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Automated and high-throughput quantum chemical investigations into chemical processes have become feasible in great detail and broad scope. This results in an increase in complexity of the tasks and in the amount of generated data. An efficient and intuitive way for an operator to interact with these data and to steer virtual experiments is required. Here, we introduce Heron, a graphical user interface that allows for advanced human-machine interactions with quantum chemical exploration campaigns into molecular structure and reactivity. Heron offers access to interactive and automated explorations of chemical reactions with standard electronic structure modules, haptic force feedback, microkinetic modeling, and refinement of data by automated correlated calculations including black-box complete active space calculations. It is tailored to the exploration and analysis of vast chemical reaction networks. We show how interoperable modules enable advanced workflows and pave the way for routine low-entrance-barrier access to advanced modeling techniques.

The software for chemical interaction networks (SCINE) project aims at pushing the frontier of quantum chemical calculations on molecular structures to a new level. While calculations on individual structures as well as on simple relations between them have become routine in chemistry, new developments have pushed the frontier in the field to high-throughput calculations. Chemical relations may be created by a search for specific molecular properties in a molecular design attempt, or they can be defined by a set of elementary reaction steps that form a chemical reaction network. The software modules of SCINE have been designed to facilitate such studies. The features of the modules are (i) general applicability of the applied methodologies ranging from electronic structure (no restriction to specific elements of the periodic table) to microkinetic modeling (with little restrictions on molecularity), full modularity so that SCINE modules can also be applied as stand-alone programs or be exchanged for external software packages that fulfill a similar purpose (to increase options for computational campaigns and to provide alternatives in case of tasks that are hard or impossible to accomplish with certain programs), (ii) high stability and autonomous operations so that control and steering by an operator are as easy as possible, and (iii) easy embedding into complex heterogeneous environments for molecular structures taken individually or in the context of a reaction network. A graphical user interface unites all modules and ensures interoperability. All components of the software have been made available as open source and free of charge., (© 2024 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International (CC BY-NC-ND) license (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Data-driven synthesis planning has seen remarkable successes in recent years by virtue of modern approaches of artificial intelligence that efficiently exploit vast databases with experimental data on chemical reactions. However, this success story is intimately connected to the availability of existing experimental data. It may well occur in retrosynthetic and synthesis design tasks that predictions in individual steps of a reaction cascade are affected by large uncertainties. In such cases, it will, in general, not be easily possible to provide missing data from autonomously conducted experiments on demand. However, first-principles calculations can, in principle, provide missing data to enhance the confidence of an individual prediction or for model retraining. Here, we demonstrate the feasibility of such an ansatz and examine resource requirements for conducting autonomous first-principles calculations on demand., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Quantum chemical calculations on atomistic systems have evolved into a standard approach to studying molecular matter. These calculations often involve a significant amount of manual input and expertise, although most of this effort could be automated, which would alleviate the need for expertise in software and hardware accessibility. Here, we present the AutoRXN workflow, an automated workflow for exploratory high-throughput electronic structure calculations of molecular systems, in which (i) density functional theory methods are exploited to deliver minimum and transition-state structures and corresponding energies and properties, (ii) coupled cluster calculations are then launched for optimized structures to provide more accurate energy and property estimates, and (iii) multi-reference diagnostics are evaluated to back check the coupled cluster results and subject them to automated multi-configurational calculations for potential multi-configurational cases. All calculations are carried out in a cloud environment and support massive computational campaigns. Key features of all components of the AutoRXN workflow are autonomy, stability, and minimum operator interference. We highlight the AutoRXN workflow with the example of an autonomous reaction mechanism exploration of the mode of action of a homogeneous catalyst for the asymmetric reduction of ketones.

Semi-empirical quantum chemical approaches are known to compromise accuracy for the feasibility of calculations on huge molecules. However, the need for ultrafast calculations in interactive quantum mechanical studies, high-throughput virtual screening, and data-driven machine learning has shifted the emphasis toward calculation runtimes recently. This comes with new constraints for the software implementation as many fast calculations would suffer from a large overhead of the manual setup and other procedures that are comparatively fast when studying a single molecular structure, but which become prohibitively slow for high-throughput demands. In this work, we discuss the effect of various well-established semi-empirical approximations on calculation speed and relate this to data transfer rates from the raw-data source computer to the results of the visualization front end. For the former, we consider desktop computers, local high performance computing, and remote cloud services in order to elucidate the effect on interactive calculations, for web and cloud interfaces in local applications, and in world-wide interactive virtual sessions. The models discussed in this work have been implemented into our open-source software SCINE Sparrow.

Every practical method to solve the Schrödinger equation for interacting many-particle systems introduces approximations. Such methods are therefore plagued by systematic errors. For computational chemistry, it is decisive to quantify the specific error for some system under consideration. Traditionally, the primary way for such an error assessment has been benchmarking data, usually taken from the literature. However, their transferability to a specific molecular system, and hence, the reliability of the traditional approach always remains uncertain to some degree. In this communication, we elaborate on the shortcomings of this traditional way of static benchmarking by exploiting statistical analyses using one of the largest quantum chemical benchmark sets available. We demonstrate the uncertainty of error estimates in the light of the choice of reference data selected for a benchmark study. To alleviate the issues with static benchmarks, we advocate to rely instead on a rolling and system-focused approach for rigorously quantifying the uncertainty of a quantum chemical result.

Quantum mechanical methods have been well-established for the elucidation of reaction paths of chemical processes and for the explicit dynamics of molecular systems. While they are usually deployed in routine manual calculations on reactions for which some insights are already available (typically from experiment), new algorithms and continuously increasing capabilities of modern computer hardware allow for exploratory open-ended computational campaigns that are unbiased and therefore enable unexpected discoveries. Highly efficient and even automated procedures facilitate systematic approaches toward the exploration of uncharted territory in molecular transformations and dynamics. In this work, we elaborate on such explorative approaches that range from reaction network explorations with (stationary) quantum chemical methods to explorative molecular dynamics and migrant wave packet dynamics. The focus is on recent developments that cover the following strategies. (i) Pruning search options for elementary reaction steps by heuristic rules based on the first-principles of quantum mechanics: Rules are required for reducing the combinatorial explosion of potentially reactive atom pairings, and rooting them in concepts derived from the electronic wave function makes them applicable to any molecular system. (ii) Enforcing reactive events by external biases: Inducing a reaction requires constraints that steer and direct elementary-step searches, which can be formulated in terms of forces, velocities, or supplementary potentials. (iii) Manual steering facilitated by interactive quantum mechanics: As ultrafast quantum chemical methods allow for real-time manual interactions with molecular systems, human-intuition-guided paths can be easily explored with suitable human-machine interfaces. (iv) New approaches for transition-state optimization with continuous curve representations can provide stable schemes to be driven in an automated way by allowing for an efficient tuning of the curve's parameters (instead of a manipulation of a collection of structures along the path), and (v) reactive molecular dynamics and direct wave packet propagation exploit the equations of motion of an underlying mechanical theory (usually, classical Newtonian mechanics or Schrödinger quantum mechanics). Explorative approaches are likely to replace the current state of the art in computational chemistry, because they reduce the human effort to be invested in reaction path elucidations, they are less prone to errors and bias-free, and they cover more extensive regions of the relevant configuration space. As a result, computational investigations that rely on these techniques are more likely to deliver surprising discoveries.

The impossibility of experiencing the molecular world with our senses hampers teaching and understanding chemistry because very abstract concepts (such as atoms, chemical bonds, molecular structure, reactivity) are required for this process. Virtual reality, especially when based on explicit physical modeling (potentially in real time), offers a solution to this dilemma. Chemistry teaching can make use of advanced technologies such as virtual-reality frameworks and haptic devices. We show how an immersive learning setting could be applied to help students understand the core concepts of typical chemical reactions by offering a much more intuitive approach than traditional learning settings. Our setting relies on an interactive exploration and manipulation of a chemical system; this system is simulated in real-time with quantum chemical methods, and therefore, behaves in a physically meaningful way.

Raman optical activity spectra of Λ-tris(ethylenediamine)-rhodium(III) {[Rh(en) 3 ] 3+ } have been calculated at 16 on-, near-, and off-resonant wavelengths between 290 and 800 nm. The resulting spectra are analyzed in detail with a focus on the observed resonance effects. Because several electronically excited states are involved, the spectra are never monosignate, as is often observed in resonance Raman optical activity spectra. Most normal modes are enhanced through these resonance effects, but in several cases, de-enhancement effects are found. The molecular origins of the Raman optical activity intensity for selected normal modes are established by means of group coupling matrices. In general, this methodology allows one to produce an intuitive explanation for the intensity behavior of a given normal mode. However, due to the complex electronic structure of [Rh(en) 3 ] 3+ , there are some intriguing resonance effects the origins of which could not be fully clarified in terms of group coupling effects. Therefore, simple and general rules that predict how the intensity of a specific normal mode is affected by resonance effects are difficult to devise.

Introducing one or two alkynyl-iron moieties onto a carbo[6]helicene results in organometallic helicenes (2 a,b) that display strong chiroptical activity combined with efficient redox-triggered switching. The neutral and oxidized forms have been studied in detail by electronic and vibrational circular dichroism, as well as by Raman optical activity (ROA) spectroscopy. The experimental results were analyzed and spectra were assigned with the help of first-principles calculations. In particular, a recently developed method for ROA calculations under resonance conditions has been used to study the intricate resonance effects on the ROA spectrum of mono-iron ethynylhelicene 2 a., (© 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Semiclassical dispersion corrections developed by Grimme and co-workers have become indispensable in applications of Kohn-Sham density functional theory. A deeper understanding of the underlying parametrization might be crucial for well-founded further improvements of this successful approach. To this end, we present an in-depth assessment of the fit parameters present in semiclassical (D3-type) dispersion corrections by means of a statistically rigorous analysis. We find that the choice of the cost function generally has a small effect on the empirical parameters of D3-type dispersion corrections with respect to the reference set under consideration. Only in a few cases, the choice of cost function has a surprisingly large effect on the total dispersion energies. In particular, the weighting scheme in the cost function can significantly affect the reliability of predictions. In order to obtain unbiased (data-independent) uncertainty estimates for both the empirical fit parameters and the corresponding predictions, we carried out a nonparametric bootstrap analysis. This analysis reveals that the standard deviation of the mean of the empirical D3 parameters is small. Moreover, the mean prediction uncertainty obtained by bootstrapping is not much larger than previously reported error measures. On the basis of a jackknife analysis, we find that the original reference set is slightly skewed, but our results also suggest that this feature hardly affects the prediction of dispersion energies. Furthermore, we find that the introduction of small uncertainties to the reference data does not change the conclusions drawn in this work. However, a rigorous analysis of error accumulation arising from different parametrizations reveals that error cancellation does not necessarily occur, leading to a monotonically increasing deviation in the dispersion energy with increasing molecule size. We discuss this issue in detail at the prominent example of the C 60 "buckycatcher". We find deviations between individual parametrizations of several tens of kilocalories per mole in some cases. Hence, in combination with any calculation of dispersion energies, we recommend to always determine the associated uncertainties for which we will provide a software tool.

We present the WCCR10 data set of 10 ligand dissociation energies of large cationic transition metal complexes for the assessment of approximate exchange-correlation functionals. We analyze nine popular functionals, namely BP86, BP86-D3, B3LYP, B3LYP-D3, B97-D-D2, PBE, TPSS, PBE0, and TPSSh by mutual comparison and by comparison to experimental gas-phase data measured with well-known precision. The comparison of all calculated data reveals a large, system-dependent scattering of results with nonnegligible consequences for computational chemistry studies on transition metal compounds. Considering further the comparison with experimental results, the nonempirical functionals PBE and TPSS turn out to be among the best functionals for our reference data set. The deviation can be lowered further by including Hartree-Fock exchange. Accordingly, PBE0 and TPSSh are the two most accurate functionals for our test set, but also these functionals exhibit deviations from experimental results by up to 50 kJ mol(-1) for individual reactions. As an important result, we found no functional to be reliable for all reactions. Furthermore, for some of the ligand dissociation energies studied in this work, invoking semiempirical dispersion corrections yields results which increase the deviation from experimental results. This deviation increases further if structure optimization including such dispersion corrections is performed, although the contrary should be the case, pointing to the need to develop the currently available dispersion corrections further. Finally, we compare our results to other benchmark studies and highlight that the performance assessed for different density functionals depends significantly on the reference molecule set chosen.

In this study, we compute and analyze theoretical Raman optical activity spectra of large model β-sheets in order to identify reliable signatures for this important secondary structure element. We first review signatures that have already been proposed to be indicative of β-sheets. From these signatures, we find that only the couplet in the amide I region can be regarded as a truly reliable signature. In addition, we propose a strong negative peak at ∼1350 cm(-1) to be another good signature for parallel as well as antiparallel β-sheets. We study the robustness of these signatures with respect to perturbations induced by the amino acid side chains, the overall conformation of the sheet structure, and microsolvation. It is found that the latter effects can be very well understood and separated employing the concept of localized modes. Finally, we investigate whether Raman optical activity is capable of discriminating between parallel and antiparallel β-sheets. The amide III region turns out to be most promising for this purpose.

We present the software package M(O)V(I)P(AC) for calculations of vibrational spectra, namely infrared, Raman, and Raman Optical Activity (ROA) spectra, in a massively parallelized fashion. M(O)V(I)P(AC) unites the latest versions of the programs SNF and AKIRA alongside with a range of helpful add-ons to analyze and interpret the data obtained in the calculations. With its efficient parallelization and meta-program design, M(O)V(I)P(AC) focuses in particular on the calculation of vibrational spectra of very large molecules containing on the order of a hundred atoms. For this purpose, it also offers different subsystem approaches such as Mode- and Intensity-Tracking to selectively calculate specific features of the full spectrum. Furthermore, an approximation to the entire spectrum can be obtained using the Cartesian Tensor Transfer Method. We illustrate these capabilities using the example of a large π-helix consisting of 20 (S)-alanine residues. In particular, we investigate the ROA spectrum of this structure and compare it to the spectra of α- and 3(10)-helical analogs., (Copyright © 2012 Wiley Periodicals, Inc.)

To study the capabilities and limitations of Raman optical activity, (-)-(M)σ-[10]helicene and (-)-(M)σ-[4]helicene serve as scaffold molecules on which new chiral centers are introduced by substitution of hydrogen atoms with other functional groups. These functional groups are deuterium atoms, fluorine atoms, and methyl groups. Multiply deuterated species are compared. Then, results of singly deuterated derivatives are compared against results obtained from singly fluorinated and methylated derivatives. The analysis required the calculation of a total of 2433 Raman optical activity spectra. The method we propose for the comparison of the various Raman optical activity spectra is based on the total intensity of squared difference spectra. This allows a qualitative comparison of pairs of Raman optical activity spectra and the extraction of the pair of most similar Raman optical activity spectra for each group of stereoisomers. Different factors were accounted for, such as the spectral resolution (modeled by line broadening) and the range of vibrational frequencies considered. In the case of σ-[4]helicene all generated stereoisomers in each group can be distinguished from one another by Raman optical activity spectroscopy. For σ-[10]helicene this holds except for the lower one of the two resolutions considered. Here, the group consisting of stereoisomers with five chiral centers contains at least one pair of derivatives whose Raman optical activity spectra cannot be distinguished from one another. This indicates that an increased molecular size has a negative effect on the number of chiral centers which can be distinguished by Raman optical activity spectroscopy. Regarding the different substituents, stereoisomers are the better distinguishable in Raman optical activity spectroscopy, the more distinct the signals of the substituent are from the rest of the spectrum.

β-turns belong to the most important secondary structure elements in proteins. On the basis of density functional calculations, vibrational Raman optical activity signatures of different types of β-turns are established and compared as well as related to other signatures proposed in the literature earlier. Our findings indicate that there are much more characteristic ROA signals of β-turns than have been hitherto suggested. These suggested signatures are, however, found to be valid for the most important type of β-turns. Moreover, we compare the influence of different amino acid side chains on these signatures and investigate the discrimination of β-turns from other secondary structure elements, namely α- and 3(10)-helices., (Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The extended amide III region in vibrational spectra of polypeptides and proteins is particularly sensitive to changes in secondary structure. To investigate this structural sensitivity, we have performed density-functional calculations on the small model compound N-acetyl-l-alanine-N-methylamide, which are analyzed using the recently developed analysis in terms of localized modes [J. Chem. Phys. 2009, 130, 084106]. We find that the local modes obtained for different backbone conformations are actually rather similar. To probe the secondary structure sensitivity, we investigate the dependence of the local-mode frequencies and coupling constants on the torsional angles phi and psi. This enables us to set up a local-mode model of the extended amide III region for better understanding its structural sensitivity.