Daniel P. Tabor
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View article: Synthesis and Persistence Length Study of Defect-Free and Non-Aggregated Conjugated Ladder Polymers
Synthesis and Persistence Length Study of Defect-Free and Non-Aggregated Conjugated Ladder Polymers Open
View article: Selective Deuteration of Neopentyl Glycol and its Effect on the Plastic Crystal Transformation
Selective Deuteration of Neopentyl Glycol and its Effect on the Plastic Crystal Transformation Open
Transitions between rotationally ordered and disordered states in globular small molecules are associated with large entropy changes, and thus, hold promise as solid-state barocaloric refrigerants. However, the relationships between elemen…
View article: Vibrational Couplings in the NO Stretch Region in Diiron Trinitrosyl Complexes
Vibrational Couplings in the NO Stretch Region in Diiron Trinitrosyl Complexes Open
Two-dimensional infrared spectroscopy offers unique capabilities for probing vibrational coupling in complex metal--ligand systems. In this paper, we combine two-dimensional infrared spectroscopy with vibrational perturbation theory to inv…
View article: Synthesis and Conformation of Defect-Free, Strained, and Non-Aggregated Conjugated Ladder Polymers
Synthesis and Conformation of Defect-Free, Strained, and Non-Aggregated Conjugated Ladder Polymers Open
A fundamental understanding of the solution properties of conjugated ladder polymers (CLPs) is essential for advancing their design, synthesis, and solution processing toward high-performance optoelectronic applications. Nevertheless, eluc…
View article: Low-Data Machine Learning Models for Predicting Thermodynamic Properties of Solid-Solid Phase Transformations in Plastic Crystals
Low-Data Machine Learning Models for Predicting Thermodynamic Properties of Solid-Solid Phase Transformations in Plastic Crystals Open
Plastic crystals, many of which are globular small molecules that exhibit transitions between rotationally ordered and rotationally disordered states, represent an important subclass of colossal barocaloric effect materials. The known set …
View article: Shadow Molecular Dynamics with a Machine Learned Flexible Charge Potential
Shadow Molecular Dynamics with a Machine Learned Flexible Charge Potential Open
We present an extended Lagrangian shadow molecular dynamics scheme with an interatomic Born-Oppenheimer potential determined by the relaxed atomic charges of a second-order charge equilibration model. To parameterize the charge equilibrati…
View article: Low-data machine learning models for predicting thermodynamic properties of solid–solid phase transformations in plastic crystals
Low-data machine learning models for predicting thermodynamic properties of solid–solid phase transformations in plastic crystals Open
This study develops low-data machine learning models to predict thermodynamic properties of solid–solid transitions in plastic crystals, identifying key physical descriptors of these materials in sparse-data regimes.
View article: HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware
HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware Open
In order to characterize and benchmark computational hardware, software, and algorithms, it is essential to have many problem instances on-hand. This is no less true for quantum computation, where a large collection of real-world problem i…
View article: Structural, Ionic, and Electronic Properties of Solid-State Phthalimide-Containing Polymers for All-Organic Batteries
Structural, Ionic, and Electronic Properties of Solid-State Phthalimide-Containing Polymers for All-Organic Batteries Open
Redox-active polymers serving as the active materials in solid-state electrodes offer a promising path toward realizing all-organic batteries. While both cathodic and anodic redox-active polymers are needed, the diversity of the available …
View article: Kinetics of the plastic crystal transition in neopentyl glycol
Kinetics of the plastic crystal transition in neopentyl glycol Open
The thermal hysteresis exhibited in plastic crystal compounds greatly reduces their cyclic efficiency, limiting their potential for replacing current environmentally harmful refrigerants. A mechanistic understanding of the origins of this …
View article: Structural, Ionic, and Electronic Properties of Solid-State Phthalimide-Containing Polymers for All-Organic Batteries
Structural, Ionic, and Electronic Properties of Solid-State Phthalimide-Containing Polymers for All-Organic Batteries Open
Redox-active polymers serving as the active materials in solid-state electrodes offer a promising path towards realizing all-organic batteries. While both cathodic and an- odic redox-active polymers are needed, the diversity of the availab…
View article: Charge Transfer in Spatially Defined Organic Radical Polymers
Charge Transfer in Spatially Defined Organic Radical Polymers Open
Charge transfer in nonconjugated redox-active polymers is influenced by redox site proximity and polymer flexibility, but it is challenging to observe these effects independently. In this work, spatially defined radical-containing polymers…
View article: HamLib: A Library of Hamiltonians for Benchmarking Quantum Algorithms and Hardware
HamLib: A Library of Hamiltonians for Benchmarking Quantum Algorithms and Hardware Open
For a considerable time, large datasets containing problem instances have proven valuable for analyzing computer hardware, software, and algorithms. One notable example of the value of large datasets is ImageNet [1], a vast repository of i…
View article: Generative Organic Electronic Molecular Design via Reinforcement Learning Integration with Quantum Chemistry: Tuning Singlet and Triplet Energy Levels
Generative Organic Electronic Molecular Design via Reinforcement Learning Integration with Quantum Chemistry: Tuning Singlet and Triplet Energy Levels Open
Generative molecular design strategies have emerged as promising alternatives to trial-and-error approaches for exploring and optimizing within large chemical spaces. To date, generative models with reinforcement learning approaches have f…
View article: Generative Organic Electronic Molecular Design via Reinforcement Learning Integration with Quantum Chemistry: Tuning Singlet and Triplet Energy Energy Levels
Generative Organic Electronic Molecular Design via Reinforcement Learning Integration with Quantum Chemistry: Tuning Singlet and Triplet Energy Energy Levels Open
Generative molecular design strategies have emerged as promising alternatives to trial-and-error approaches for exploring and optimizing within large chemical spaces. To date, generative models with reinforcement learning approaches have f…
View article: LEARNING MOLECULAR HAMILTONIANS DIRECTLY FROM SPECTRA
LEARNING MOLECULAR HAMILTONIANS DIRECTLY FROM SPECTRA Open
Assigning and interpreting the spectroscopy of large molecules and clusters often requires a manual trial-and-error approach.Here, we present our efforts to automate spectroscopic assignments through a data-driven approach.We will consider…
View article: HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware
HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware Open
In order to characterize and benchmark computational hardware, software, and algorithms, it is essential to have many problem instances on-hand. This is no less true for quantum computation, where a large collection of real-world problem i…
View article: Reorganization Energy Predictions with Graph Neural Networks Informed by Low-Cost Conformers
Reorganization Energy Predictions with Graph Neural Networks Informed by Low-Cost Conformers Open
A critical bottleneck for the design of high-conductivity organic materials is finding molecules with low reorganization energy. To enable high-throughput virtual screening campaigns for many types of organic electronic materials, a fast r…
View article: Data-Driven Models for Predicting Intrinsically Disordered Protein Polymer Physics Directly from Composition or Sequence
Data-Driven Models for Predicting Intrinsically Disordered Protein Polymer Physics Directly from Composition or Sequence Open
The molecular-level understanding of intrinsically disordered proteins is challenging due to experimental characterization difficulties. Computational understanding of IDPs also requires fundamental advances, as the leading tools for predi…
View article: Data-driven models for predicting intrinsically disordered protein polymer physics directly from composition or sequence
Data-driven models for predicting intrinsically disordered protein polymer physics directly from composition or sequence Open
A new representation for intrinsically disordered protein sequences is developed for usage in both classical and deep learning machine learning models.
View article: Generative organic electronic molecular design informed by quantum chemistry
Generative organic electronic molecular design informed by quantum chemistry Open
Reinforcement learning methods, coupled with quantum chemistry, discover a diverse set of organic singlet fission and triplet–triplet annihilation candidates.
View article: Accelerating Organic Electronic Materials Design with Low-Cost, Robust Molecular Reorganization Energy Predictions
Accelerating Organic Electronic Materials Design with Low-Cost, Robust Molecular Reorganization Energy Predictions Open
A critical bottleneck for the design of high-conductivity organic materials is finding molecules with low reorganization energy. The development of low-cost machine-learning-based models for calculating the reorganization energy has proven…
View article: INVERSE INFRARED SPECTROSCOPY WITH BAYESIAN METHODS
INVERSE INFRARED SPECTROSCOPY WITH BAYESIAN METHODS Open
View article: Solvent-Mediated Charge Transfer Dynamics of a Model Brown Carbon Aerosol Chromophore: Photophysics of 1-Phenylpyrrole Induced by Water Solvation
Solvent-Mediated Charge Transfer Dynamics of a Model Brown Carbon Aerosol Chromophore: Photophysics of 1-Phenylpyrrole Induced by Water Solvation Open
Nitrogen heterocycles are known to be important light-absorbing chromophores in a relatively new class of aerosols, commonly referred to as ‘brown carbon’ (BrC) aerosols. Due to their significant absorption and spectral overlap with the so…
View article: Discovery of lead low-potential radical candidates for organic radical polymer batteries with machine-learning-assisted virtual screening
Discovery of lead low-potential radical candidates for organic radical polymer batteries with machine-learning-assisted virtual screening Open
The discovery and development of new low reduction potential molecules that also have fast charge transfer kinetics is necessary for the further development of organic redox-active polymers in practical battery applications. Theoretical me…
View article: Robust chain aggregation of low-entropy rigid ladder polymers in solution
Robust chain aggregation of low-entropy rigid ladder polymers in solution Open
Conjugated ladder polymer forms highly robust, temperature-insensitive aggregation in the solution due to low entropy change of rigid backbone, which is promising for highly robust intermolecular interaction at high temperature.
View article: Discovery of lead low-potential radical candidates for organic radical polymer batteries with machine-learning-assisted virtual screening
Discovery of lead low-potential radical candidates for organic radical polymer batteries with machine-learning-assisted virtual screening Open
Lead candidate radicals for use in radical polymer batteries are discovered by virtual screening with low computational footprint, chemistry-informed machine learning methods.
View article: Near- and long-term quantum algorithmic approaches for vibrational spectroscopy
Near- and long-term quantum algorithmic approaches for vibrational spectroscopy Open
Determining the vibrational structure of a molecule is central to fundamental\napplications in several areas, from atmospheric science to catalysis, fuel\ncombustion modeling, biochemical imaging, and astrochemistry. However, when\nsignifi…
View article: MOLECULAR FRAGMENT MACHINE LEARNING TRAINING TECHNIQUES TO PREDICT CLUSTER ENERGETICS AND FREQUENCIES IN BROWN CARBON AEROSOL CLUSTERS
MOLECULAR FRAGMENT MACHINE LEARNING TRAINING TECHNIQUES TO PREDICT CLUSTER ENERGETICS AND FREQUENCIES IN BROWN CARBON AEROSOL CLUSTERS Open
Density functional theory (DFT) has become a popular method for computational work involving larger molecular systems as it provides accuracy that rivals ab initio methods while lowering computational cost. Nevertheless, computational cost…
View article: Interface chemistry of an amide electrolyte for highly reversible lithium metal batteries
Interface chemistry of an amide electrolyte for highly reversible lithium metal batteries Open
Metallic lithium is a promising anode to increase the energy density of rechargeable lithium batteries. Despite extensive efforts, detrimental reactivity of lithium metal with electrolytes and uncontrolled dendrite growth remain challengin…