Epitaxial Alkali Antimonide Photocathode Growth and Fabrication
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43 PARTICLE ACCELERATORS↗
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Fundamentals of SrCoO 3-δ Based Oxygen Deficient Perovskites as Cathodes for Solid Oxide Fuel Cells
The local structure and oxygen stoichiometry in oxide systems have a profound impact on oxygen electrocatalysis encountered in metal-air batteries and solid oxide fuel cells (SOFCs). However, this knowledge is often obtained under conditions different from the real working conditions of the material, resulting in misinterpretation and misunderstanding. This PhD dissertation aims to obtain the structure and oxygen-stoichiometry information of a class of perovskite oxides under their real working conditions in solid oxide fuel cells. Several perovskite oxides were selected for the study: Sr 0.9 Y 0.1 CoO 3-δ (SYC10), Sr 0.9 Y 0.3 CoO 3-δ (SYC30), SrCo 0.9 Nb 0.1 O 3-δ (SCN10) and SrCo 0.9 Ta0.1O 3-δ (SCT10). The local crystal structure and oxygen stoichiometry of these materials were systematically characterized with in-situ neutron diffraction (ND). The oxygen stoichiometry was also measured by thermogravimetric analysis (TGA) and iodometric titration methods. To establish the correlation among structure, oxygen stoichiometry and oxygen reduction reaction (ORR) activity, high temperature electrochemical impedance spectroscopy, oxygen permeation and single cell testing were also performed. In chapter 2, SYC10 is described to have a more symmetrical structure and $V_o^{··}$ distribution, and higher $V_o^{··}$ concentration than SYC30. Molecular orbital energy analysis based on the local structure of the ORR-active Co1-polyhedra indicates SYC30 has a higher Fermi level relative to O-2p energy level in the active Co1-polyhedra, and thus a higher motional enthalpy for $V_o^{··}$ migration. However, the ORR activity of Y-doped SrCoO 3-δ (SCO) are found uncompetitive with other popular catalysts. In chapter 3 and 4, systematic structural studies are presented for Nb and Ta-doped SCO, namely SCN10 and SCT10, respectively. The methodology of unrevealing the structure-activity relationships in chapter 2 is also found applicable to SYC10, SCN10 and SCT10 as presented in chapter 5. The electrochemical tests indicate that SCT10 is the best catalyst due to its excellent thermal and electrochemical stability. In chapter 6, SCT10 is evaluated in a real solid oxide fuel cell in the form of nanoscaled SCT10 layer coating on the commercial (La 0.6 Sr 0.4 ) 0.95 Co 0.2 Fe 0.8 O 3-δ (LSCF). The bilayer structured cathode shows excellent properties of coarsening-resistant, Sr-segregation-free and high ORR-activity.
Yang, Tianrang↗
Deep Learning Potential For Investigation of Chemical Conversion of CO2 at Air-Reactive Deep Eutectic Solvent Interface
Capturing CO2 from air is urgent to battle against the climate change. Traditional CO2 capture by alkaline solution or aqueous amine has high regeneration cost, equipment corrosion, and amine leakage. Deep eutectic solvents (DESs) are promising alternatives with low corrosion, non-toxicity, and biodegradable nature. Functionalized DESs can capture and convert CO2 at low partial pressures. Developing reactive DESs for efficient CO2 capture needs a foundational understanding of the reaction-transport coupling of CO2 at the air-DES interface. In this study, we develop a deep learning potential (DLP) to investigate the absorption and reaction of CO2 at the air-DES interface (DES: 1-ethyl-3-methylimidazolium 2-cyanopyrrolide ([Emim][2-CNpyr]) and ethylene glycol (EG)). The DLP model allows us to simulate chemical reactions at a lower computational cost with ab initio accuracy. By analyzing reaction free energy surfaces, molecular interactions among CO2, DES components and reaction products, and transport of CO2 through the interface, we identify three main reaction pathways of CO2 at the interface: forming carboxylate with [Emim], carbamate with [2-CNpyr], and carbonate with EG. The mechanistic understanding of CO2 chemisorption at the interface will facilitate the development of novel direct air capture technology using DESs.
Nguyen, Manh Tien↗
Plastic Parallel Pathways Platform - 4P Model
Global momentum is building towards a circular economy capable of keeping plastics in use and out of waste streams. Given that 79% of all plastic produced since 1950 has accumulated in landfills or the natural environment,rapid implementation of various end-of-life (EoL) management technologies will be needed to reach this target. However, it can be challenging to develop an effective plastic EoL strategy when the available options - chemical or molecular recycling, energy recovery, upcycling, downcycling, closed-loop (plastic-to-plastic) or open-loop (plastic-to-x) recycling, among others - can generate products ranging from low-grade to virgin-quality plastic and from fuels to value-added chemicals. We present a flexible material flow model capable of analyzing the effects of both plastic-to-plastic and plastic-to-x EoL management strategies on the U.S. PET economy. This Plastic Parallel Pathways Platform (4P) assesses the environmental impacts, costs, and circularity of a PET system in which waste is managed through six potential EoL pathways: landfill, incineration with energy recovery, pyrolysis to fuel oil, upcycling to glass fiber reinforced plastic (GFRP), mechanical recycling to low-grade PET, and chemical recycling (glycolysis) to bottle-grade PET. We compare the pathways across multiple metrics using multi-criteria decision analysis (MCDA) and then use a brute force algorithm to predict an optimal combination of EoL pathways to minimize greenhouse gas (GHG) emissions and costs and maximize circularity. This work highlights the need to implement a diverse portfolio of EoL strategies in parallel to enable a PET economy that meets environmental, economic, and circularity requirements simultaneously.
downcycling↗
CAFQA: A Classical Simulation Bootstrap for Variational Quantum Algorithms
Classical computing plays a critical role in the advancement of quantum frontiers in the NISQ era. In this spirit, this work uses classical simulation to bootstrap Variational Quantum Algorithms (VQAs). VQAs rely upon the iterative optimization of a parameterized unitary circuit (ansatz) with respect to an objective function. Since quantum machines are noisy and expensive resources, it is imperative to classically choose the VQA ansatz initial parameters to be as close to optimal as possible to improve VQA accuracy and accelerate their convergence on today’s devices. This work tackles the problem of finding a good ansatz initialization, by proposing CAFQA, a Clifford Ansatz For Quantum Accuracy. The CAFQA ansatz is a hardware-efficient circuit built with only Clifford gates. In this ansatz, the parameters for the tunable gates are chosen by searching efficiently through the Clifford parameter space via classical simulation. The resulting initial states always equal or outperform traditional classical initialization (e.g., Hartree-Fock), and enable high-accuracy VQA estimations. CAFQA is well-suited to classical computation because: a) Clifford-only quantum circuits can be exactly simulated classically in polynomial time, and b) the discrete Clifford space is searched efficiently via Bayesian Optimization. For the Variational Quantum Eigensolver (VQE) task of molecular ground state energy estimation (up to 18 qubits), CAFQA’s Clifford Ansatz achieves a mean accuracy of nearly 99% and recovers as much as 99.99% of the molecular correlation energy that is lost in Hartree-Fock initialization. CAFQA achieves mean accuracy improvements of 6.4x and 56.8x, over the state-of-the-art, on different metrics. Here, the scalability of the approach allows for preliminary ground state energy estimation of the challenging chromium dimer (Cr2) molecule. With CAFQA’s high-accuracy initialization, the convergence of VQAs is shown to accelerate by 2.5x, even for small molecules. Furthermore, preliminary exploration of allowing a limited number of non-Clifford (T) gates in the CAFQA framework, shows that as much as 99.9% of the correlation energy can be recovered at bond lengths for which Clifford-only CAFQA accuracy is relatively limited, while remaining classically simulable.
bayesian optimization↗
Combining Force Fields and Neural Networks for an Accurate Representation of Chemically Diverse Molecular Interactions
A key goal of molecular modeling is the accurate reproduction of the true quantum mechanical potential energy of arbitrary molecular ensembles with a tractable classical approximation. The challenges are that analytical expressions found in general purpose force fields struggle to faithfully represent the intermolecular quantum potential energy surface at close distances and in strong interaction regimes; that the more accurate neural network approximations do not capture crucial physics concepts, e.g., nonadditive inductive contributions and application of electric fields; and that the ultra-accurate narrowly targeted models have difficulty generalizing to the entire chemical space. We therefore designed a hybrid wide-coverage intermolecular interaction model consisting of an analytically polarizable force field combined with a short-range neural network correction for the total intermolecular interaction energy. Here, we describe the methodology and apply the model to accurately determine the properties of water, the free energy of solvation of neutral and charged molecules, and the binding free energy of ligands to proteins. The correction is subtyped for distinct chemical species to match the underlying force field, to segment and reduce the amount of quantum training data, and to increase accuracy and computational speed. For the systems considered, the hybrid ab initio parametrized Hamiltonian reproduces the two-body dimer quantum mechanics (QM) energies to within 0.03 kcal/mol and the nonadditive many-molecule contributions to within 2%. Simulations of molecular systems using this interaction model run at speeds of several nanoseconds per day.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Shadow energy functionals and potentials in Born–Oppenheimer molecular dynamics
In Born–Oppenheimer molecular dynamics (BOMD) simulations based on the density functional theory (DFT), the potential energy and the interatomic forces are calculated from an electronic ground state density that is determined by an iterative self-consistent field optimization procedure, which, in practice, never is fully converged. The calculated energies and forces are, therefore, only approximate, which may lead to an unphysical energy drift and instabilities. Here, we discuss an alternative shadow BOMD approach that is based on backward error analysis. Instead of calculating approximate solutions for an underlying exact regular Born–Oppenheimer potential, we do the opposite. Instead, we calculate the exact electron density, energies, and forces, but for an underlying approximate shadow Born–Oppenheimer potential energy surface. In this way, the calculated forces are conservative with respect to the approximate shadow potential and generate accurate molecular trajectories with long-term energy stabilities. We show how such shadow Born–Oppenheimer potentials can be constructed at different levels of accuracy as a function of the integration time step, δt, from the constrained minimization of a sequence of systematically improvable, but approximate, shadow energy density functionals. For each energy functional, there is a corresponding ground state Born–Oppenheimer potential. These pairs of shadow energy functionals and potentials are higher-level generalizations of the original “zeroth-level” shadow energy functionals and potentials used in extended Lagrangian BOMD. The proposed shadow energy functionals and potentials are useful only within this extended dynamical framework, where also the electronic degrees of freedom are propagated as dynamical field variables together with the atomic positions and velocities. The theory is quite general and can be applied to MD simulations using approximate DFT, Hartree–Fock, or semi-empirical methods, as well as to coarse-grained flexible charge models.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Probing High-Pressure Structural Evolution in Polyurea with In Situ Energy-Dispersive X-ray Diffraction and Molecular Dynamics Simulations
Polyurea, an elastomer with a phase-segregated microstructure, has been proven as an effective coating in defense applications. To gain a more complete understanding of the high-pressure atomic-level morphology of these phases and to validate molecular dynamics (MD) simulations, multi-angle energy-dispersive X-ray diffraction experiments were performed in situ up to pressures of ~6 GPa at room temperature. Structure factors were obtained and compared to MD simulations with an average error of less than 5% between major peak positions. The first sharp diffraction peak shifted from 4.56 Å to lower d-spacing with pressure, indicating compression between hard segments. This was further supported by the behavior of a peak at ~3.86 Å from the pair distribution function (PDF), suspected to represent π-stacking and separation between soft segments. Compression within the hard segments themselves is minimal as low-r peaks in the PDF are not greatly affected by pressure.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Converting Second‐Order Saddle Points to Transition States: New Principles for the Design of 4π Photoswitches
Abstract Molecular photoswitches have demonstrated potential for storing solar energy at the molecular level, with power densities comparable to commercial batteries and hydroelectric energy storage. However, development of efficient photoswitches is hindered by limitations in cyclability and optical properties of existing materials. We here demonstrate that certain limitations in photoswitches based on electrocyclizations stem from the issue of controlling competition between Woodward‐Hoffmann allowed and forbidden pathways. Our approach moves beyond the traditional view of activation barriers and reveals that second‐order saddle points are crucial in dictating the competition between disrotatory and conrotatory pathways. These insights suggest new opportunities to manipulate the competition between these pathways through geometric constraints, fundamentally altering the connectivity of the potential energy surface. Our study also emphasizes the necessity of multi‐reference methods and the need to conduct higher‐dimensional explorations for competing pathways beyond photoswitch design.
Chemistry↗
Dissipation Pathways in a Photosynthetic Complex
Determining how energy flows within and between molecules is crucial for understanding chemical reactions, material properties, and even vital processes such as photosynthesis. While the general principles of energy transfer are well established, elucidating the specific molecular pathways by which energy is funneled remains challenging, as it requires tracking energy flow in complex molecular environments. Here, we demonstrate how photon excitation energy is partially dissipated in the light-harvesting Fenna–Matthews–Olson (FMO) complex, mediating the excitation energy transfer from light-harvesting chlorosomes to the photosynthetic reaction center in green sulfur bacteria. Specifically, we isolate the contribution of the protein and specific vibrational modes of the pigment molecules to the energy dynamics. For this, we introduce an efficient computational implementation of a recently proposed theory of dissipation pathways for open quantum systems, based on second-order perturbation theory in the electronic couplings. Using it and a state-of-the-art FMO model with highly structured and chromophore-specific spectral densities, we demonstrate that energy dissipation is dominated by low-frequency modes (<800 cm –1 ) as their energy range is near-resonance with the energy gaps between electronic states of the pigments. We identify the most important modes for dissipation to be in-plane breathing modes (∼200 cm –1 ) of the bacteriochlorophylls in the complex. Conversely, far-detuned intramolecular vibrations with higher frequencies (>800 cm –1 ) play no role in dissipation. Interestingly, the FMO complex first needs to borrow energy from the environment to release excess photonic energy, indicating that the energy exchange between the system and thermal environment is not strictly unidirectional in time but involves a transient thermally activated step. Beyond their fundamental value, these insights can guide the development of artificial light-harvesting devices and, more broadly, engineer environments for chemical and quantum control tasks.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Trapping Ca + inside a molecular cavity: computational study of the potential energy surfaces for Ca + -[ n ]cycloparaphenylene, n = 5–12
Ion trap quantum computing utilizes electronic states of atomic ions such as Ca + to encode information on to a qubit. To explore the fundamental properties of Ca + inside molecular cavities, we describe here a computational study of Ca + bound inside neutral [n]-cycloparaphenylenes (n = 5–12), often referred to as “nanohoops”. This ab initio study characterizes optimized structures, harmonic vibrational frequencies, potential energy surfaces, and ion molecular orbital distortion as functions of increasing nanohoop size. Here the results of this work provide a first step in guiding experimental studies of the spectroscopy of these ion-molecular cavity complexes.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Combining molecular beam epitaxy and low-energy electron microscopy with in situ magnetic susceptibility measurements within an integrated ultrahigh vacuum system
Quantum two-dimensional materials, including ultrathin superconducting films, are of great current research interest. These films are typically fabricated under ultra-high vacuum (UHV) conditions and are sensitive to the environment—prone to oxidation and contamination when exposed to the atmosphere. This hampers the study of their intrinsic properties by standard ex situ techniques. Here, we present a variable-temperature mutual inductance probe system integrated under UHV with molecular beam epitaxy (MBE) synthesis and low-energy electron microscopy, enabling nondestructive in situ characterization of superconducting thin films. The system employs a reflection-type configuration and reaches a low temperature (∼4 K) using a high-cooling-power, vibration-isolated cryocooler. In conclusion, we demonstrate the system performance by measuring the superconducting critical temperature in a copper-oxide thin film.
2D materials↗
Poly(cyclosilane) Connectivity Tunes Optical Absorbance
We report herein the influence of skeletal connectivity on the conformation-dependent optical properties of cyclosilane homo- and copolymers. 1,3-Linked cyclosilanes were bathochromically shifted by 20 nm in solution relative to 1,4-linked cyclosilanes, an effect reproduced by quantum chemical calculations on oligomeric model systems. Polysilane optical properties are conformation-dependent, and 1,3-linked cyclosilanes were hypothesized to adopt a favorable conformation unavailable to 1,4-linked cyclosilanes constrained to an endocyclic gauche conformation. Copolymerization of the isomeric cyclosilanes 1,3Si 6 and 1,4Si 6 afforded linear statistical copolymers, as characterized by 1 H and 29 Si NMR spectroscopies. The distinct connectivity of each comonomer was found to give rise to tunable absorption spectra, where the position of the absorption band systematically increased with the increased corporation of 1,3Si 6 . Computational studies pointed to conformation-dependent changes in orbital symmetry in shifting the most intense transition from the low-energy highest occupied molecular orbital (HOMO) → lowest unoccupied molecular orbital (LUMO) transition to a higher-energy HOMO → LUMO + n transition. Here, the results of these studies demonstrate for the first time the role of silicon skeletal connectivity in controlling conformation and optoelectronic properties and provide new insight into the structure-based design of solution-processable silicon-based polymeric materials.
36 MATERIALS SCIENCE↗
Energy based fracture initiation criterion for strain-crystallizing rubber-like materials with pre-existing cracks
Fracture prediction is indispensable for polymers, like rubbers, which have a broad range of applications mainly due to their high extensibility. The phenomenon known as strain-induced crystallization further contributes to the fracture toughness of certain rubbers. Here in this study, a criterion based on internal bond energy, incorporating the effects of crystallization, is proposed to predict fracture initiation in rubber-like materials with pre-existing cracks. First, a multi-scale mechanical model is developed for characterizing the behavior of rubber when subjected to both uniaxial and biaxial deformation states. At the microscale, both the amorphous and crystalline chain segments are modeled as elastic in order to consider the energy contribution by the molecular bond distortions. This internal energy is considered along with the entropic and crystalline free energy for each chain. In the chain model, the effects of loading condition and the relative orientation of a chain on its crystallinity are taken into account. At the macroscopic scale, an existing crystallinity distribution function is adapted and a mixed finite element formulation with an augmented Lagrangian multiplier is utilized to impose the incompressibility constraint. A non-affine maximal advance path constraint based homogenization model is utilized for bridging the two scales. Its potential to account for anisotropy in the stretched network compels the model to be preferable due to its physical significance, for the purpose of fracture modeling. The rigidity of the crystallites is accounted for by proposing a crystallite distortion energy in addition to the critical bond dissociation energy, for fracture initiation to occur. The model is validated by comparison with existing experimental results for both crystallizing and non-crystallizing rubbers. In addition to its potential to predict the material behavior when subjected to uniaxial and biaxial loading, the capability of the model to quantitatively estimate the effect of crystallization on fracture initiation is also verified.
36 MATERIALS SCIENCE↗
Energy conversion and storage via photoinduced polarization change in non-ferroelectric molecular [CoGa] crystals
To alleviate the energy and environmental crisis, in the last decades, energy harvesting by utilizing optical control has emerged as a promising solution. Here we report a polar crystal that exhibits photoenergy conversion and energy storage upon light irradiation. The polar crystal consists of dinuclear [CoGa] molecules, which are oriented in a uniform direction inside the crystal lattice. Irradiation with green light induces a directional intramolecular electron transfer from the ligand to a low-spin Co III centre, and the resultant light-induced high-spin Co II excited state is trapped at low temperature, realizing energy storage. Additionally, electric current release is observed during relaxation from the trapped light-induced metastable state to the ground state, because the intramolecular electron transfer in the relaxation process is accompanied with macroscopic polarization switching at the single-crystal level. It demonstrates that energy storage and conversion to electrical energy is realized in the [CoGa] crystals, which is different from typical polar pyroelectric compounds that exhibit the conversion of thermal energy into electricity.
25 ENERGY STORAGE↗
Simulation guided molecular design of hydrofluoroether solvent for high energy batteries
The study introduces novel asymmetric hydrofluoroether (HFE) designs, uncovers solvation-property relationships, and leverages molecular dynamics modeling for high-performance electrolytes in advanced lithium batteries.
25 ENERGY STORAGE↗
Characterization of light-induced potentials in the strong-field dissociation of O 2 +
In this work, we investigate theoretically the imprints of light-induced potentials (LIPs) on the dissociation dynamics of O 2 + molecular ions, as observable in angle-resolved fragment kinetic-energy-release (KER) spectra. Following the vibrational and rotational dynamics of the initial pump-laser-excited cationic nuclear wave packet, while accounting for the dipole coupling between the O 2 + ( a 4 Π u ) and O 2 + ( f 4 Π g ) electronic states in 800-nm 40-fs probe-laser pulses with peak intensities between 10 13 and 10 14 W / cm 2 , we calculate angle-resolved KER spectra which reveal characteristic energy- and angle-dependent fringe structures. These fringes shift downward in energy as the molecular alignment angle θ relative to the probe-pulse polarization direction increases from 0 to π / 2 . The angle-dependent shifts in the KER fringes increase for larger probe-pulse peak intensities and follow the angle and light-wave-intensity dependence of the vibrational spectrum in the associated Floquet bond-hardening well, which is a manifestation of transient O 2 + nuclear-probability trapping in the LIP during dissociation. By examining the rovibrational dynamics of the dissociating molecular cation near the light-induced conical intersection (LICI) in the cationic LIP surface at θ = π / 2 , we identify related angle-dependent structures in the KER spectra, suggesting a means for assessing the significance of LICIs in molecular dissociation pathways.
74 ATOMIC AND MOLECULAR PHYSICS↗
Hydrogen as Part of a 100% Clean Energy System: Exploring Its Decarbonization Roles
Today's energy system uses a variety of fuels and energy carriers in molecular forms, such as coal, oil, and natural gas, each contributing to CO2 emissions (Figure 1). As solar and wind levels grow and the energy system becomes more electrified, fossil molecular fuels will contribute a progressively smaller fraction of overall energy. As shown in Figure 2, hydroelectric storage and molecules, such as coal and natural gas, provide substantial storage and dispatch functionality today that will become increasingly critical for electricity operation and stability. Emerging low-carbon gases, such as hydrogen, can support the efficient integration of renewables in the transition from today's energy system to one that is 100% clean from a carbon emissions perspective.
clean energy system↗