Machine learning models are poised to make a transformative impact on chemical sciences by dramatically accelerating computational algorithms and amplifying insights available from computational chemistry methods. However, achieving this requires a confluence and coaction of expertise in computer science and physical sciences. This review is written for new and experienced researchers working at the intersection of both fields. We first provide concise tutorials of computational chemistry and machine learning methods, showing how insights involving both can be achieved. We then follow with a critical review of noteworthy applications that demonstrate how computational chemistry and machine learning can be used together to provide insightful (and useful) predictions in molecular and materials modeling, retrosyntheses, catalysis, and drug design.
Reliable predictions of the behaviour of chemical systems are essential across many industries, from nanoscale engineering over validation of advanced materials to nanotoxicity assessment in health and medicine. For the future we therefore envision a paradigm shift for the design of chemical simulations across all length scales from a prescriptive to a predictive and quantitative science. This paper presents an integrative perspective about the state-of-the-art of modelling in computational and theoretical chemistry with examples from data- and equation-based models. Extension to include relia…
We introduce an extension of a recently published method\cite{Mendels2018} to obtain low-dimensional collective variables for studying multiple states free energy processes in chemical reactions. The only information needed is a collection of simple statistics of the equilibrium properties of the reactants and product states. No information on the reaction mechanism has to be given. The method allows studying a large variety of chemical reactivity problems including multiple reaction pathways, isomerization, stereo- and regiospecificity. We applied the method to two fundamental organic chemica…
We introduce DeePKS-kit, an open-source software package for developing machine learning based energy and density functional models. DeePKS-kit is interfaced with PyTorch, an open-source machine learning library, and PySCF, an ab initio computational chemistry program that provides simple and customized tools for developing quantum chemistry codes. It supports the DeePHF and DeePKS methods. In addition to explaining the details in the methodology and the software, we also provide an example of developing a chemically accurate model for water clusters.
We present a solution to the conservation form (Eulerian form) of the quantum hydrodynamic equations which arise in chemical dynamics by implementing a mixed/discontinuous Galerkin (MDG) finite element numerical scheme. We show that this methodology is stable, showing good accuracy and a remarkable scale invariance in its solution space. In addition the MDG method is robust, adapting well to various initial-boundary value problems of particular significance in a range of physical and chemical applications. We further show explicitly how to recover the Lagrangian frame (or pathline) solutions.
The Independent Reaction Time method is a computationally efficient Monte-Carlo based approach to simulate the evolution of initially heterogeneously distributed reaction-diffusion systems that has seen wide-scale implementation in the field of radiation chemistry modeling. The method gains its efficiency by preventing multiple calculations steps before a reaction can take place. In this work we outline the development and implementation of this method in the Geant4 toolkit to model ionizing radiation induced chemical species in liquid water. The accuracy and validity of these developed chemic…
We present a generator of virtual molecules that selects valid chemistry on the basis of the octet rule. Also, we introduce a mesomer group key that allows a fast detection of duplicates in the generated structures. Compared to existing approaches, our model is simpler and faster, generates new chemistry and avoids invalid chemistry. Its versatility is illustrated by the correct generation of molecules containing third-row elements and a surprisingly adept handling of complex boron chemistry. Without any empirical parameters, our model is designed to be valid also in unexplored regions of chem…
Significant progress in the development of efficient and fast algorithms for quantum chemical calculations has been made in the past two decades. The main focus has always been the desire to be able to treat ever larger molecules or molecular assemblies---especially linear and sub-linear scaling techniques are devoted to the accomplishment of this goal. However, as many chemical reactions are rather local, they usually involve only a limited number of atoms so that models of about two hundred (or even less) atoms embedded in a suitable environment are sufficient to study their mechanisms. Thus…
The rational design of molecules and materials is becoming more and more important. With the advent of powerful computer systems and sophisticated algorithms, quantum chemistry plays an important role in rational design. While traditional quantum chemical approaches predict the properties of a predefined molecular structure, the goal of inverse quantum chemistry is to find a structure featuring one or more desired properties. Herein, we review inverse quantum chemical approaches proposed so far and discuss their advantages as well as their weaknesses.
The prospects, needs and limits in current approaches in catalysis to accelerate the transition to e-chemistry, where this term indicates a fossil fuel-free chemical production, are discussed. It is suggested that e-chemistry is a necessary element of the transformation to meet the targets of net zero emissions by year 2050 and that this conversion from the current petrochemistry is feasible. However, the acceleration of the development of catalytic technologies based on the use of renewable energy sources (indicated as reactive catalysis) is necessary, evidencing that these are part of a syst…
Accurate Chemistry Collection: Coupled cluster atomization energies for broad chemical space
Microsoft Research, AI for Science（微软研究院，AI for Science）；Microsoft Research, Accelerator（微软研究院，Accelerator）；School of Science and Technology, University of New England, Australia（澳大利亚新南威尔士大学科学与技术学院）
It has been shown that it is possible to transform a well-stirred chemical medium into a logic-gate simply by varying the chemistry's external conditions (feed rates, lighting conditions, etc). We extend this work, showing that the same method can be generalized to spatially-extended systems. We vary the external conditions of a well-known chemical medium (a cubic autocatalytic reaction diffusion model), so that different regions of the simulated chemistry are operating under particular conditions at particular times. In so doing, we are able to transform the initially uniform chemistry, not j…
Polaritonic chemistry has become a rapidly developing field within the last few years. A multitude of experimental observations suggest that chemical properties can be fundamentally altered and novel physical states appear when matter is strongly coupled to resonant cavity modes, i.e. when hybrid light-matter states emerge. Up until now, theoretical approaches to explain and predict these observations were either limited to phenomenological quantum optical models, suited to describe collective polaritonic effects, or alternatively to ab initio approaches for small system sizes. The later metho…
Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fast and accurate predictions of atomistic chemical properties, they do not explicitly capture the electronic degrees of freedom of a molecule, which limits their applicability for reactive chemistry and chemical analysis. Here we present a deep learning framework for the prediction of the quantum mechanical wavefunction in a local basis of atomic orbitals from which all other ground-state properties can be derived. Th…
We demonstrate the occurrence of oscillatory reactions in the ultra-cold chemistry of atom-molecular Bose-Einstein condensate. Nonlinear oscillations in the mean-field dynamics occur for a specific range of elliptic modulus, giving rise to both in- and out-phase modulations in the atom-molecule population density. The reaction front velocity is found to be controlled by photoassociation, which also regulates the condensate density. Two distinct pair of in-phase bright localized gap solitons are found as exact solutions, existence of one of which necessarily requires a background. Cnoidal atomi…
The chemical production of graphene as well as its controlled wet- chemical modification is a challenge for synthetic chemists and the characterization of reaction products requires sophisticated analytic methods. In this review we first describe the structure of graphene and graphene oxide. We then outline the most important synthetic methods which are used for the production of these carbon based nanomaterials. We summarize the state-of-the-art for their chemical functionalization by non-covalent and covalent approaches. We put special emphasis on the differentiation of the terms graphite, g…
A Fast, Parallelized, GPU-Accelerated Photochemical Model, XODIAC, with Built-in Equilibrium Chemistry and Multiple Chemical Networks for Exoplanetary Atmospheres
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 typica…
The answers to many unsolved problems lie in the intractable chemical space of molecules and materials. Machine learning techniques are rapidly growing in popularity as a way to compress and explore chemical space efficiently. One of the most important aspects of machine learning techniques is representation through the feature vector, which should contain the most important descriptors necessary to make accurate predictions, not least of which is the atomic species in the molecule or material. In this work we introduce a compressed representation of physical properties for atomic species we c…
Chemistry has arrived on the shore of the Island of Stability with the first chemical investigation of the superheavy elements Cn, 113, and 114. The results of three experimental series leading to first measured thermodynamic data and qualitatively evaluated chemical properties for these elements are described. An interesting volatile compound class has been observed in the on-line experiments for the elements Bi and Po. Hence, an exciting chemical study of their heavier transactinide homologues, elements 115 and 116 is suggested.
Many chemical concepts can be well defined in the context of quantum chemical theories. Examples are the electronegativity scale of Mulliken and Jaffe and the hard and soft acids and bases concept of Pearson. The sound theoretical basis allows for a systematic definition of such concepts. However, while they are often used to describe and compare chemical processes in terms of reactivity, their predictive power remains unclear. In this work, we elaborate on the predictive potential of chemical reactivity concepts, which can be crucial for autonomous reaction exploration protocols to guide them…
Quantum computing, an innovative computing system carrying prominent processing rate, is meant to be the solutions to problems in many fields. Among these realms, the most intuitive application is to help chemical researchers correctly de-scribe strong correlation and complex systems, which are the great challenge in current chemistry simulation. In this paper, we will present a standalone quantum simulation tool for chemistry, ChemiQ, which is designed to assist people carry out chemical research or molecular calculation on real or virtual quantum computers. Under the idea of modular programm…
Chemical processes in closed systems are poorly controllable since they always relax to equilibrium. Living systems avoid this fate and give rise to a much richer diversity of phenomena by operating under nonequilibrium conditions. Recent experiments in dissipative self-assembly also demonstrated that by opening reaction vessels and steering certain concentrations, an ocean of opportunities for artificial synthesis and energy storage emerges. To navigate it, thermodynamic notions of energy, work and dissipation must be established for these open chemical systems. Here, we do so by building upo…
Modern quantum chemistry can make quantitative predictions on an immense array of chemical systems. However, the interpretation of those predictions is often complicated by the complex wave function expansions used. Here we show that an exceptionally simple algebraic construction allows for defining atomic core and valence orbitals, polarized by the molecular environment, which can exactly represent self-consistent field wave functions. This construction provides an unbiased and direct connection between quantum chemistry and empirical chemical concepts, and can be used, for example, to calcul…
We present a detailed discussion of self-energy embedding theory (SEET) which is a quantum embedding scheme allowing us to describe a chosen subsystem very accurately while keeping the description of the environment at a lower cost. We apply SEET to molecular examples where commonly our chosen subsystem is made out of a set of strongly correlated orbitals while the weakly correlated orbitals constitute an environment. Such a self-energy separation is very general and to make this procedure applicable to multiple systems a detailed and practical procedure for the evaluation of the system and en…
Although the simulation of quantum chemistry is one of the most anticipated applications of quantum computing, the scaling of known upper bounds on the complexity of these algorithms is daunting. Prior work has bounded errors due to Trotterization in terms of the norm of the error operator and analyzed scaling with respect to the number of spin-orbitals. However, we find that these error bounds can be loose by up to sixteen orders of magnitude for some molecules. Furthermore, numerical results for small systems fail to reveal any clear correlation between ground state error and number of spin-…
In this work, we demonstrate a remarkable change of chemical trend of Iron under high pressure that is of great importance for understanding the distribution of elements in the Earth's mantle and core. Using first principles crystal structure search method, we conduct a systematic study of the propensity of p block elements to chemically bind with iron under high pressures ranging from ambient conditions to that of Earth's core. We show that under increasing pressure, iron tends to reverse its chemical nature, changing from an electron donor (reductant) to an electron acceptor, and oxidizes p-…
Achieving control over chemical reaction's rate and stereoselectivity realizes one of the Holy Grails in chemistry that can revolutionize chemical and pharmaceutical industries. Strong light-matter interaction in optical or nanoplasmonic cavities might provide the knob to reach such control. In this work, we demonstrate the catalytic and selectivity control of an optical cavity for two selected Diels-Alder cycloaddition reactions using the quantum electrodynamics coupled cluster (QED-CC) method. Herein, we find that by changing the molecular orientation with respect to the polarization of the …
Quantum mechanical tunneling of atoms is increasingly found to play an important role in many chemical transformations. Experimentally, atom-tunneling can be indirectly detected by temperature-independent rate constants at low temperature or by enhanced kinetic isotope effects. On the contrary, using computational investigations the influence of tunneling on the reaction rates can directly be monitored. The tunnel effect, for example, changes reaction paths and branching ratios, enables chemical reactions in an astrochemical environment that would be impossible by thermal transition, and influ…
The basic concepts of orbital entanglement and its application to chemistry are briefly reviewed. The calculation of orbital entanglement measures from correlated wavefunctions is discussed in terms of reduced $n$-particle density matrices. Possible simplifications in their evaluation are highlighted in case of seniority-zero wavefunctions. Specifically, orbital entanglement allows us to dissect electron correlation effects in its strong and weak contributions, to determine bond orders, to assess the quality and stability of active space calculations, to monitor chemical reactions, and to iden…
The relationship between the chemical picture of an isolated molecule and that arising from the eiegenfunctions of the Schrodinger Coulomb Hamiltonian ror the isolated molecule are examined and discussed.
With the rapid development of quantum technology, one of the leading applications is the simulation of chemistry. Interestingly, even before full scale quantum computers are available, quantum computer science has exhibited a remarkable string of results that directly impact what is possible in chemical simulation with any computer. Some of these results even impact our understanding of chemistry in the real world. In this perspective, we take the position that direct chemical simulation is best understood as a digital experiment. While on one hand this clarifies the power of quantum computers…
Chemists now routinely use software as part of their work. For example, virtual chemistry allows chemical reactions to be simulated. In particular, a selection of software is available for the visualisation of complex 3-dimensional molecular structures. Many of these are very beautiful in their own right. As well as being included as illustrations in academic papers, such visualisations are often used on the covers of chemistry journals as artistically decorative and attractive motifs. Chemical images have also been used as the basis of artworks in exhibitions. This paper explores the developm…
In this activity, we describe how the video game Fortnite provides a nice opportunity for students to think about chemistry. The game has a survival system based on the acquisition and use of items, which has interesting chemical and physical properties. In addition, the game also provides an important platform of crafting and base building and open discussion on materials.
The collisions between high-energy ions and solids can result in significant physical and chemical changes to the material. These effects are potentially important for better understanding the chemistry of interstellar and planetary bodies, which are exposed to cosmic radiation and the solar wind, respectively, however, modeling such collisions on a detailed microscopic basis has thus far been largely unsuccessful. To that end, a new model, entitled CIRIS: the Chemistry of Ionizing Radiation in Solids, was created to calculate the physical and chemical effects of the irradiation of solid mater…
Molecular polaritons are the optical excitations which emerge when molecular transitions interact strongly with confined electromagnetic fields. Increasing interest in the hybrid molecular-photonic materials that host these excitations stems from recent observations of their novel and tunable chemistry. Some of the remarkable functionalities exhibited by polaritons include the ability to induce long-range excitation energy transfer, enhance charge conductivity, and inhibit or enhance chemical reactions. In this review, we explain the effective theories of molecular polaritons which form a basi…
We theoretically demonstrate that chemical reaction rate constant can be significantly suppressed by coupling molecular vibrations with an optical cavity, exhibiting both the collective coupling effect and the cavity-frequency modification of the rate constant. When a reaction coordinate is strongly coupled to the solvent molecules, the reaction rate constant is reduced due to the dynamical caging effect. We demonstrate that collectively coupling the solvent to the cavity can further enhance this dynamical caging effect, leading to additional suppression of the chemical kinetics. This effect i…
Quantum chemistry calculations such as the prediction of molecular properties and modeling of chemical reactions are a few of the critical areas where near-term quantum computers can showcase quantum advantage. We present a method to calculate energy derivatives for both ground state and excited state energies with respect to the parameters of a chemical system based on the framework of the variational quantum eigensolver (VQE). A low-depth implementation of quantum circuits within the hybrid variational paradigm is designed, and their computational costs are analyzed. We showcase the effectiv…
The demonstration of strong and ultrastrong coupling regimes of cavity QED with polyatomic molecules has opened new routes to control chemical dynamics at the nanoscale. We show that strong resonant coupling of a cavity field with an electronic transition can effectively decouple collective electronic and nuclear degrees of freedom in a disordered molecular ensemble, even for molecules with high-frequency quantum vibrational modes having strong electron-vibration interactions. This type of polaron decoupling can be used to control chemical reactions. We show that the rate of electron transfer …
Inclusion of sulfur chemistry in a validated C/H/O/N chemical network: identification of key C/S coupling pathways
Université Paris Cité and Univ Paris Est Creteil, CNRS, LISA（巴黎西岱大学与巴黎东克雷泰伊大学，法国国家科学研究中心，LISA）；Astrophysics Group, University of Exeter（埃克塞特大学天体物理学组）；Université de Lorraine, CNRS, LRGP（洛林大学，法国国家科学研究中心，LRGP）；Department of Physics and Astronomy, University College London（伦敦大学学院物理与天文系）
Identification of Solid-Electrolyte Interphase Species by Joint Characterization of Li-ion Battery Chemistry by Mass Spectrometry and Electro-Chemical Reaction Networks
Bakar Institute of Digital Materials for the Planet, University of California at Berkeley（加州大学伯克利分校巴克数字材料星球研究所）；Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）；Department of Materials Science and Engineering, University of California at Berkeley（加州大学伯克利分校材料科学与工程系）；Université de Rouen Normandie, INSA Rouen Normandie, Université de Caen Normandie, ENSICAEN, CNRS, Institut CARMeN UMR 6064（鲁昂诺曼底大学、鲁昂国立应用科学学院、卡昂诺曼底大学、ENSICAEN、法国国家科学研究中心CARMeN联合研究所）；TotalEnergies OneTech, TotalEnergies Research & Technology Gonfreville（道达尔能源OneTech、道达尔能源贡夫勒维尔研究与技术部）；Saft, Corporate Research（萨博公司企业研究部）；International Joint Laboratory-Complex Matrices Molecular Characterization (iC2MC)（国际联合实验室-复杂基体分子表征）；TotalEnergies OneTech Belgium（道达尔能源OneTech比利时）；TotalEnergies EP Research & Technology（道达尔能源勘探与生产研究与技术部）；Universite de Pau et des Pays de l’Adour, CNRS, IPREM（波城与阿杜尔地区大学、法国国家科学研究中心IPREM）
Generative artificial intelligence for computational chemistry: a roadmap to predicting emergent phenomena
University of Maryland（马里兰大学）；Institute for Physical Science and Technology（物理科学与技术研究所）；University of Maryland Institute for Health Computing（马里兰大学健康计算研究所）；Department of Chemistry and Biochemistry（化学与生物化学系）；Department of Physics（物理系）；Biophysics Program（生物物理学项目）
