Rational design of covalent protein-labeling reagents in complex biological environments requires a molecular-level understanding of how the protein microenvironment governs chemical reactivity; yet, ...

Inverted singlet–triplet (INVEST) materials, characterized by a negative singlet–triplet energy gap (ΔEST), hold great promise for next-generation Organic Light Emitting Diode (OLED) applications. How...

Chemical bonding explains how atoms bind together, but it remains hard to define in universal terms. Here, the authors use quantum entanglement to uncover and quantify bonds in complex systems beyond ...

The Global Natural Orbital Functional (GNOF) provides a straightforward approach to capture most electron correlation effects without needing perturbative corrections or limited active spaces selectio...

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Open-shell hydrocarbons are of great interest in molecular materials, yet their electronic structures remain challenging to describe. Here we investigate triangular acenes, formed by fusing three iden...

Variational quantum eigensolvers (VQEs) are among the most promising quantum algorithms for solving electronic structure problems in quantum chemistry, particularly during the noisy intermediate-scale...

We present a spin-permutation diabatization strategy that transforms ab initio spin-pure eigenstates into spin-localized diabatic states, enabling direct mapping to spin-effective Hamiltonians without projection or orbital localization. The method provides both a real-space decomposition of electronic states in terms of localized spins and a straightforward evaluation of exchange couplings. Applications to several representative systems, including ethylene torsion, prototypical diradicals (benzynes, xylylenes, methylene), trimethylenebenzene triradical, singlet–triplet excited states of organic chromophores, and triplet-pair states in a tetracene dimer, demonstrate that the approach provides magnetic couplings and affords a clear physical interpretation of interacting spins. This general and conceptually transparent framework bridges ab initio electronic structure theory and spin models, and is expected to be especially valuable for systems with nontrivial distributions of unpaired electrons, such as delocalized or strongly correlated molecular magnets and spin-active chromophores.

This figure illustrates the workflow for analyzing excited states using localized molecular orbitals (LMOs). Canonical molecular orbitals (CMOs) from self-consistent field calculations are transforme...

We benchmark second-order perturbative corrections to the Restricted Active Space Configuration Interaction in the hole and particle approximation, RAS(h,p), for valence singlet and triplet excitation...

21st International Conference on Density Functional Theory and its Applications

21st International Conference on Density Functional Theory and its Applications

YouTube video by Donostia International Physics Center

The adaptive derivative-assembled problem-tailored variational quantum eigensolver (ADAPT-VQE) is one of the most widely used algorithms for electronic structure calculations in quantum computers. It adaptively selects operators based on their gradient, constructing ansätze that continuously evolve to match the energy landscape, helping avoid local traps and barren plateaus. However, this flexibility in reoptimization can lead to the inclusion of redundant or inefficient operators that have almost zero parameter value, barely contributing to the ansatz. We identify three phenomena responsible for the appearance of these operators: poor operator selection, operator reordering, and fading operators. In this work, we propose an automated, cost-free refinement method that removes unnecessary operators from the ansatz without disrupting convergence. Our approach evaluates each operator after ADAPT-VQE optimization by using a function that considers both its parameter value and position in the ansatz, striking a balance between eliminating low-coefficient operators while preserving the natural reduction of coefficients as the ansatz grows. Additionally, a dynamic threshold based on the parameters of recent operators enables efficient convergence. We apply this method to several molecular systems and find that it reduces ansatz size and accelerates convergence, particularly in cases with flat energy landscapes. The refinement process incurs, at most, a small additional computational cost and consistently improves or maintains ADAPT-VQE performance.

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Programa definitivo Naukas Bilbao 15 Aniversario (19 al 21 septiembre 2025)

Noncovalent interactions (NCIs) are fundamental to the structure, stability, and function of proteins. These interactions form complex networks that control how different protein regions relate to eac...

A new class of diarylethene compounds containing backbone phosphine oxide groups are reported, exhibiting turn-on aggregation-induced emission. Side chain functionalization enabled emission color tun...

Biomolecular condensates often form through the self-assembly of disordered proteins with low-complexity sequences. In these polypeptides, the aromatic amino acids phenylalanine and tyrosine act as ke...

Facile methods of materials fabrication create polycrystalline structures and introduce grain boundary (GB) and other defects that influence performance. Focusing on a typical GB in a popular all-inorganic metal halide perovskite, we combine ab initio and machine learning tools to study the evolution of the GB structural and electronic properties in a halide-rich environment on a nanosecond time scale. We demonstrate that separately, the GB and halide dopant introduce midgap electron and hole trap states. However, the chemical driving force and low barriers allow dopant diffusion to the GB region, resulting in self-passivation of the extended and point defects. Every few tens or hundreds of picoseconds, the halide dopant hops, perturbing geometric and electronic structure and giving rise to trap states within the bandgap. This lasts only transiently, a few picoseconds. Halide doping makes the GB more structurally sound compared to the undoped GB, which exhibits long, 100 ps regions of structural instability and persistent trap states. The transient trap states originate from jammed structures in sub-boundary regions, while unfavorable conformations directly at the GB have sufficient space to relax. Most of the time, the doped GB contains no midgap traps while separating electrons and holes and assisting in exciton dissociation. The demonstrated self-healing of perovskite GBs under halide-rich conditions provides an efficient strategy for improving material properties. The detailed atomistic analysis, obtained with the help of modern machine learning tools, assists in resolving conflicting statements regarding the influence of perovskite GBs on material performance and provides valuable insights into the unusual properties of these important materials.

We introduce a state-interaction approach for computing g-matrices within time-dependent density functional theory (TDDFT) and the Tamm–Dancoff approximation (TDA), applied here for the first time. Th...