SEARCH · Engineering Papers

Results for “Quantum mechanical calculations”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Enhancing the accuracy of density functional tight binding models through ChIMES many-body interaction potentials

Semi-empirical quantum models such as Density Functional Tight Binding (DFTB) are attractive methods for obtaining quantum simulation data at longer time and length scales than possible with standard approaches. However, application of these models can require lengthy effort due to the lack of a systematic approach for their development. In this work, we discuss the use of the Chebyshev Interaction Model for Efficient Simulation (ChIMES) to create rapidly parameterized DFTB models, which exhibit strong transferability due to the inclusion of many-body interactions that might otherwise be inaccurate. We apply our modeling approach to silicon polymorphs and review previous work on titanium hydride. We also review the creation of a general purpose DFTB/ChIMES model for organic molecules and compounds that approaches hybrid functional and coupled cluster accuracy with two orders of magnitude fewer parameters than similar neural network approaches. In all cases, DFTB/ChIMES yields similar accuracy to the underlying quantum method with orders of magnitude improvement in computational cost. In conclusion, our developments provide a way to create computationally efficient and highly accurate simulations over varying extreme thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly, and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1995

Nucleosynthesis in AGB stars: Observation of Mg-25 and Mg-26 in IRC+10216 and possible detection of Al-26

We report the detection in the circumstellar envelope IRC+10216 of millimeter lines of the rare isotopomers (25)MgNC and (26)MgNC, as well as of a line at 234433 MHz, which could be the J= 7-6 transition of (26)AlF (an alternate, although less likely identified would be the J= 9-8 transition of NaF). The derived Mg-24:Mg-25:Mg-26 isotopic abundance ratios (78 : 11+/- 1 : 11 +/-1) are consistent with the solar system values (79.0:10.0:11.0), following Anders & Grevesse 1989). According to new calculations of evolutionary models of 3 solar mass and 5 solar mass asymptotic giant branch (AGB) stars, these ratios and the previously measured N, O and Si isotopic ratios imply that the central star had an initial mass 3 solar mass (less than or equal to M(sub *, ini) less than 5 solar mass and has already experienced many 3rd dredge-up events. From this, it can be predicted that the Al-26/Al-27 isotopics ratio lies between 0.01 and 0.08; in fact, the value derived in the case that U234433 arises from (26)AlF is Al-26/Al-27 = 0.04. The identification of the (25)MgNC and (26)MgNC lines was made possible by ab-initio quantum mechanical calculations of the molecule geometrical structure. It was confirmed through millimeter-wave laboratory measurements. The quantum mechanical calculations are briefly described and the laboratory results presented in some detail. The rotation constants B, D, H and the spin-rotation constant gamma of (25)MgNC and (26)MgNC are determined from a fit of laboratory and astronomical data.

Guelin, M.↗

NASA NTRS1998

Modeling and Simulation of Semiconductor Quantum Well Structures and Lasers

In this talk I will cover two aspects of modeling and simulation efforts at NASA Ames Research Center. In the quantum well structure simulation, we typically start from the quantum mechanical calculation of the quantum well structures for the confined/and unconfined eigen states and functions. A bandstructure calculation of the k*p type is then performed for the confined valence states. This information is then used to computer the optical gain and refractive index of the quantum well structures by solving the linearized multiband semiconductor Bloch equations with the many-body interactions included. In our laser simulation, we typically solve the envelope equations for the laser field in space-time domain, coupled with a reduced set of material equations using the microscopic calculation of the first step. Finally I will show some examples of both aspects of simulation and modeling.

Ning, Cun-Zheng↗

NASA NTRS1998

Molecular Processes in Comets

The research focused on molecular hydrogen and its response to ultraviolet radiation, photoelectron impact excitation and X-ray radiation and on the interpretation of the ultraviolet spectra of the Jupiter dayglow and auroras. A systematic effort was made to obtain reliable rate coefficients for rovibrational energy transfer of H2, particularly in collisions with hydrogen atoms. We carried out elaborate quantum-mechanical calculations of the scattering of H and H2 on what had been characterized as a reliable potential energy surface of the H3 molecular system. These calculations took into account reactive channels and rate coefficients for ortho-para transitions were obtained. Quantal calculations are too complex to be applied to all the possible rovibrational transitions and we turned to a semi-classical method. With it we calculated rate coefficients for transitions, reactive and non-reactive, for all the rovibrational levels. We carried out the calculations for three of the available H3 potential energy surfaces. We discovered an unexpected sensitivity of the rate coefficients for the non-reactive channels to the potential energy surface. This discovery stimulated more thorough investigations of the potential energy surface elsewhere and to the construction of a new surface. We have used it in further semi-classical calculations in work that will shortly be 2 completed and which, together with new quantum-mechanical calculations should comprise a set of reliable rate coefficients that can be used in discussions of H2 on the Jovian planets. We carried out a detailed study of the Jovian ultraviolet dayglow. There has been a long-running argument about the dayglow on Jupiter. There are two sources of excitation: fluorescence and photoelectron impact excitation. It had been argued that a third source "the electron glow" was needed to bring theory and observation into agreement. We believe we have shown conclusively that the third source is unnecessary. We have achieved a close quantitative agreement between the predicted spectrum arising from fluorescence and photoelectrons and the measured spectrum. We also demonstrated a method by which the presence of HD could be established observationary. Similar calculations were carried out of the ultraviolet spectra of the Jovian auroras. We again found close agreement. Indeed, the agreement was so detailed we were able to derive the temperature of the atmosphere. We found, contrary to the standard model of the time, a high temperature between 400 K and 600 K and established the presence of a significant temperature gradient. A large temperature gradient was indeed found by direct sampling with the Jupiter probe.

Dalgarno, A.↗

DOE OSTI2020

A First–Principles–Based Sub–Lattice Formalism for Predicting Off–Stoichiometry in Materials for Solar Thermochemical Applications: The Example of Ceria

Theoretical models that reliably can predict off-stoichiometry in materials via accurate descriptions of underlying thermodynamics are crucial for energy applications. For example, transition-metal and rare-earth oxides that can tolerate a large number of oxygen vacancies, such as CeO 2 and doped CeO 2 , can split water and carbon dioxide via a two-step, oxide-based solar thermochemical (STC) cycle. The search for new STC materials with a performance superior to that of state-of-the-art CeO 2 can benefit from predictions accurately describing the thermodynamics of oxygen vacancies. The sub-lattice formalism, a common tool used to fit experimental data and build temperature-composition phase diagrams, can be useful in this context. Here, sub-lattice models are derived solely from zero-temperature quantum mechanics calculations to estimate fairly accurate temperature- and oxygen-partial-pressure-dependent off-stoichiometries in CeO 2 and Zr-doped CeO 2 . Physical motivations for deriving some of the “excess” sub-lattice model parameters directly from quantum mechanical calculations, instead of fitting to minimize deviations from experimental and/or theoretical data, are identified. As a result, important limitations and approximations of the approach used are specified and extensions to multi-cation oxides are also suggested to help identify novel candidates for water and carbon dioxide splitting and related applications.

08 HYDROGEN↗

DOE OSTI2024

Toward transferable empirical valence bonds: Making classical force fields reactive

The empirical valence bond technique allows classical force fields to model reactive processes. However, parametrization from experimental data or quantum mechanical calculations is required for each reaction present in the simulation. We show that the parameters present in the empirical valence bond method can be predicted using a neural network model and the SMILES strings describing a reaction. This removes the need for quantum calculations in the parametrization of the empirical valence bond technique. In doing so, we have taken the first steps toward defining a new procedure for enabling reactive atomistic simulations. This procedure would allow researchers to use existing classical force fields for reactive simulations, without performing additional quantum mechanical calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Protein3D: Enabling analysis and extraction of metal‐containing sites from the Protein Data Bank with molSimplify

Abstract Metalloenzymes catalyze a wide range of chemical transformations, with the active site residues playing a key role in modulating chemical reactivity and selectivity. Unlike smaller synthetic catalysts, a metalloenzyme active site is embedded in a larger protein, which makes interrogation of electronic properties and geometric features with quantum mechanical calculations challenging. Here we implement the ability to fetch crystallographic structures from the Protein Data Bank and analyze the metal binding sites in the program molSimplify. We show the usefulness of the newly created protein3D class to extract the local environment around non‐heme iron enzymes containing a two histidine motif and prepare 372 structures for quantum mechanical calculations. Our implementation of protein3D serves to expand the range of systems molSimplify can be used to analyze and will enable high‐throughput study of metal‐containing active sites in proteins.

Edholm, Freya↗

DOE OSTI2021

Importance of Engineered and Learned Molecular Representations in Predicting Organic Reactivity, Selectivity, and Chemical Properties

Machine-readable chemical structure representations are foundational in all attempts to harness machine learning for the prediction of reactivities, selectivities, and chemical properties directly from molecular structure. The featurization of discrete chemical structures into a continuous vector space is a critical phase undertaken before model selection, and the development of new ways to quantitatively encode molecules is an active area of research. Here, we highlight the application and suitability of different representations, from expert-guided “engineered” descriptors to automatically “learned” features, in different prediction tasks relevant to organic and organometallic chemistry, where differing amounts of training data are available. These tasks include statistical models of stereo- and enantioselectivity, thermochemistry, and kinetics developed using experimental and quantum chemical data. The use of expert-guided molecular descriptors provides an opportunity to incorporate chemical knowledge, domain expertise, and physical constraints into statistical modeling. In applications to stereoselective organic and organometallic catalysis, where data sets may be relatively small and 3D-geometries and conformations play an important role, mechanistically informed features can be used successfully to obtain predictive statistical models that are also chemically interpretable. We provide an overview of several recent applications of this approach to obtain quantitative models for reactivity and selectivity, where topological descriptors, quantum mechanical calculations of electronic and steric properties, along with conformational ensembles, all feature as essential ingredients of the molecular representations used. Alternatively, more flexible, general-purpose molecular representations such as attributed molecular graphs can be used with machine learning approaches to learn the complex relationship between a structure and prediction target. This approach has the potential to out-perform more traditional representation methods such as “hand-crafted” molecular descriptors, particularly as data set sizes grow. One area where this is particularly relevant is in the use of large sets of quantum mechanical data to train quantitative structure–property relationships. A general approach toward curating useful data sets and training highly accurate graph neural network models is discussed in the context of organic bond dissociation enthalpies, where this strategy outperforms regression using precomputed descriptors. Finally, we describe how graph neural network predictions can be incorporated into mechanistically informed statistical models of chemical reactivity and selectivity. Once trained, this approach avoids the expensive computational overhead associated with quantum mechanical calculations, while maintaining chemical interpretability. We illustrate examples for which fast predictions of bond dissociation enthalpy and of the identities of radicals formed through cleavage of a molecule’s weakest bond are used in simple physical models of site-selectivity and reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

An experimental and chemical kinetic modeling study of 4-butoxyheptane combustion

Here, the combustion kinetics of a novel oxygenated bioblendstock for diesel, 4-butoxyheptane (4-BH), was investigated experimentally using a flow reactor and a heated, high-pressure shock tube. The flow reactor experiments employed oxygen as the oxidizer and helium as the diluent with oxidation conducted at atmospheric pressure and 10 bar for temperatures from 400 to 1000 K at 20-K intervals. The fuel, oxidizer, and diluent flow rates were varied at different temperatures to maintain a constant initial fuel mole fraction of 1000 ppm, with stoichiometric equivalence ratio, and a residence time of 2.0 s. The reacted gas was fed to two separate GC systems that could qualitatively and quantitatively detect product species. Additionally, real fuel-air ignition delay time (IDT) data were collected using a heated, high-pressure shock-tube facility. Fuel lean (φ = 0.5) and stoichiometric (φ = 1.0) mixtures were investigated at 10 atm as well as at 30 atm for the fuel lean case for temperatures between 847 and 1259 K. A detailed chemical kinetics mechanism was developed to model the product distribution from the flow reactor and IDTs from the shock tube. The proposed model was able to predict the double NTC behavior in flow reactor experiments reasonably well. Model predictions at low temperatures were observed to be highly sensitive to the rate constants of ketohydroperoxide (KHP) decomposition in the case of the OOH group in α position which were modeled based on existing literature studies on ethers. It was noted that in the absence of theoretical or experimental studies, the rate constants for KHP decomposition used in the literature were empirically set. Additional studies are required to address the gap in model prediction obtained in this study and to reduce the uncertainty in kinetics models for ether oxidation. Predicted product concentrations and IDTs showed some quantitative agreement with experimental data, but the overall reactivity of the IDTs is underpredicted. Additionally, significant deviation is observed for the IDT results at 10 atm for the stoichiometric case with minor deviations for the other cases. The reaction pathways to the missing products were then further analyzed theoretically through quantum-mechanical calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Melting curves of ice polymorphs in the vicinity of the liquid–liquid critical point

The possible existence of a liquid–liquid critical point in deeply supercooled water has been a subject of debate due to the challenges associated with providing definitive experimental evidence. The pioneering work by Mishima and Stanley [Nature 392, 164–168 (1998)] sought to shed light on this problem by studying the melting curves of different ice polymorphs and their metastable continuation in the vicinity of the expected liquid–liquid transition and its associated critical point. Based on the continuous or discontinuous changes in the slope of the melting curves, Mishima [Phys. Rev. Lett. 85, 334 (2000)] suggested that the liquid–liquid critical point lies between the melting curves of ice III and ice V. Herein we explore this conjecture using molecular dynamics simulations with a machine learning model based on ab initio quantum-mechanical calculations. We study the melting curves of ices III, IV, V, VI, and XIII and find that all of them are supercritical and do not intersect the liquid–liquid transition locus. We also find a pronounced, yet continuous, change in the slope of the melting lines upon crossing of the liquid locus of maximum compressibility. Finally, we analyze the literature in light of our findings and conclude that the scenario in which the melting curves are supercritical is favored by the most recent computational and experimental evidence. Although the preponderance of evidence is consistent with the existence of a second critical point in water, the behavior of ice polymorph melting lines does not provide strong evidence in support of this viewpoint, according to our calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Toward Addressing the Challenge to Predict the Heat Capacities of RDX and HMX Energetic Materials

Availability of heat capacity as function of pressure and temperature is an essential prerequisite for development of a computational multiscale strategy capable to address the evolution of microstructure and energy release in advanced high energy density materials. In the case of 1,3,5-trinitro-1,3,5-triazinane (RDX) and 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX) systems as two of the most studied energetic materials, there are substantial gaps in experimental data, with available heat capacities values distributed only in a region close to standard ambient conditions. In this study we demonstrate how these major experimental limitations can be addressed in the case of the RDX and HMX systems based on the combined use of classical and quantum mechanical calculations. We show that by considering ideal gas properties evaluated using quantum mechanical methods, and residual properties obtained from molecular simulations using fully flexible atomistic force field models, excellent agreement can be obtained for the predicted heat capacities to the most recent experimental values. An important advantage of the current computational methodology is that it allows evaluation of both constant-volume and constant-pressure heat capacities for a broad interval of temperatures and pressures, which encompasses solid and liquid phases conditions. In the case of the solid α and γ phases of RDX and the β phase of HMX, the predicted results follow closely both the available experimental data at standard ambient conditions and the results obtained using density functional theory calculations at high pressures, a regime where experimental data are not available. A perspective to expand the current methodology is also discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Multi-level parallelization of quantum-chemical calculations

Here, strategies for multiple-level parallelizations of quantum-mechanical calculations are discussed, with an emphasis on using groups of workers for performing parallel tasks. These parallel programming models can be used for a variety ab initio quantum chemistry approaches, including the fragment molecular orbital method and replica-exchange molecular dynamics. Strategies for efficient load balancing on problems of increasing granularity are introduced and discussed. A four-level parallelization is developed based on a multi-level hierarchical grouping, and a high parallel efficiency is achieved on the Theta supercomputer using 131 072 OpenMP threads.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Partially polaron-transformed quantum master equation for exciton and charge transport dynamics

Polaron-transformed quantum master equation (PQME) offers a unified framework to describe the dynamics of quantum systems in both limits of weak and strong couplings to environmental degrees of freedom. Thus, the PQME serves as an efficient method to describe charge and exciton transfer/transport dynamics for a broad range of parameters in condensed or complex environments. However, in some cases, the polaron transformation (PT) being employed in the formulation invokes an over-relaxation of slow modes and results in premature suppression of important coherence terms. A formal framework to address this issue is developed in the present work by employing a partial PT that has smaller weights for low frequency bath modes. In this work, it is shown that a closed form expression of a second order time-local PQME including all the inhomogeneous terms can be derived for a general form of partial PT, although more complicated than that for the full PT. All the expressions needed for numerical calculation are derived in detail. Applications to a model of a two-level system coupled to a bath of harmonic oscillators, with test calculations focused on those due to homogeneous relaxation terms, demonstrate the feasibility and the utility of the present approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

A deep potential model with long-range electrostatic interactions

Machine learning models for the potential energy of multi-atomic systems, such as the deep potential (DP) model, make molecular simulations with the accuracy of quantum mechanical density functional theory possible at a cost only moderately higher than that of empirical force fields. However, the majority of these models lack explicit long-range interactions and fail to describe properties that derive from the Coulombic tail of the forces. To overcome this limitation, we extend the DP model by approximating the long-range electrostatic interaction between ions (nuclei + core electrons) and valence electrons with that of distributions of spherical Gaussian charges located at ionic and electronic sites. The latter are rigorously defined in terms of the centers of the maximally localized Wannier distributions, whose dependence on the local atomic environment is modeled accurately by a deep neural network. In the DP long-range (DPLR) model, the electrostatic energy of the Gaussian charge system is added to short-range interactions that are represented as in the standard DP model. The resulting potential energy surface is smooth and possesses analytical forces and virial. Missing effects in the standard DP scheme are recovered, improving on accuracy and predictive power. By including long-range electrostatics, DPLR correctly extrapolates to large systems the potential energy surface learned from quantum mechanical calculations on smaller systems. We illustrate the approach with three examples: the potential energy profile of the water dimer, the free energy of interaction of a water molecule with a liquid water slab, and the phonon dispersion curves of the NaCl crystal.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Influence of uranyl complexation on the reaction kinetics of the dodecane radical cation with used nuclear fuel extraction ligands (TBP, DEHBA, and DEHiBA)

Specialized extractant ligands – such as tri-butyl phosphate (TBP), N,N-di-(2-ethylhexyl)butyramide (DEHBA), and N,N-di-2-ethylhexylisobutryamide (DEHiBA) – have been developed for the recovery of uranium from used nuclear fuel by reprocessing solvent extraction technologies. These ligands must function in the presence of an intense multi-component radiation field, and thus it is critical that their radiolytic behaviour be thoroughly evaluated. This is especially true for their metal complexes, where there is negligible information on the influence of complexation on radiolytic reactivity, despite the prevalence of metal complexes in used nuclear fuel reprocessing solvent systems. Here we present a kinetic investigation into the effect of uranyl (UO 2 2+ ) complexation on the reaction kinetics of the dodecane radical cation (RH˙ + ) with TBP, DEHBA, and DEHiBA. Complexation had negligible effect on the reaction of RH˙ + with TBP, for which a second-order rate coefficient (k) of (1.3 ± 0.1) × 10 10 M -1 s -1 was measured. For DEHBA and DEHiBA, UO 2 2+ complexation afforded an increase in their respective rate coefficients: k(RH˙ + + [UO 2 (NO 3 ) 2 (DEHBA) 2 ]) = (2.5 ± 0.1) × 10 10 M -1 s -1 and k(RH˙ + + [UO 2 (NO 3 ) 2 (DEHiBA) 2 ]) = (1.6 ± 0.1) × 10 10 M -1 s -1 . This enhancement with complexation is indicative of an alternative RH˙ + reaction pathway, which is more readily accessible for [UO 2 (NO 3 ) 2 (DEHBA) 2 ] as it exhibited a much larger kinetic enhancement than [UO 2 (NO 3 ) 2 (DEHiBA) 2 ], 2.6× vs. 1.4×, respectively. Complementary quantum mechanical calculations suggests that the difference in reaction kinetic enhancement between TBP and DEHBA/DEHiBA is attributed to a combination of reaction pathway (electron/hole transfer vs. proton transfer) energetics and electron density distribution, wherein attendant nitrate counter anions effectively ‘shield’ TBP from RH˙ + electron transfer processes.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2023

Fission with Exotic Nuclei (Full Technical Report)

Despite its importance for stockpile stewardship or nuclear forensics, data on fission is fragmentary: most experiments have only been performed on stable actinide nuclei and are often incomplete, and theoretical simulations often contain many parameters hard to constrain, which results in large uncertainties. Consequently, nuclear libraries have large gaps for important isotopes. The goal of this project was to prepare to take advantage of the unprecedented yields of radioactive isotopes at the upcoming DOE Facility for Rare Ion Beams and to leverage recent progress in the field of machine learning to develop a comprehensive program of fission studies that could address some of the most pressing problems in nuclear fission over the next several decades. Our project leveraged synergies between experimental nuclear physics, nuclear theory, and data science expertise at LLNL. On the experimental front, our main objective was to develop in-house expertise for inverse kinematics reactions with relativistic beams as well as to field and test new detectors to perform correlated measurements of fission properties. On the theoretical side, the objective was to develop a novel, high-fidelity and scalable approach of fissionfragment calculations based on emulating computationally expensive, quantum-mechanical calculations of nuclear properties with deep neural networks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

In situ x-ray absorption investigations of a heterogenized molecular catalyst and its interaction with a carbon nanotube support

A highly active heterogenized molecular CO 2 reduction catalyst on a conductive carbon support is investigated to identify if its improved catalytic activity can be attributed to strong electronic interactions between catalyst and support. The molecular structure and electronic character of a [Re +1 (tBu-bpy)(CO) 3 Cl] (tBu-bpy = 4,4'-tert-butyl-2,2'-bipyridine) catalyst deposited on multiwalled carbon nanotubes are characterized using Re L 3 -edge x-ray absorption spectroscopy under electrochemical conditions and compared to the homogeneous catalyst. The Re oxidation state is characterized from the near-edge absorption region, while structural changes of the catalyst are assessed from the extended x-ray absorption fine structure under reducing conditions. Chloride ligand dissociation and a Re-centered reduction are both observed under applied reducing potential. The results confirm weak coupling of [Re(tBu-bpy)(CO) 3 Cl] with the support, since the supported catalyst exhibits the same oxidation changes as the homogeneous case. However, these results do not preclude strong interactions between a reduced catalyst intermediate and the support, preliminarily investigated here using quantum mechanical calculations. Thus, our results suggest that complicated linkage schemes and strong electronic interactions with the initial catalyst species are not required to improve the activity of heterogenized molecular catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Computational investigation of water glasses using machine-learning potentials

The molecular origins of water’s anomalous properties have long been a subject of scientific inquiry. The liquid–liquid phase transition hypothesis, which posits the existence of distinct low-density and high-density liquid states separated by a first-order phase transition terminating at a critical point, has gained increasing experimental and computational support and offers a thermodynamically consistent framework for many of water’s anomalies. However, experimental challenges in avoiding crystallization near the postulated liquid–liquid critical point have focused attention to water’s canonical glassy states: low-density and high-density amorphous ice. Here, we use two Deep Potential machine-learning models, trained on the Strongly Constrained and Appropriately Normed density functional and the highly accurate Many-Body Polarizable potential, to conduct an investigation of water’s glassy phenomenology based on quantum mechanical calculations. Despite not being explicitly trained on amorphous ices, both models accurately capture the structure and transformation of the water glasses, including their interconversion along different thermodynamic paths. Isobaric quenching of liquid water at various pressures generates a continuum of intermediate amorphous ices and density fluctuations increase near the liquid–liquid critical pressure. The glass transition temperatures of the amorphous ices produced at different pressures exhibit two distinct branches, corresponding to low-density and high-density amorphous ice behaviors, consistent with experiment and the liquid–liquid transition hypothesis. Extrapolating transformation pressures from isothermal compressions to experimental compression rates brings our simulations into excellent agreement with data. Our findings demonstrate that machine-learning potentials trained on equilibrium phases can effectively model nonequilibrium glassy behavior and pave the way for studying long-timescale, out-of-equilibrium processes with quantum mechanical accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗