

arXiv2025

Investigating the Role of pH and Counterions in the Intrinsic Fluorescence of Solid-State L-Lysine

There is currently a growing interest in understanding the origins of intrinsic fluorescence as a way to design non-invasive probes for biophysical processes. In this regard, understanding how pH influences fluorescence in non-aromatic biomolecular assemblies is key to controlling their optical properties in realistic cellular conditions. Here, we combine experiments and theory to investigate the pH-dependent emission of solid-state L-Lysine (Lys). Lys aggregates prepared at different pH values using HCl and H$_2$SO$_4$ exhibit protonation- and counterion-dependent morphology and fluorescence, as shown by microscopy and steady-state measurements. We find an enhancement in the fluorescence moving from acidic to basic conditions. To uncover the molecular origin of these trends, we performed non-adiabatic molecular dynamics simulations on three Lys crystal models representing distinct protonation states. Our simulations indicate that enhanced protonation under acidic conditions facilitates non-radiative decay via proton transfer, whereas basic conditions favor radiative decay. Our combined experimental-theoretical work highlights pH and counterion identity as key factors tuning fluorescence in Lys assemblies, offering insights for designing pH responsive optical materials based on non-aromatic amino acids.

physics.chem-ph↗

arXiv2024

Aqueous Solution Chemistry In Silico and the Role of Data Driven Approaches

The use of computer simulations to study the properties of aqueous systems is, today more than ever, an active area of research. In this context, during the last decade there has been a tremendous growth in the use of data-driven approaches to develop more accurate potentials for water as well as to characterize its complexity in chemical and biological contexts. We highlight the progress, giving a historical context, on the path to the development of many-body and reactive potentials to model aqueous chemistry, including the role of machine learning strategies. We focus specifically on conceptual and methodological challenges along the way in performing simulations that seek to tackle problems in modeling the chemistry of aqueous solutions. In conclusion, we summarize our perspectives on the use and integration of advanced data-science techniques to provide chemical insights in physical chemistry and how this will influence computer simulations of aqueous systems in the future.

physics.chem-ph↗

arXiv2023

Exploratory Data Science on Supercomputers for Quantum Mechanical Calculations

Literate programming - the bringing together of program code and natural language narratives - has become a ubiquitous approach in the realm of data science. This methodology is appealing as well for the domain of Density Functional Theory (DFT) calculations, particularly for interactively developing new methodologies and workflows. However, effective use of literate programming is hampered by old programming paradigms and the difficulties associated with using High Performance Computing (HPC) resources. Here we present two Python libraries that aim to remove these hurdles. First, we describe the PyBigDFT library, which can be used to setup materials or molecular systems and provides high-level access to the wavelet based BigDFT code. We then present the related remotemanager library, which is able to serialize and execute arbitrary Python functions on remote supercomputers. We show how together these libraries enable transparent access to HPC based DFT calculations and can serve as building blocks for rapid prototyping and data exploration.

physics.chem-ph↗

arXiv2022

Probing Disorder in 2CzPN using Core and Valence States

Molecules which exhibit thermally activated delayed fluorescence (TADF) show great promise for use in efficient, environmentally-friendly OLEDs, and thus the design of new TADF emitters is an active area of research. However, when used in devices, they are typically in the form of disordered thin films, where both the external molecular environment and thermally-induced internal variations in parameters such as the torsion angle can strongly influence their electronic structure. In this work, we use density functional theory and X-ray photoelectron spectroscopy to investigate the impact of disorder on both core and valence states in the TADF emitter 2CzPN. By simulating gas phase molecules displaying varying levels of disorder, we assess the relative sensitivity of the different states to factors such as varying torsion angle. The theoretical results for both core and valence states show good agreement with experiment, thereby also highlighting the advantages of our approach for interpreting experimental spectra of large aromatic molecules, which are too complex to interpret based solely on experimental data.

physics.chem-ph↗

arXiv2022

Transition-Based Constrained DFT for the Robust and Reliable Treatment of Excitations in Supramolecular Systems

Despite the variety of available computational approaches, state-of-the-art methods for calculating excitation energies such as time-dependent density functional theory (TDDFT), are computationally demanding and thus limited to moderate system sizes. Here, we introduce a new variation of constrained DFT (CDFT), wherein the constraint corresponds to a particular transition (T), or combination of transitions, between occupied and virtual orbitals, rather than a region of the simulation space as in traditional CDFT. We compare T-CDFT with TDDFT and $Δ$SCF results for the low lying excited states (S$_{1}$ and T$_{1}$) of a set of gas phase acene molecules and OLED emitters, as well as with reference results from the literature. At the PBE level of theory, T-CDFT outperforms $Δ$SCF for both classes of molecules, while also proving to be more robust. For the local excitations seen in the acenes, T-CDFT and TDDFT perform equally well. For the charge-transfer (CT)-like excitations seen in the OLED molecules, T-CDFT also performs well, in contrast to the severe energy underestimation seen with TDDFT. In other words, T-CDFT is equally applicable to both local excitations and CT states, providing more reliable excitation energies at a much lower computational cost than TDDFT. T-CDFT is designed for large systems and has been implemented in the linear scaling BigDFT code. It is therefore ideally suited for exploring the effects of explicit environments on excitation energies, paving the way for future simulations of excited states in complex realistic morphologies, such as those which occur in OLED materials.

physics.chem-ph↗

arXiv2020

Fast Molecular Compression by a Hyperthermal Collision Gives Bond-Selective Mechanochemistry

Using electrospray ion beam deposition, we collide the complex molecule Reichardt's Dye (C41H30NO+) at low, hyperthermal translational energy (2-50 eV) with a Cu(100) surface and image the outcome at single-molecule level by scanning tunneling microscopy. We observe bond-selective reaction induced by the translational kinetic energy. The collision impulse compresses the molecule and bends specific bonds, prompting them to react selectively. This dynamics drives the system to seek thermally inaccessible reactive pathways, since the compression timescale (sub-ps) is much shorter than the thermalization timescale (ns), thereby yielding reaction products that are unobtainable thermally.

physics.chem-ph↗