Potential Energy Surface Research Articles

DFT/MM Simulations for Cycloreversion Reaction of Cyclobutane Pyrimidine Dimer with Deprotonated and Protonated E283.

DNA photolyase targets the primary ultraviolet (UV)-induced DNA lesion─cyclobutane pyrimidine dimer (CPD), attaches to it, and catalyzes its dissociation. The catalytic mechanism of DNA photolyase and the role of the conserved residue E283 remain subjects of debate. This study employs two-dimensional potential energy surface maps and minimum free energy paths calculated at the ωB97XD/6-31G/MM level to elucidate these mechanisms. Results suggest that the catalytic process follows a sequential, stepwise reaction in which the C5-C5 and C6-C6 bonds are cleaved in order, facilitated by a protonated E283. Activation free energies for these cleavages are calculated at 4.4 and 4.2 kcal·mol-1, respectively. Protonation of E283 reduces electrostatic repulsion with CPD and forms dual hydrogen bonds with it and provides better solvation, stabilizing the CPD radical anion, particularly during intermediate state. This stabilization renders the initial splitting step exergonic, slows reverse reactions of the C5-C5 bond cleavage and electron transfer, and ensures a high quantum yield. Furthermore, the protonation state of E283 significantly affects the type of bond cleavage. Other residues in the active site were also investigated for their roles in the mechanism.

An Exhaustive Quantum-Classical Study of C6F6+ Using the Newly Formulated Parallel TDDVR Method.

We recently implemented our parallelized quantum-classical dynamical approach, known as the Time-Dependent Discrete Variable Representation (TDDVR) method, which is applied to the spectroscopically important hexafluorobenzene (HFBz) radical cation, where several conical intersections exist in their seven lowest excited electronic states (S11B2u, S21E1g, S31B1u, S41E1u, and S51A2u) considering degeneracy among potential energy surfaces (PESs), to demonstrate their various dynamical aspects. This new parallel version shows almost linear scalability with increasing number of computing processors. To get photoelectron (PE) spectra, Mass-Analyzed Threshold Ionization (MATI) spectra, population dynamics, and many other dynamical observables, the first-principles dynamics is applied at the state-of-the-art level to the corresponding Hamiltonian, where the Jahn-Teller (JT) and pseudo-Jahn-Teller (PJT) type interactions are involved in those coupled seven electronic states. The quantum-classical method is used to thoroughly analyze the effects of these couplings on the nuclear dynamics of the involved electronic states, and the findings are compared with those observables obtained from experiments. Intrinsic dynamical properties are explained using the reduced densities of the wave packet (WP) in a coupled electronic manifold. The PE and MATI spectra of HFBz computed using TDDVR are found to be in good agreement with earlier experimental data and other theoretically simulated spectra.

Neural canonical transformations for vibrational spectra of molecules.

The behavior of polyatomic molecules around their equilibrium positions can be regarded as that of quantum-coupled anharmonic oscillators. Solving the corresponding Schrödinger equations enables the interpretation or prediction of the experimental spectra of molecules. In this study, we developed a novel approach for solving the excited states of anharmonic vibrational systems. The normal coordinates of the molecules are transformed into new coordinates through a normalizing flow parameterized by a neural network. This facilitates the construction of a set of orthogonal many-body variational wavefunctions. This methodology has been validated on an exactly solvable 64-dimensional coupled harmonic oscillator, yielding numerical results with a relative error of 10-6. The neural canonical transformations are also applied to calculate the energy levels of two specific molecules, acetonitrile (CH3CN) and ethylene oxide (C2H4O). These molecules involve 12 and 15 vibrational modes, respectively. A key advantage of this approach is its flexibility concerning the potential energy surface, as it requires no specific form. Furthermore, this method can be readily implemented on large-scale distributed computing platforms, making it easy to extend to investigating complex vibrational structures.

Ab initio exploration of low-lying electronic states of linear and bent MNX+ (M = Ca, Sr, Ba, Ra; X = O, S, Se, Te, Po) and their origins.

High-level multireference and coupled cluster quantum calculations were employed to analyze low-lying electronic states of linear-MNX+ and side-bonded-M[NX]+ (M = Ca, Sr, Ba, Ra; X = O, S, Se, Te, Po) species. Their full potential energy curves (PECs), dissociation energies (Des), geometric parameters, excitation energies (Tes), and harmonic vibrational frequencies (ωes) are reported. The first three chemically bound electronic states of MNX+ and M[NX]+ are 3Σ-, 1Δ, 1Σ+ and 3A″, 1A', 1A″, respectively. The 3Σ-, 1Δ, 1Σ+ of MNX+ originate from the M+(2D) + NX(2Π) fragments, whereas the 3A″, 1A', 1A″ states of M[NX]+ dissociate to M+(2S) + NX(2Π) as a result of avoided crossings. The MNX+ and M[NX]+ are real minima on the potential energy surface and their interconversions are possible. The M2+NX-/M2+[NX]- ionic structure is an accurate representation for their low-lying electronic states. The Des of MNX+ species were found to depend on the dipole moment (μ) of the corresponding NX ligands and a linear relationship between these two parameters was observed.

Relativistic coupled-cluster simulation of the kinetics of the hydrolysis of uranium hexafluoride

Uranium hexafluoride ( UF 6 ) is used ubiquitously in the nuclear fuel cycle. Its spontaneous hydrolysis in the presence of atmospheric moisture is well known but the associated reaction mechanism is poorly understood. Here a computational study was undertaken with the aim of characterizing the rate-limiting step of the hydrolysis of UF 6 under dry conditions. Toward this end, we began by examining the convergence of various energy contributions to the atomization enthalpy ( Δ H at ) of UF 6 and its hydrolysis product, UO 2 F 2 . This enabled a refinement of our previous composite method, resulting in a composite method with improved accuracy that also scales well by leveraging existing massively-parallel codes. We find that extremely high levels of theory are required to obtain Δ H at within experimental error bars, in agreement with the literature. Having calibrated our composite scheme, we proceed to investigate approximations appropriate for computing accurate binding energies and barrier heights on the potential energy surface governing the hydrolysis of UF 6 . In combination with high-accuracy relative energies, a master equation approach is used to generate rate constants, and comparisons are made with recent measurements [Richards et al., RSC Adv., 2020, 10, 34729]. Based on kinetic and equilibrium arguments, we conclude that the hydrolysis of U F 6 , when proceeding under very dry conditions, is unlikely to be initiated via U F 6 + H 2 O → UF 5 OH + HF type reactions. Finally, computed equilibrium constants and rate coefficients are tabulated for the temperature range 300–1800 K.

Accelerating structure search using atomistic graph-based classifiers.

We introduce an atomistic classifier based on a combination of spectral graph theory and a Voronoi tessellation method. This classifier allows for the discrimination between structures from different minima of a potential energy surface, making it a useful tool for sorting through large datasets of atomic systems. We incorporate the classifier as a filtering method in the Global Optimization with First-principles Energy Expressions (GOFEE) algorithm. Here, it is used to filter out structures from exploited regions of the potential energy landscape, whereby the risk of stagnation during the searches is lowered. We demonstrate the usefulness of the classifier by solving the global optimization problem of two-dimensional pyroxene, three-dimensional olivine, Au12, and Lennard-Jones LJ55 and LJ75 nanoparticles.

Unveiling the molecular insights of 2-(carboxymethyl) benzoic acid: A density functional theory approach towards structural and biological attributes

Nowadays density functional theory (DFT) is one of the best methods to explore the vibrational modes and structure of the biological system. Quantum mechanical calculations are performed using gas phase and different solvents (DMSO, methanol and water). The derived global reactive parameters, structural and topological study provides the clear insight of the 2-(Carboxymethyl) benzoic acid. Depth studies of DFT proves the existence of hydrogen bonds between donor and acceptor in the compound, which is supportive for the biological applications. In this paper, different experimental and computational simulated FT-IR, FT-Raman, UV–Vis spectral studies are used to explicate vibration assignments of the 2-(Carboxymethyl) benzoic acid. Experimentally observed vibrational frequency is compared with theoretically simulated spectrum. B3LYP method with 6–311++G (d, p) basis set is used in DFT to optimize the 2-(Carboxymethyl)benzoic acid structure. The most stable lower energy conformer is identified using potential energy surface (PES) analysis using Gaussian 16 W software. ESP, HOMO-LUMO, NBO, and QTAIM calculations have evinced an adequate electronic characterization of 2-(Carboxymethyl) benzoic acid. Further, van der Waals and steric interactions among 2-(Carboxymethyl) benzoic acid have been discussed with the help of RDG study. Hirshfeld surface studies establish the existing various interaction among molecules and total packing arrangement of the crystal structure. Due to the high biological activity score, 2-(Carboxymethyl) benzoic acid is a good therapeutic candidate. Lipophilicity analysis of 2-(Carboxymethyl)benzoic acid clearly explicates the bioactivity properties and its effective drug applications. Further, molecular docking investigates that the compound can be used as anticancer medication. The detailed DFT study of the 2-(Carboxymethyl) benzoic acid justified its biological applications of the present communication. The calculated NLO parameters of 2-(Carboxymethyl)benzoic acid evidenced for good efficacy in diverse filed application has been discussed.

Removal mechanism of double-diamond-abrasive-grinding GaN single crystals under graphene lubrication

Gallium nitride (GaN) is an advanced material used to manufacture chip wafers and high-power devices. Recently, grinding processing, has been applied in the fields of machinery manufacturing, aerospace, and medical devices as a highly efficient machining method. An in-depth understanding of the material removal mechanism produced by the double-grinding processes can provide guidance for the design of GaN-based nanodevices. Herein, molecular dynamics simulations were used to investigate the mechanism of removal of double-diamond-abrasive-grinding gallium nitride crystals under graphene lubrication, and a systematic study was performed to investigate the involved surface morphology, grinding force, stress distribution, and subsurface damage behavior. Results reveal that graphene can substantially enhance the wear resistance of GaN substrates by reducing surface wear, atomic displacement., potential energy, and subsurface damage, thereby playing a protective role toward the substrate. As the grinding depth increases, the grinding force and subsurface damage depth also increase. Furthermore, the effects of abrasive grain spacing on subsurface damage depth and phase change atoms were analyzed and found to have limited influence on material removal efficiency. These results deepen our understanding of material removal and protection mechanisms relative to substrates resulting from double-grinding processes as well as offer valuable insights for the rational design of abrasive wheels.

Fulvenallenyl Radical (C7H5·)-Mediated Gas-Phase Synthesis of Bicyclic Aromatic C10H8 Isomers: Can Fulvenallenyl Efficiently React with Closed-Shell Hydrocarbons?

To understand the reactivity of resonantly stabilized radicals, often found in relevant concentrations in gaseous environments, it is important to determine their main reaction pathways. Here, it is investigated whether the fulvenallenyl radical (C7H5·) reacts preferentially with closed-shell molecules or radicals. Electronic structure calculations on the C10H9 potential energy surface accessed by the reactions of C7H5· with methylacetylene (CH3CCH) and allene (H2CCCH2) were combined with RRKM-ME calculations of temperature- and pressure-dependent rate constants using the automated EStokTP software suite and kinetic modeling to assess the reactivity of C7H5· with closed-shell unsaturated hydrocarbons. Experimentally, the reactions were attempted in a chemical microreactor heated to 998 ± 10 K by preparing fulvenallenyl radicals via pyrolysis of trichloromethylbenzene (C7H5Cl3) and seeding the radicals in methylacetylene or allene carrier gas, with product identification by means of photoionization mass spectrometry. The measured photoionization efficiency curve of m/z = 128 was assigned to a linear combination of the reference curves of two C10H8 isomers, azulene (minor) and naphthalene (major), presumably resulting from the C7H5· plus C3H4 reactions. However, the calculations demonstrated that these reactions are too slow, and kinetic modeling of processes in the reactor allowed us to conclude that the observation of naphthalene and azulene is due to the C7H5· plus C3H3· reaction, where propargyl is produced by direct hydrogen atom abstraction by chlorine (Cl) atoms from allene or methylacetylene and Cl stem from the pyrolysis of C7H5Cl3. Modeling results under the copyrolysis conditions of toluene and methylacetylene in high-temperature shock tube experiments confirmed the prevalence of the fulvenallenyl reaction with propargyl over its reactions with C3H4 even when the concentrations of allene and methylacetylene largely exceed that of propargyl. Overall, the reactions of fulvenallenyl with both allene and methylacetylene were found to be noncompetitive in the formation of naphthalene and azulene thus attesting the inefficiency of the fulvenallenyl radical reactions with the prototype closed-shell hydrocarbon species. In the meantime, the new reaction pathways revealed, including H-assisted isomerizations between C10H8 isomers and decomposition reactions of various C10H9 isomers, emerge as relevant and are recommended for inclusion in combustion kinetic models for naphthalene formation.

Novel Insights into the Catalytic Mechanism of Collagenolysis by Zn(II)-Dependent Matrix Metalloproteinase-1.

Collagen hydrolysis, catalyzed by Zn(II)-dependent matrix metalloproteinases (MMPs), is a critical physiological process. Despite previous computational investigations into the catalytic mechanisms of MMP-mediated collagenolysis, a significant knowledge gap in understanding remains regarding the influence of conformational sampling and entropic contributions at physiological temperature on enzymatic collagenolysis. In our comprehensive multilevel computational study, employing quantum mechanics/molecular mechanics (QM/MM) metadynamics (MetD) simulations, we aimed to bridge this gap and provide valuable insights into the catalytic mechanism of MMP-1. Specifically, we compared the full enzyme-substrate complex in solution, clusters in solution, and gas-phase to elucidate insights into MMP-1-catalyzed collagenolysis. Our findings reveal significant differences in the catalytic mechanism when considering thermal effects and the dynamic evolution of the system, contrasting with conventional static potential energy surface QM/MM reaction path studies. Notably, we observed a significant stabilization of the critical tetrahedral intermediate, attributed to contributions from conformational flexibility and entropy. Moreover, we found that protonation of the scissile bond nitrogen occurs via proton transfer from a Zn(II)-coordinated hydroxide rather than from a solvent water molecule. Following C-N bond cleavage, the C-terminus remains coordinated to the catalytic Zn(II), while the N-terminus forms a hydrogen bond with a solvent water molecule. Subsequently, the release of the C-terminus is facilitated by the coordination of a water molecule. Our study underscores the pivotal role of protein conformational dynamics at physiological temperature in stabilizing the transition state of the rate-limiting step and key intermediates, compared to the corresponding reaction in solution. These fundamental insights into the mechanism of collagen degradation provide valuable guidance for the development of MMP-1-specific inhibitors.

Deciphering the Factors Controlling Hydrogen and Methyl Spillover on Rh/Cu(111) Single-Atom Alloy.

Spillover of adsorbed species from one active site to another is a key step in heterogeneous catalysis. However, the factors controlling this step, particularly the spillover of polyatomic species, have rarely been studied. Herein, we investigate the spillover dynamics of H* and CH3* species on a single-atom alloy surface (Rh/Cu(111)) upon the dissociative chemisorption of methane (CH4), using molecular dynamics that considers both surface phonons and electron-hole pairs. These dynamical calculations are made possible by a high-dimensional potential energy surface machine learned from density functional theory data. Our results provide compelling evidence that the H* and CH3* can spill over on the metal surface at experimental temperatures and reveal novel dynamical features involving an internal motion during diffusion for CH3*. Increasing surface temperature hasminor effect on promoting spillover, as geminate recombinative desorption becomes more prevalent. However, the poisoning of the active site can be mitigated byfrequent gaseous molecular collisions that occur under ambient pressure in real-world catalysis, which transfer energy to the trapped adsorbates. Interestingly, the bulky CH3* exhibits a significant spillover advantage over the light H* due to its larger size, which facilitates energy acquisition. These insights help to advance our understanding of spillover in heterogeneous catalysis.

Steric Effect and Intrinsic Electrophilicity and Nucleophilicity from a Conceptual Density Functional Theory and Information-Theoretic Approach as Quantitative Probes of Chemical Reactions.

Appreciating reactivity in terms of physicochemical effects for chemical processesis one of the most important undertakings in chemistry. While transition state (TS) theory provides the framework enabling the reliable calculation of the barrier height for a given elementary step, analytical tools are necessary to gain insight into key factors governing the different processes during chemical reactions. In this contribution, we partition the potential energy surface of an elementary step along the intrinsic coordinate into three segments, the so-called Pre-TS, TS, and Post-TS regions, and then determine the most important factors dictating each segment. This analysis is based on the use of both reactivity descriptors from conceptual density functional theory and concepts from the information-theoretic approach in density functional theory. We found that in both Pre-TS and Post-TS regions, steric effects are the dominant factors, whereas in the TS region, it is the intrinsic electrophilic and nucleophilic propensity of the transition state structure that governs the reactivity. The wide applicability of our approach is shown by a validation for a total of 37 organic and inorganic reactions. This work thus, in our view, provides a novel perspective on how chemical reactivity can be quantified at different stages of chemical reactions.

Construction of Highly Accurate Machine Learning Potential Energy Surfaces for Excited-State Dynamics Simulations Based on Low-Level Data Sets.

Machine learning is capable of effectively predicting the potential energies of molecules in the presence of high-quality data sets. Its application in the construction of ground- and excited-state potential energy surfaces is attractive to accelerate nonadiabatic molecular dynamics simulations of photochemical reactions. Because of the huge computational cost of excited-state electronic structure calculations, the construction of a high-quality data set becomes a bottleneck. In the present work, we first built two data sets. One was obtained from surface hopping dynamics simulations at the semiempirical OM2/MRCI level. Another was extracted from the dynamics trajectories at the CASSCF level, which was reported previously. The ground- and excited-state potential energy surfaces of ethylene-bridged azobenzene at the CASSCF computational level were constructed based on the former low-level data set. Although non-neural network machine learning methods can achieve good or modest performance during the training process, only neural network models provide reliable predictions on the latter external test data set. The BPNN and SchNet combined with the Δ-ML scheme and the force term in the loss functions are recommended for dynamics simulations. Then, we performed excited-state dynamics simulations of the photoisomerization of ethylene-bridged azobenzene on machine learning potential energy surfaces. Compared with the lifetimes of the first excited state (S1) estimated at different computational levels, our results on the E isomer are in good agreement with the high-level estimation. However, the overestimation of the Z isomer is unimproved. It suggests that smaller errors during the training process do not necessarily translate to more accurate predictions on high-level potential energies or better performance on nonadiabatic dynamics simulations, at least in the present case.

A Neural Network Potential Energy Surface and Quantum Dynamics Study of Ca(1S) + H2(v 0 = 0, j 0 = 0) → CaH + H Reaction.

The reactive collision between Ca and H2 molecules has attracted great interest experimentally due to the key role of the product CaH molecule in the field of astrophysics and cold molecules. However, quantum dynamics calculations for this system have not been reported due to the lack of a global potential energy surface (PES). Herein, a globally accurate PES of the ground-state CaH2 is developed by combining 11365 high-level ab initio points and permutation invariant polynomial neural network method. Based on the newly constructed PES, the state-to-state quantum dynamics calculations for the Ca(1S) + H2 (v 0 = 0, j 0 = 0) → CaH + H reaction are carried out using the time-dependent wave packet method. The dynamic results reveal that the reaction follows the complex-forming mechanism near the reactive threshold, whereas both the indirect insertion mechanism and direct abstraction mechanism have effects at higher collision energies. The newly constructed PES can be used to further study the influence of isotope substitution, rovibrational excitation, and spatial orientation of reactant molecules on reaction dynamics.

Computational determination of the S1(Ã1A″) absorption spectra of HONO and DONO using full-dimensional neural network potential energy surfaces.

The Ã1A″ ← X̃1A' absorption spectra of HONO and DONO were simulated by a full six-dimensional quantum mechanical method based on the newly constructed potential energy surfaces for the ground and excited electronic states, which were represented by the neural network method utilizing over 36 000 abinitio energy points calculated at the multireference configuration interaction level with Davidson correction. The absorption spectrum of HONO/DONO comprises a superposition of the spectra from two isomers, namely, trans- and cis-HONO/DONO, due to their coexistence in the ground X̃1A' state. Our calculated spectra of both HONO and DONO were found to be in fairly good agreement with the experiment, including the energy positions and widths of the peaks. The dominant progression was assigned to the N=O stretch mode (20n) associated with trans-HONO/DONO, which can be attributed to the promotion of an electron to the π* orbital of N=O. Specifically, the resonances with higher vibrational quanta were found to be in the domain of the Feshbach-type resonances. The assignments of the spectra and mode specificity therein are discussed.

Toward Accurate Spin-Orbit Splittings from Relativistic Multireference Electronic Structure Theory.

Most nonrelativistic electron correlation methods can be adapted to account for relativistic effects, as long as the relativistic molecular spinor integrals are available, from either a four-, two-, or one-component mean-field calculation. However, relativistic multireference correlation methods remain a relatively unexplored area, with mixed evidence regarding the improvements brought by perturbative treatments. We report, for the first time, the implementation of state-averaged four-component relativistic multireference perturbation theories to second and third order based on the driven similarity renormalization group (DSRG). With our methods, named 4c-SA-DSRG-MRPT2 and 3, we find that the dynamical correlation included on top of 4c-CASSCF references can significantly improve the spin-orbit splittings in p-block elements and potential energy surfaces when compared to 4c-CASSCF and 4c-CASPT2 results. We further show that 4c-DSRG-MRPT2 and 3 are applicable to these systems over a wide range of the flow parameter, with systematic improvement from second to third order in terms of both improved error statistics and reduced sensitivity with respect to the flow parameter.

Paddlanes revisited: Which are the smallest possible?

AbstractPaddlanes are tricyclic molecules with four bridging chains that share the same two bridgehead carbon atoms. The smallest known paddlane containing only carbon atoms in the main framework has a total of 18 atoms. We utilized computational chemistry (MP2/cc‐pVTZ) to locate the smallest possible all‐carbon paddlanes that meet the criterion suggested by Hoffmann, Schleyer, and Schaefer as being “fleeting,” meaning frequency calculations suggest the structures are energy minima on their respective potential energy surfaces (PES). Our results suggest that paddlane compounds with a total of 10 or fewer atoms can be considered to be non‐viable either because they are not energy minima on the PES or due to strain in the system that manifests as especially long carbon–carbon bonds. Some paddlanes with a total of 11 carbon atoms proved to be energy minima but still exhibited longer carbon–carbon bonds than normal. Finally, several paddlanes with a total of 12 carbons appear to be the least strained since carbon–carbon bond lengths remain reasonable.

Distinguishing homolytic vs heterolytic bond dissociation of phenylsulfonium cations with localized active space methods

Modeling chemical reactions with quantum chemical methods is challenging when the electronic structure varies significantly throughout the reaction and when electronic excited states are involved. Multireference methods, such as complete active space self-consistent field (CASSCF), can handle these multiconfigurational situations. However, even if the size of the needed active space is affordable, in many cases, the active space does not change consistently from reactant to product, causing discontinuities in the potential energy surface. The localized active space SCF (LASSCF) is a cheaper alternative to CASSCF for strongly correlated systems with weakly correlated fragments. The method is used for the first time to study a chemical reaction, namely the bond dissociation of a mono-, di-, and triphenylsulfonium cation. LASSCF calculations generate smooth potential energy scans more easily than the corresponding, more computationally expensive CASSCF calculations while predicting similar bond dissociation energies. Our calculations suggest a homolytic bond cleavage for di- and triphenylsulfonium and a heterolytic pathway for monophenylsulfonium.

Machine Learning Accelerates Precise Excited-State Potential Energy Surface Calculations on a Quantum Computer.

Electronically excited-state problems represent a crucial research field in quantum chemistry, closely related to numerous practical applications in photophysics and photochemistry. The emerging of quantum computing provides a promising computational paradigm to solve the Schrödinger equation for predicting potential energy surfaces (PESs). Here, we present a deep neural network model to predict parameters of the quantum circuits within the framework of variational quantum deflation and subspace search variational quantum eigensolver, which are two popular excited-state algorithms to implement on a quantum computer. The new machine learning-assisted algorithm is employed to study the excited-state PESs of small molecules, achieving highly accurate predictions. We then apply this algorithm to study the excited-state properties of the ArF system, which is essential to a gas laser. Through this study, we believe that with future advancements in hardware capabilities, quantum computing could be harnessed to solve excited-state problems for a broad range of systems.

Accurate reference spectra of HD in an H2–He bath for planetary applications

Context. The hydrogen deuteride (HD) molecule is an important deuterium tracer in astrophysical studies. The atmospheres of gas giants are dominated by molecular hydrogen, and the simultaneous observation of H2 and HD lines provides reliable information on the D/H ratios on these planets. The reference spectroscopic parameters play a crucial role in such studies. Under the thermodynamic conditions encountered in these atmospheres, spectroscopic studies of HD require not only the knowledge of line intensities and positions but also accurate reference data on pressure-induced line shapes and shifts. Aims. Our aim is to provide accurate collision-induced line-shape parameters for HD lines that cover any thermodynamic conditions relevant to the atmospheres of giant planets, namely any relevant temperature, pressure, and perturbing gas composition (the H2–He mixture). Methods. We performed quantum-scattering calculations on our new, highly accurate ab initio potential energy surface (PES), and we used scattering S matrices obtained in this way to determine the collision-induced line-shape parameters. We used cavity ring-down spectroscopy to validate our theoretical methodology. Results. We report accurate collision-induced line-shape parameters for the pure rotational R(0), R(1), and R(2) lines, the most relevant HD lines for investigations of the atmospheres of the giant planets. Besides the basic Voigt-profile collisional parameters (i.e., the broadening and shift parameters), we also report their speed dependences and the complex Dicke parameter, which can influence the effective width and height of the HD lines up to almost a factor of 2 for giant planet conditions. The sub-percent-level accuracy reached in this work is a considerable improvement over previously available data. All the reported parameters (and their temperature dependences) are consistent with the HITRAN database format, hence allowing for the use of the HITRAN Application Programming Interface (HAPI) for generating the beyond-Voigt spectra of HD.