Volume 97, Issue 11 - Special Issue: Quantum Science and Technology; Guest Editors: Russell Boyd and Manuel Yañez Montero

This recommendation defines the preferred methodology for determining reactivity ratios from copolymer composition data using the terminal model for radical copolymerization. The method is based on measuring conversion ( X ) and copolymer composition ( F ) of three or more copolymerization reactions conducted with different initial monomer compositions ( f 0 ). Both low and high conversion experiments can be combined, or alternatively only low conversion experiments can be used. The method provides parameter estimates, but can also reveal deviations from the terminal model and the presence of systematic errors in the measurements. Special attention is given to error estimation in F and construction of the joint confidence interval for the reactivity ratios. Previous experiments measuring f 0 − F (i.e., copolymer composition as a function of varying f 0 ) or f − X (i.e., how f varies with X in an experiment) can also be analyzed with this IUPAC recommended method. The influence of systematic errors in the measurements on the reactivity ratio determinations is addressed. The document has a broad significance in that it seeks to eradicate the use of incorrect methods and common mistakes in determining reactivity ratios in radical copolymerizations.

This report provides a summary of recommended or suggested values of the rate coefficients for thermal decomposition ( k d ) and of the efficiencies for radical generation ( f g ) and initiation of polymerization ( f i ) for some commercially available dialkyldiazene (also known as azo-compound) initiators. These initiators are one of the most important classes of initiators used in both conventional radical polymerization and reversible-deactivation radical polymerization (RDRP). Although values of k d can be cited with confidence for many initiators, it must also be stated that for most initiators there is insufficient quality data in the open literature to allow a rigorous statistical analysis. The situation is complicated by some initiators existing as a mixture of diastereomers and decomposition rates being subject to small, yet experimentally significant, solvent dependence. Efficiencies for radical generation ( f g ) are available for some initiators. Efficiencies for initiation of polymerization ( f i ) are less common and have been demonstrated to be strongly dependent on the initiator, the complexity of the mechanisms for radical generation and for initiation of polymerization, the reaction medium, the monomers being polymerized and their concentration as determined by the amount of solvent, and the conversion of monomer to polymer. Consequently, only general recommendations for initiator efficiency are possible at this stage.

In this Technical Report, we introduce the application of FAIR (findable, accessible, interoperable, and reusable) data management in the form of a “FAIRSpec-ready spectroscopic data collection” – that is, a collection of instrument data, chemical structure representations, and related digital items that is ready to be automatically or semi-automatically extracted for metadata that will allow the production of an IUPAC FAIRSpec Finding Aid. Associating this finding aid with the collection produces an IUPAC FAIRSpec Data Collection. The challenge we set for researchers is relatively simple: to maintain their data in a form that allows critical metadata to be extracted in a discipline-specific way, increasing the probability that the data will be findable and reusable both during the research process and after publication. We focus on a few specific suggestions that researchers can use to maximize the “fairness” of their spectroscopic data collection. Most importantly, following these guidelines ensures that instrument datasets are unambiguously associated with the chemical structure. The guidelines promote the inclusion of the instrument dataset itself in the collection and describe ways of organizing the collection such that automated metadata creation is possible. In these guidelines, we emphasize the importance of systematically organizing data throughout the entire research process, not just at the time of publication.

Although the accuracy of first-principles calculations makes them ideal for modeling noncovalent interactions, their high computational cost limits their applicability to moderate system sizes. Analytic potentials have emerged as an excellent means of modeling large-scale systems because of their simplicity and computational efficiency. However, the effectiveness of the analytic potentials depends heavily on the choice and the transferability of their parameters. Herein, employing noble gases as a testbed, we embarked on assessing the transferability of parameters of two widely used pair potentials, Lennard-Jones (LJ) and improved Lennard-Jones (ILJ) potentials. We established the inadequacy of the various traditional combination rules for the LJ potential in describing noble gas heterodimer interactions. The potentials that are parametrized against benchmark CCSD(T) calculations for noble gas homodimers and heterodimers failed to accurately describe the interactions in dimers of noble gas dimers. However, a parametrization of the LJ and the ILJ potentials against reference electronic structure calculations describing noble gas dimer-dimer interactions was found to be effective. The ILJ potential consistently exhibited improved accuracy over the LJ potential. Our study showcases the non-transferability of the LJ and the ILJ parametrizations developed for the elementary pairwise interactions to the description of complex chemical systems.

The story of the development of quantum mechanics is briefly told, from the perspective of human dynamics, and in the spirit of the sobering truth behind it. Three long term contributions from the author’s lab are succinctly presented: (i) FFLUX, a machine-learnt potential for the molecular dynamics of peptides in water, thereby overhauling the architecture of classical force fields; (ii) REG, an unbiased and minimal method to compute chemical insight, thereby reducing the vexing gap between it and modern wavefunctions; (iii) AIBL, a gas-phase-based predictor of pK a values in solution, including for tautomerisable and multiprotic compounds of more than 50 atoms, and able to even correct experiment.

This perspective offers a personal reflection on the evolution, current status, and open challenges of quantum chemistry in the context of large molecular systems. Beginning with Dirac’s famous 1929 prophecy, I revisit the historical trajectory of our discipline, from the development of early conceptual models to the emergence of density functional theory and correlated wavefunction methods. While enormous progress has been made in algorithmic sophistication, enabling accurate calculations on systems with thousands of atoms, I argue that accurate energies alone do not solve the entirety of chemical problems. Real-world applications demand more than electronic structure: solvation, entropy, conformational complexity, and the sheer complexity of large molecules challenge our methods and our assumptions. Equally important are the conceptual and philosophical tensions that continue to shape the field, especially the difficult balance between prediction and understanding. I advocate for a more integrative approach that values models, insight, and falsifiability alongside numerical precision. Finally, I briefly consider the emerging role of machine learning and the implications of automation for the future of theory. This article is not a review but a dialogue – with the field, with its history, and with its practitioners.

The International Year of Quantum Science and Technology (IYQ) celebrates the centenary of quantum mechanics (QM). In this perspective, I highlight that QM is not only a playground for physical chemists but of tremendous value to organic chemists as exemplified in its ever-increasing role in the career of Nobel prizewinner R.B. Woodward. Over three decades, this ranged from the prediction of UV-visible absorption wavelengths arising from electronic excitations to the importance of molecular orbital symmetry and the derivation of the Woodward-Hoffmann rules for pericyclic reactions.

This perspective revisits key developments and challenges in the theoretical description of atomic and molecular electronic properties within the framework of relativistic quantum chemistry. Fundamental conceptual issues arising from the extension of non-relativistic theories to the relativistic domain are discussed, with particular emphasis on four-component formalisms, the treatment and interpretation of negative-energy states, including virtual excitations involving these states, the reinterpretation of operators and observables, and the introduction of weak interactions into this field of research. Special attention is given to the construction of model Hamiltonians as accurately as possible and the analysis of the electronic contributions due to spin-dependent and spin-independent effective Hamiltonians to molecular properties. In this context, the generalization of the spin-symmetry to time-reversal-restricted symmetry is emphasized. Recent methodological advances, including the application of the relativistic polarization propagator theory, are also highlighted.

This essay presents an examination of the rise and evolution of quantum mechanics, approached from a chemical viewpoint. The emergence of quantum mechanics have led to significant progress and discoveries in chemistry, offering well grounded and rigorous concepts to rationalize the observed behavior of matter. Quantum chemistry’s progress is credited to the application of quantum mechanics in molecular systems, with the objective of characterizing their electronic structures and elucidating their properties and reactivity. The link between the reactivity principles that govern the behavior of matter in classical chemistry and specific global electronic properties identified in quantum chemistry is well recognized. Notably, the electronic chemical potential is highlighted as a crucial property for uncovering the nature of matter and its chemical transformation processes. It plays an essential role in influencing molecular reactivity and is crucial for evaluating reaction mechanisms through its first derivative, known as the reaction electronic flux. In addition, the local baseline electronic activity within molecular systems is briefly examined, this is a nonreactive electronic activity that arises from the vibrational dynamics intrinsic to molecular systems, it is also characterized via the electronic chemical potential, thus confirming the relevance of the later property in chemistry.

Prior to 1970, no successful ab initio electronic structure predictions were made that challenged experiment for polyatomic molecules. For diatomics, the work of Ernest Davidson stands out, in 1960 explaining that two spectroscopically known but misunderstood electronic states of H 2 were in fact part of the very same potential energy curve. Another diatomic example was the startling 1968 overturn by Kolos and Wolniewicz of the “known” experimental dissociation energy of H 2 . Moving to polyatomics, the research in 1970 concerning the structure of triplet methylene captured the imagination of many chemists, and the 1982 success of theory for the singlet-triplet separation of methylene confirmed for many the great usefulness of ab initio theory. In the second half of this paper, the utility of methods based on single Slater determinant reference wavefunctions for both singlet and triplet methylene is demonstrated. In particular, we examine how the optimized geometries and harmonic vibrational frequencies of triplet and singlet CH 2 evolve with systematic improvements in basis set size and valence electron correlation treatment. To accurately pinpoint the geometric structures and singlet-triplet splitting of methylene, we perform comprehensive focal point analyses (FPA) that push the level of theory to new heights, leveraging core-valence basis sets up to sextuple-zeta quality and all-electron coupled-cluster methods through CCSDTQ(P) appended with relativistic (MVD1) and non-Born-Oppenheimer (DBOC) corrections. Our final FPA prediction for the singlet-triplet splitting is 9.01 kcal mol −1 , in complete agreement with the best empirical estimate of 9.00 ± 0.01 kcal mol −1 . The corresponding optimized FPA geometries are [ r e (H–C), θ e (H–C–H)] = (1.1063 Å, 102.35°) for ã 1 A 1 CH 2 and (1.0756 Å, 133.94°) for X̃ 3 B 1 CH 2 , in close agreement with the best existing experimental and theoretical structures but with a little finer precision. Our outcomes not only affirm the validity of the contemporary single-reference coupled-cluster theory pushed to high order but also provide definitive resolutions for a paradigmatic molecule that has long been emblematic of the challenges and triumphs that have shaped a century of quantum chemistry.

We first give a brief, incomplete overview over historic milestones leading to the emergence of quantum chemistry, starting from John Dalton’s earliest attempts to describe the atom in the early 19th century. After the formulation of the Schrödinger equation in 1926 and the first successful description of covalent bonding using the new theory, it became soon clear that the main challenge ahead was to find efficient approximations to the Schrödinger equation, as was famously stated by Paul A. M. Dirac in 1929. Since then, many quantum-chemical approximations have been introduced, with a key problem being the exponential increase of the computational cost with the system size when approaching the exact solution of the Schrödinger equation. In the second part, we will hence focus on selected techniques to overcome the scaling problem. Finally, we close with some insights into the new and challenging field of reaction network exploration, offering a glimpse into potential future directions of quantum chemistry.

In this Perspective, we discuss how quantum computers may advance the simulation of nonadiabatic molecular dynamics, a framework central to describing excited-state processes in photochemistry, biology, and materials science. Classical approaches span from exponentially scaling full quantum dynamics to more approximate mixed quantum–classical techniques such as surface hopping and Ehrenfest dynamics. Hybrid quantum–classical algorithms – particularly those based on the variational quantum eigensolver – offer a transformative alternative by providing access to the key electronic properties needed to drive nonadiabatic molecular dynamics simulations, including energies, gradients, and nonadiabatic couplings. We examine recent proof-of-principle quantum simulations of reduced model systems which, despite being restricted to small molecules and limited active spaces due to constraints of qubit number and device noise, already showcase the potential of quantum devices to capture phenomena such as conical intersections and ultrafast relaxation. Although practical applications are not yet feasible in the present noisy intermediate-scale quantum era, these efforts underline the conceptual and methodological advances of quantum algorithms paving the way for large-scale quantum simulations of nonadiabatic processes. Framed within the 2025 International Year of Quantum Science and Technology, such progress exemplifies how quantum computing may open new horizons for chemistry and beyond.

Based on semi-empirical quantum mechanics calculations and extensive molecular mechanics calculations and molecular dynamics simulations, a novel molecular level conceptualization of key biochemical events in the pathogenesis of Alzheimer’s disease (AD) is presented. In response to immune stimulating events ( e.g ., infection, trauma), β-amyloid (Aβ) protein is released in brain as a protective immunopeptide triggering an immunity cascade in which Aβ exhibits antimicrobial activity, which mistakenly results in a misdirected attack upon “self” neurons, arising from the macromolecular and electrochemical similarities between neurons and bacteria in terms of transmembrane potential gradients and anionic charge distribution geometries on outer membrane macromolecules (gangliosides in neurons; cardiolipins or lipopolysaccharides in bacteria). Molecular mechanics/dynamics calculations are used to demonstrate how the inability of Aβ to distinguish between bacteria and neurons is a central pathological process in the pathogenesis of AD.

The surface electrostatic potential ( V S ( r )) is an established tool for characterization and prediction of sites susceptible to participate in intermolecular interactions. In particular, maxima in V S ( r ) ( V S,max ) have been shown to reflect σ-holes and π-holes, including the electrophilic sites of hydrogen bond donors and halogen bond donors as well as traditional Lewis acids. The characterization of nucleophilic sites on Lewis bases has proven more difficult, and surface minima ( V S,min ) often fail to predict the angular direction of interactions with electrophiles. In this study, it is demonstrated that the predictive capacity of spatial minima in the electrostatic potential ( V min ) is much higher than V S,min for interactions with neutral electrophiles, such as HF, BF 3 , BrF and LiF. V S,min , on the other hand, is better for interactions with ionic electrophiles, such as Li + . This latter observation can be explained by that the position of the V S,min corresponds to the site on the surface that has strongest electrostatic interaction with a point charge. V min performs better for interactions with neutral electrophiles, as the nucleophile interacts electrostatically with the entire charge distribution of the electrophile and not only with that of its electrophilic site; the charge distribution of a neutral electrophile can be approximated by a dipole or a superposition of dipoles, and a dipole interacting with a Lewis base (nucleophile) has its lowest electrostatic energy when it is pointed along the direction of strongest electrostatic field, which generally coincides with the direction of the  V min .

Developing efficient organic photoredox catalysts is essential for advancing sustainable CO 2 conversion technologies. This paper investigates the photophysical properties of oligo- p -phenylenes (OPP- n ), with a focus on p -terphenyl (OPP-3), and its functionalized derivatives to identify structural features that may enhance their photocatalytic potential. We examine how symmetric and asymmetric terminal substitutions affect excitation energies, oscillator strengths, exciton characteristics, and fluorescence. Our results show that push–pull derivatives have significantly lower excitation energies and larger oscillator strengths, promoting efficient radical anion generation. These derivatives also exhibit longer fluorescence lifetimes, which may improve the probability of productive interactions with sacrificial electron donors. Exciton analysis reveals that asymmetric substitutions introduce charge-transfer character, whereas higher oligomers maintain tightly bound excitons with limited delocalization. Overall, functionalized OPP- n chromophores, especially push–pull derivatives of OPP-3, demonstrate favorable optical and excitonic properties for photoredox catalysis, making them promising candidates for CO 2 reduction and hydrogen evolution applications.

Accurate wavefunction methods like CCSD(T) can predict chemical and thermodynamic properties of small molecules with near-experimental precision. However, their steep computational cost limits their use for large systems or extensive datasets. In contrast, DFT is faster and more practical for large molecules but often fails to accurately capture electronic changes, especially upon geometry relaxation. To address this, we have developed a graph neural network (GNN)-based Delta-Machine Learning (ΔML) model using Connectivity-Based Hierarchy (CBH-2) molecular fragments as descriptors to predict adiabatic ionization potentials (IPs). Our approach shows systematic error cancellation, guided by electron population difference maps to identify ionization sites within the molecule to construct CBH-2 fragments. We have considered both structural and electronic features to improve our ΔML model. We have observed that upon incorporation of electronic features, the graph-based ΔML model achieved a coupled cluster level of accuracy with an MAE of 0.02 eV for IP prediction. Furthermore, we compared adiabatic and vertical IP predictions across different methods. While raw DFT errors are strongly dependent on the functional used, our ΔML model is robust and much less functional-sensitive.

The dianion [B 10 H 14 ] 2− has attracted renewed attention due to its structural characteristics and a mercury-free synthesis route. Although its arachno structure has been reported, we explored the potential energy surface of B 10 H 14 2− to identify more stable species. Subsequent analyses included bonding evaluation, kinetic studies, and Born-Oppenheimer molecular dynamics (BO-MD) simulations. Calculations indicate that the closo -[B 10 H 10 ] 2− ⋯2H 2 complex is 21.5 kcal mol −1 more stable than the arachno structure. The complex is stable below 110 K but dissociates into closo -[B 10 H 10 ] 2− and H 2 at higher temperatures. The arachno isomer remains kinetically stable because a 30 kcal/mol activation barrier prevents its conversion. BO-MD simulations corroborate this kinetic stability, as the arachno framework is maintained during the trajectories. The effects of the solvent and the counterions were also examined and found to have a negligible influence on the relative energetics.

A simple physical model of atomic structure and reactivity is extracted from quantum mechanics using widely known facts and relations but no expert knowledge of quantum chemistry. The Aufbau model is included and extended to account for the role of electron dynamics and energy degeneracy of the atomic ground states. The periodically variable reactivity is found to arise due to dynamical constraints on electron motion which lead to degeneracy (coincidence or near-coincidence) in the atomic energy spectrum. Verification is found in a strong correlation between energy degeneracy and reactivity with the inert gas atoms found to display least degeneracy. Chemical bonding follows as a means of relaxing atomic reactivity and reducing energy degeneracy. This can be achieved by permanent electron rearrangement among atomic centers (ionic bonding) or by oscillatory electron motion between atoms (covalent bonding). Ionic bonding is directly related to the variable stability of atomic structures, not only of neutral atoms but also of atomic ions formed by permanent electron redistribution. The most stable ions then form nondegenerate molecular structures by electrostatic interaction in neutral ionic clusters. The covalent bonding mechanism is instead fundamentally dynamical and interatomic since it depends directly on the facility (rate and spatial extent) with which electrons can move between atomic centers in a molecule. Energy degeneracy is found to imply dynamical constraint on electron motion which is reduced by covalent bonding, normally, but not always, to form a nondegenerate molecular ground state. Facilitation of interatomic electron motion, and the corresponding decrease in degeneracy of the ground and lowest energy excited states, thus become the covalent bonding mechanism. Equilibrium molecular geometries optimally balance this attraction against interatomic repulsions of electrostatic and steric (Pauli) nature which dominate at short range. The fundamental role of electron dynamics in atomic properties and bonding is reflected in a corresponding importance of not only ground state energy but the spectrum of low energy states.

We recently proposed a new approach that permits to apply the methods of Quantum Chemistry to infinite periodic systems. This is based on the transformation of the topology of a finite fragment of the periodic system into a Clifford Torus, and a redefinition of the distances in this new manifold. The standard Gaussian orbitals, that are so common in Quantum-Chemistry calculations, are also redefined, in order to obtain smooth orbitals whose behavior is compatible with the periodicity of the torus. We call these new functions “Clifford Gaussians”. Finally, after a set of calculations on systems having increasing size, an extrapolation to a system having infinite size is performed, in order to obtain the crystal properties at the thermodynamic limit. In the present paper, we apply this formalism to the study of two model systems: the free particle in a ring (a 1D system), and a pair of electrons in a square (2D) or a cube (3D). In the first case, for which the spectrum of the Hamiltonian is analytically known, we show that a set of s -type Clifford Gaussians is able to reproduce the exact eigenvalues of the system with an extremely high accuracy, suggesting that the Clifford Gaussians, under some circumstances, could form a complete basis set for the torus. In the case of the second system, that had already be studied by our group by using a large number of ordinary Gaussians, we show that two Clifford Gaussians only are able to reproduce the behavior of the system with a good accuracy. In particular, they are able to describe the Wigner localization of the electrons that occurs at very low density. We believe that this formalism could open a new approach for the study of infinite periodic systems within the powerful and well established framework of Quantum Chemistry.

Sodium-ion batteries are increasingly regarded as a sustainable alternative to lithium-ion technology for large-scale energy storage, but their development remains limited by the lack of durable high-energy cathodes. Among the most promising candidates, P2–Mn-based layered oxides combine high theoretical capacity with structural versatility, yet their performance is constrained by two degradation pathways: (i) the irreversible participation of lattice oxygen in the redox process and (ii) voltage-driven solid-state phase transitions. This research article synthesizes our recent ab initio investigations aimed at disentangling the atomistic origins of these processes occurring in the high-voltage regime. We show that Mn deficiency activates oxygen redox but also promotes O 2 release, whereas Fe and Ru doping strengthen TM–O covalency, enabling reversible anionic redox. In parallel, we identify cooperative Jahn–Teller distortions and Na + /vacancy reorganization as the driving forces of high-voltage phase transitions and propose simple geometric descriptors as predictive tools for structural stability. Together, these insights help to establish quantum-based design guidelines for layered sodium cathodes: reinforce TM–O covalency, suppress oxygen evolution, and mitigate phase instabilities. By combining first-principles modeling with targeted compositional design, we pave the way toward the accelerated discovery of sustainable, cobalt-free, and high-energy cathodes for next-generation sodium-ion batteries.