A never-ending search for the truth: Thermodynamics in the uncertain era of the internet

Frenkel, Michael

doi:10.1016/j.jct.2014.12.016

Cited by 9 publications

(7 citation statements)

References 92 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The past few years have witnessed an intense renewal of interest for force-field refinement procedures. This is in large part due to a number of computational and methodological advances − that have enabled an increased accuracy, automation, and throughput of these procedures, including more powerful processors and coprocessors (graphics processing units (GPUs) − and field-programmable gate arrays (FPGAs) − ), faster algorithms and improved simulation methodologies ( e.g ., for nonbonded interactions − and free-energy calculations − ), more accessible experimental data − (online literature and databases), and faster QM calculation codes. − In turn, these progresses have increased the practical usefulness of force-field-based simulations, in particular in the context of material and drug design, where approaches relying on atomistic MD simulations can nowadays keep pace with the fast time scale of industrial and pharmaceutical product development. − ,− …”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Systematic Optimization of a Fragment-Based Force Field against Experimental Pure-Liquid Properties Considering Large Compound Families: Application to Saturated Haloalkanes

Oliveira

Andrey

Rieder

et al. 2020

J. Chem. Theory Comput.

100

View full text Add to dashboard Cite

Direct optimization against experimental condensedphase properties concerning small organic molecules still represents the most reliable way to calibrate the empirical parameters of a force field. However, compared to a corresponding calibration against quantum-mechanical (QM) calculations concerning isolated molecules, this approach is typically very tedious and time-consuming. The present article describes an integrated scheme for the automated refinement of force-field parameters against experimental condensedphase data, considering entire classes of organic molecules constructed using a fragment library via combinatorial isomer enumeration. The main steps of the scheme, referred to as CombiFF, are as follows: (i) definition of a molecule family; (ii) combinatorial enumeration of all isomers; (iii) query for experimental data; (iv) automatic construction of the molecular topologies by fragment assembly; and (v) iterative refinement of the force-field parameters considering the entire family. As a first application, CombiFF is used here to design a GROMOS-compatible united-atom force field for the saturated acyclic haloalkane family. This force field relies on an electronegativity-equalization scheme for the atomic partial charges and involves no specific terms for σ-holes and halogen bonding. A total of 749 experimental liquid densities ρ liq and vaporization enthalpies ΔH vap concerning 486 haloalkanes are considered for calibration and validation. The resulting root-mean-square deviations from experiment are 49.8 (27.6) kg•m −3 for ρ liq and 2.7 (1.8) kJ•mol −1 for ΔH vap for the calibration (validation) set. The values are lower for the validation set which contains larger molecules (stronger influence of purely aliphatic interactions). The trends in the optimized parameters along the halogen series and across the compound family are in line with chemical intuition based on considerations related to size, polarizability, softness, electronegativity, induction, and hyperconjugation. This observation is particularly remarkable considering that the force-field calibration did not involve any QM calculation. Once the time-consuming task of target-data selection/curation has been performed, the optimization of a force field only takes a few days. As a result, CombiFF enables an easy assessment of the consequences of functional-form decisions on the accuracy of a force field at an optimal level of parametrization.

show abstract

Section: Introductionmentioning

confidence: 99%

“…Here also, the approaches are too diverse to be listed exhaustively. They include in particular setup/simulation/analysis workflows, ,− as well as experimental databases and data-extraction procedures. − …”

Section: Introductionmentioning

confidence: 99%

Systematic Optimization of a Fragment-Based Force Field against Experimental Pure-Liquid Properties Considering Large Compound Families: Application to Saturated Haloalkanes

Oliveira

Andrey

Rieder

et al. 2020

J. Chem. Theory Comput.

100

View full text Add to dashboard Cite

show abstract

“…4,5 A broad variety of data validation methods have been developed, tested, and incorporated into the ThermoData Engine software (TDE) 6 for thermophysical properties of pure compounds, binary mixtures, and ternary mixtures 7−9 as a part of the implementation of the dynamic data evaluation concept 10 within a framework of a Global Information System in Thermodynamics. 1,11 Volumetric properties are a major category of thermophysicalproperty information within the context of any dynamic data evaluation such as the TDE evaluation for thermophysical and thermochemical properties, along with phase boundary property information and energy-related property information. 10 Each category can be evaluated systematically in order to accumulate understanding about the behavior of a chemical system in thermodynamic space.…”

Section: Introductionmentioning

confidence: 99%

“…It is estimated that about 30 % of the articles reporting new thermophysical-property data obtained from direct measurements contain erroneous information in numerical values, metadata associated with these values, or their uncertainties. 2 As this information propagates through the community's data infrastructure, it can lead (and has led) to significant damage 1 as it is fed into data-driven analyses and is used as the basis for new correlations and prediction methodologies.…”

Section: Introductionmentioning

confidence: 99%

“…The doubling every 10 years of published experimental thermophysical property data provides significant societal benefits, but the associated rate of published erroneous data is alarming. It is estimated that about 30 % of the articles reporting new thermophysical-property data obtained from direct measurements contain erroneous information in numerical values, metadata associated with these values, or their uncertainties .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Representation and Validation of Liquid Densities for Pure Compounds and Mixtures

Diky

O’Connell

Abildskov³

et al. 2015

J. Chem. Eng. Data

Self Cite

View full text Add to dashboard Cite

Reliable correlation and prediction of liquid densities are important for designing chemical processes at normal and elevated pressures. A corresponding-states model from molecular theory was extended to yield a robust method for quality testing of experimental data that also provides predicted values at unmeasured conditions. The model has been shown to successfully represent and validate the pressure and temperature dependence of liquid densities greater than 1.5 of the critical density for pure compounds, binary mixtures, and ternary mixtures from the triple to critical temperatures at pressures up to 10 6 kPa. The systems include the full range of organic compounds, including complex solutions, and ionic liquids. Minimal data are required for making predictions.

show abstract

Chemical space deconstruction-based dynamic model ensemble architecture for molecular property prediction

Wen,

Nan,

Zhang

et al. 2024

Chemical Engineering Science

View full text Add to dashboard Cite

A never-ending search for the truth: Thermodynamics in the uncertain era of the internet

Cited by 9 publications

References 92 publications

Systematic Optimization of a Fragment-Based Force Field against Experimental Pure-Liquid Properties Considering Large Compound Families: Application to Saturated Haloalkanes

Systematic Optimization of a Fragment-Based Force Field against Experimental Pure-Liquid Properties Considering Large Compound Families: Application to Saturated Haloalkanes

Representation and Validation of Liquid Densities for Pure Compounds and Mixtures

Chemical space deconstruction-based dynamic model ensemble architecture for molecular property prediction

Contact Info

Product

Resources

About