Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “density functional theory development”

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.

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

At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Alloying multiple halide perovskites on the same sublattice in search of stability and target band gaps

Single-component halide perovskites (HPs) rarely satisfy all the necessary criteria for optoelectronic applications, such as achieving an optimal band gap while maintaining high chemical and structural stability. Alloying halide perovskites has emerged as a promising strategy, not only to enhance stability but also to fine-tune their electronic and optical properties. In this work, we explore multiple degrees of freedom in alloy design, considering different substitution sublattices sites (A, B, or X in ABX3 perovskites), various chemical species (isovalent and hetero-valent elements), and multi-component compositions on a given sublattice. Using first-principles calculations based on density functional theory (DFT), we investigate how compositional variations influence the electronic (band gap) and structural properties (mixing enthalpy) of HP alloys. Our approach employs the polymorphous cell model, allowing full local relaxation which breaks local symmetry while preserving global cubic symmetry—an essential framework for accurately modeling HPs. Our results reveal that X-site mixing (halogen substitution) primarily affects the valence band maximum, allowing target band gap engineering. Additionally, variations in halogen radii introduce internal strain through octahedral distortions, influencing the mixing enthalpy. A-site substitution, while not directly contributing to the band edge states, modifies structural stability via volume effects, indirectly impacting the band gap. B-site alloying plays a dominant role in band gap modulation, leading to either positive or negative band gap bowing. Specifically, isovalent B-site mixing (Sn–Pb) induces strong positive bowing, where the alloy band gap is smaller than the average gap of parent compounds, whereas hetero-valent mixing (Cd–Pb) results in pronounced negative bowing. As an aside, we investigate the competition between the excess energy of disordered alloys vs. that of long-range ordered double perovskites of the same compositions, seeking examples of ordered phases emerging from disordered alloys. Furthermore, our findings provide fundamental insights into the electronic and structural behavior of HP alloys, offering valuable design principles for the development of stable and efficient materials for next-generation photovoltaic and optoelectronic devices.

14 SOLAR ENERGY↗
DOE OSTI2025

Development of Parameters for the Particle Size Distribution of TATB

Laser light scattering (LLS), manual counting of scanning electron microscopy (SEM) images, and reduction of SEM images using ImageJ (open source program) to determine Feret (caliper) diameters were applied to determine particle size distribution (PSD) of four preparations of 1,3,5‐triamino‐2,4,6‐trinitrobenzene (TATB) and yttria‐stabilized zirconia (YSZ), an SEM certified standard. Mie theory was used to reduce the LLS data. The spherical nature of the YSZ made it a good candidate for LLS. Variations in n , the refractive index, and iκ, the imaginary component, produced very little change in the PSD. However, changing the carrier liquid from H 2 O to a 40% aqueous sucrose solution, thereby changing the carrier refractive index, n 0 , substantially affected the PSD. The Mie complex refractive indices for the YSZ were n = 2.200, iκ = 0.100, with a 40% aqueous sucrose solution, n 0 = 1.400. The triclinic crystal structure of TATB made refractive index determinations more difficult, so a study was conducted varying Mie parameters and comparing them to the same data reduced using the Fraunhofer theory. Changing the n and κ parameters produced PSD with a small concentration of particles less than 1 µm in size or none in this range. SEM images, Feret data, manual counting, and Fraunhofer data reduction indicate particles less than 1 µm are probably < 5% in concentration. The final selection of Mie parameters for TATB was n = 2.283, iκ = 0.1, and suspension medium, n 0 = 1.330. Finally, computations, using density functional theory produced similar parameters.

Feret diameter↗
DOE OSTI2026

First-principles investigation of structure-property relationships in stable and metastable MXenes

Understanding the structure–property relationships in layered transition-metal carbides or nitrides, known as MXenes, is of critical importance for their rational design, synthesis, and application. However, the vast chemical and structural diversity of MXenes, stemming from their wide range of M and X elements, surface terminations, and different atomic coordination environments, makes it challenging to clearly understand these structure–property relationships. Here, in this work, we perform first-principles density functional theory (DFT) calculations and molecular dynamics (MD) simulations to comprehensively investigate the stability and a variety of physical properties of MXenes with different coordination environments. Using Ti- and Mo-based carbide MXenes as model systems, energetic calculations reveal that Ti-based MXenes are most stable in octahedral coordination, whereas Mo-based MXenes preferentially adopt prismatic coordination. This fundamental difference in preferred atomic coordination gives rise to markedly distinct properties between these two systems as a function of the fraction of octahedral and prismatic sites. For instance, the in-plane stiffness of Ti-based MXenes increases as octahedral coordination becomes dominant, but it decreases in the Mo-based MXenes under the same conditions. Additional stability analyses based on mechanical, lattice-dynamical, and temperature-dependent thermodynamic properties demonstrate that many metastable MXenes not only satisfy the strict stability criteria but can also undergo phase transitions among different structures and even become stabilized at elevated temperatures. Although surface terminations, such as F and O atoms, do not alter the energetic ordering or the overall stiffness trends among stable and metastable MXenes, they influence other material properties. For instance, O termination can induce semiconducting behavior in both stable and metastable Ti 2 ⁢CO 2 MXenes. This study significantly advances the fundamental understanding of structure–property relationships in MXenes and provides valuable guidance for developing coordination-based design principles to precisely engineer MXenes with improved properties.

Oyeniran, Noah [University of Alabama, Tuscaloosa,↗
DOE OSTI2021

Developing Accelerated Test Protocols and Tuning Microstructures of the Common Materials to Improve Robustness, Reliability, and Endurance of SOFC Cells

This work is built on our prior work where we found that phase transformation in praseodymium nickelates, e.g. Pr 2 NiO 4 (PNO) and (Pr 1-x Nd x ) 2 NiO 4 (PNNO), can be electrochemically driven, and is substantially faster when compared to thermal annealing studies. The first task aims at an attempt to further accelerate the phase transformation in the oxygen electrode by alternating the current input in the cells, which lead to the development of accelerated test protocols (ATPs). ATPs showed up to 60x faster phase transformation and up to 10x faster performance degradation in (Pr 0.50 Nd 0.50 ) 2 NiO 4 electrodes, when compared to long-term operation under constant current density. Furthermore, the phase stable Nd 2 NiO 4 and (La 0.6 Sr 0.4 )(Co 0.8 Fe 0.2 )O 3 (LSCF6482) electrodes were tested in full cells under ATPs, and showed up to 10x faster performance degradation within 1,100 hours in a comparison with long-term thermal annealing studies and electrochemical operation under constant current density. The second task aims at the quantification of the contributions of cell components to the total impedance of a solid oxide fuel cell (SOFC) using electrochemical impedance spectroscopy (EIS) and distribution of relaxation times (DRT). Specifically, the role of gas composition at both anode and cathode was systematically studied, aiming at deconvoluting, identifying and quantifying the contributions of different electrode processes. This was achieved by first tuning the partial pressure of H 2 at the anode and subsequently varying the partial pressure of O 2 at the cathode. The results suggest that, while DRT offers a viable way of deconvoluting different times distributions, additional attention is needed before assigning a peak to a specific electrode process due to the significant overlap of the contributions from the cathode and the anode. Density function theory studies show that both Pr-vacancies and O-defects play a key role on the activity and stability for nickelates towards oxygen reduction reaction. The resident O-interstitials and oxygen ions in the PrO layer form peroxide (O 2 2- ) nearby Pr vacancies. The O 2 2- limits oxygen-ion transport due to the required additional energy to break its O-O bond. We further calculated the formation and segregation energies for different Ln ions (La, Pr, Nd, Pm, Sm, Gd, Tb, Dy, and Ho) in PNO and CeO 2 (111) surfaces. In addition to Nd, Pm and La are suggested as potential dopants in PNO to enhance it stability without decomposition due to their more negative formation energies, lower diffusion energies, and positive separation energies.

01 COAL, LIGNITE, AND PEAT↗
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

Defects go green: using defects in nanomaterials for renewable energy and environmental sustainability

Induction of point defects in nanomaterials can bestow upon them entirely new physics or augment their pre-existing physical properties, thereby expanding their potential use in green energy technology. Predicting structure-property relationships for defects a priori is challenging, and developing methods for precise control of defect type, density, or structural distribution during synthesis is an even more formidable task. Hence, tuning the defect structure to tailor nanomaterials for enhanced device performance remains an underutilized tool in materials design. We review here the state of nanomaterial design through the lens of computational prediction of defect properties for green energy technology, and synthesis methods to control defect formation for optimal performance. We illustrate the efficacy of defect-focused approaches for refining nanomaterial physics by describing several specific applications where these techniques hold potential. Most notably, we focus on quantum dots for reabsorption-free solar windows and net-zero emission buildings, oxide cathodes for high energy density lithium-ion batteries and electric vehicles, and transition metal dichalcogenides for electrocatalytic green hydrogen production and carbon-free fuels.

14 SOLAR ENERGY↗
NASA NTRS2010

Thermal Performance of Cryogenic Multilayer Insulation at Various Layer Spacings

Multilayer insulation (MLI) has been shown to be the best performing cryogenic insulation system at high vacuum (less that 10 (exp 3) torr), and is widely used on spaceflight vehicles. Over the past 50 years, many investigations into MLI have yielded a general understanding of the many variables that are associated with MLI. MLI has been shown to be a function of variables such as warm boundary temperature, the number of reflector layers, and the spacer material in between reflectors, the interstitial gas pressure and the interstitial gas. Since the conduction between reflectors increases with the thickness of the spacer material, yet the radiation heat transfer is inversely proportional to the number of layers, it stands to reason that the thermal performance of MLI is a function of the number of layers per thickness, or layer density. Empirical equations that were derived based on some of the early tests showed that the conduction term was proportional to the layer density to a power. This power depended on the material combination and was determined by empirical test data. Many authors have graphically shown such optimal layer density, but none have provided any data at such low densities, or any method of determining this density. Keller, Cunnington, and Glassford showed MLI thermal performance as a function of layer density of high layer densities, but they didn't show a minimal layer density or any data below the supposed optimal layer density. However, it was recently discovered that by manipulating the derived empirical equations and taking a derivative with respect to layer density yields a solution for on optimal layer density. Various manufacturers have begun manufacturing MLI at densities below the optimal density. They began this based on the theory that increasing the distance between layers lowered the conductive heat transfer and they had no limitations on volume. By modifying the circumference of these blankets, the layer density can easily be varied. The simplest method of determining the thermal performance of MLI at cryogenic temperature is by boil-off calorimetry. Several blankets were procured and tested at various layer densities at the Cryogenics Test Laboratory at Kennedy Space Center. The densities that the blankets were tested over covered a wide range of layer densities including the analytical minimum. Several of the blankets were tested at the same insulation thickness while changing the layer density (thus a different number of reflector layers). Optimizing the layer density of multilayer insulation systems for heat transfer would remove a layer density from the complex method of designing such insulation systems. Additional testing was performed at various warm boundary temperatures and pressures. The testing and analysis was performed to simplify the analysis of cryogenic thermal insulation systems. This research was funded by the National Aeronautics and Space Administration's Exploration Technology Development Program's Cryogenic Fluid Management Project

Johnson, Wesley Louis↗
DOE OSTI2023

Transferring a Molecular Foundation Model for Polymer Property Predictions

Transformer-based large language models have remarkable potential to accelerate design optimization for applications such as drug development and material discovery. Self-supervised pretraining of transformer models requires large-scale data sets, which are often sparsely populated in topical areas such as polymer science. Further, state-of-the-art approaches for polymers conduct data augmentation to generate additional samples but unavoidably incur extra computational costs. In contrast, large-scale open-source data sets are available for small molecules and provide a potential solution to data scarcity through transfer learning. In this work, we show that using transformers pretrained on small molecules and fine-tuned on polymer properties achieves comparable accuracy to those trained on augmented polymer data sets for a series of benchmark prediction tasks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Size-Dependent Energy of Ni Nanoparticles on Graphene Films on Ni(111) and Adhesion Energetics by Adsorption Calorimetry

The use of carbon supports for late transition-metal nanoparticle catalysts has grown substantially in recent years due to efforts to develop electrocatalysts for clean energy applications and catalysts for new aqueous-phase biomass-related conversions and due to the evolution of new carbon materials with unique properties (e.g., graphene, carbon nanotubes, and so forth). However, much less is known about the bonding energetics of catalytic metal nanoparticles on carbon supports in comparison with oxide supports, which are more common for thermal catalysis. Here, we report the growth morphology and heats of adsorption of Ni vapor deposited onto graphene/Ni(111) at 300 K and 100 K using metal vapor single-crystal adsorption calorimetry and He + low-energy ion scattering (LEIS). These results provide the Ni chemical potential versus particle size, and the Ni/graphene adhesion energy. LEIS intensities suggest that Ni grows as flat-topped face-centered cubic islands with a nearly constant thickness of ~1.5 nm when deposited at 300 K. At 100 K, Ni grows as smaller nanoparticles, well modeled as hemispherical hexagonal close-packed nanoparticles with a density of ~2 × 10 16 particles/m 2 . The Ni chemical potential as a function of average particle diameter in the 0.5 to 4 nm range at 100 K was determined from the heats of Ni gas adsorption. Further, by fitting the measured chemical potential as a function of diameter, we determined an adhesion energy of 3.6 J/m 2 for large Ni particles on graphene/Ni(111). This adhesion energy is in good agreement with previous scanning tunneling microscopy and density functional theory investigations of Ni/graphene/Ni(111).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Noise and error analysis and optimization in particle-based kinetic plasma simulations

In this paper we analyze the noise in macro-particle methods used in plasma physics and fluid dynamics, leading to approaches for minimizing the total error, focusing on electrostatic models in one dimension. We begin by describing kernel density estimation for continuous values of the spatial variable x, expressing the kernel in a form in which its shape and width are represented separately. The covariance matrix of the noise in the density is computed, first for uniform true density. The bandwidth of the covariance matrix C(x,y) is related to the width of the kernel. A feature that stands out is the presence of constant negative terms in the elements of the covariance matrix both on and off-diagonal. These negative correlations are related to the fact that the total number of particles is fixed at each time step; they also lead to the property ∫C(x,y)dy = 0. We investigate the effect of these negative correlations on the electric field computed by Gauss's law, finding that the noise in the electric field is related to a process called the Ornstein-Uhlenbeck bridge, leading to a covariance matrix of the electric field with variance significantly reduced relative to that of a Brownian process. For non-constant density, p(x), still with continuous x, we analyze the total error in the density estimation and discuss it in terms of bias-variance optimization (BVO). For some characteristic length l, determined by the density and its second derivative, and kernel width h, having too few particles within h leads to too much variance; for h that is large relative to l, there is too much smoothing of the density. The optimum between these two limits is found by BVO. For kernels of the same width, it is shown that this optimum (minimum) is weakly sensitive to the kernel shape. Next, we repeat the analysis for x discretized on a grid. In this case the charge deposition rule is determined by a particle shape. An important property to be respected in the discrete system is the exact preservation of total charge on the grid; this property is necessary to ensure that the electric field is equal at both ends, consistent with periodic boundary conditions. We find that if the particle shapes satisfy a partition of unity property, the particle charge deposited on the grid is conserved exactly. Further, if the particle shape is expressed as the convolution of a kernel with another kernel that satisfies the partition of unity, then the particle shape obeys the partition of unity. This property holds for kernels of arbitrary width, including widths that are not integer multiples of the grid spacing. Furthermore, we show results relaxing the approximations used to do BVO optimization analytically, by doing numerical computations of the total error as a function of the kernel width, on a grid in x. The comparison between numerical and analytical results shows good agreement over a range of particle shapes. We discuss the practical implications of our results, including the criteria for design and implementation of computationally efficient particle shapes that take advantage of the developed theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Graphene-supported single atom catalysts for high performance lithium-oxygen batteries

The optimal choice of d-block metals in single atom catalysts (SACs) is crucial for designing efficient electrocatalysts for activating the Oxygen reduction reaction (ORR)/ Oxygen evolution reaction (OER) in lithiumoxygen batteries (LOBs). Herein, we used the Quantum Mechanics methods to understand the origin of reactivity for a series of 16 d-block metals supported on nitrogen-doped graphene as SACs for ORR and OER in LOBs. Based on the Gibbs free energy calculations, we found that among the 16 SACs investigated, Zn-SAC exhibits the highest electrochemical activity with the lowest overpotential of 0.17 V. Here we then used machine learning (ML) to develop an intrinsic descriptor, phi, that correlates the catalytic activity with electronic and chemical properties of the catalytic centers at the M-N 4 active site on graphene surface. We established a linear relationship between phi and the catalytic activity that provides guidance for designing efficient SACs for electrocatalysis in LOBs. To validate these predictions, we report electrochemical measurements showing that Zn-SAC exhibits an ultra-stable cyclability with reduced overpotentials over Mo-SAC and nitrogen-doped graphene (NG), confirming our theoretical prediction. This fundamental work provides a deep understanding on the rational design of efficient SACs for OER/ ORR in LOBs.

25 ENERGY STORAGE↗
DOE OSTI2024

Efficient Mixed-Precision Matrix Factorization of the Inverse Overlap Matrix in Electronic Structure Calculations with AI-Hardware and GPUs

In recent years, a new kind of accelerated hardware has gained popularity in the artificial intelligence (AI) community which enables extremely high-performance tensor contractions in reduced precision for deep neural network calculations. In this article, we exploit Nvidia Tensor cores, a prototypical example of such AI-hardware, to develop a mixed precision approach for computing a dense matrix factorization of the inverse overlap matrix in electronic structure theory, S –1 . This factorization of S –1 , written as ZZT = S –1 , is used to transform the general matrix eigenvalue problem into a standard matrix eigenvalue problem. Here we present a mixed precision iterative refinement algorithm where Z is given recursively using matrix–matrix multiplications and can be computed with high performance on Tensor cores. To understand the performance and accuracy of Tensor cores, comparisons are made to GPU-only implementations in single and double precision. Additionally, we propose a nonparametric stopping criteria which is robust in the face of lower precision floating point operations. The algorithm is particularly useful when we have a good initial guess to Z, for example, from previous time steps in quantum-mechanical molecular dynamics simulations or from a previous iteration in a geometry optimization.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Validation of a Polyimide Foam Model for Use in Transmission Loss Applications

The work described in this paper was focused on the use of a new polyimide foam in a double wall sound transmission loss application. Recall that polyimide foams are functionally attractive, compared to polyurethane foams, for example, owing to their fire resistance. The foam considered here was found to have a flow resistivity that was too high for conventional acoustical applications, and as a result, it was processed by partial crushing to lower the flow resistivity into an acceptable range. Procedures for measuring the flow resistivity and Young s modulus of the material have been described, as was an inverse characterization procedure for estimating the remaining Biot parameters based on standing wave tube measurements of transmission loss and absorption coefficient. The inverse characterization was performed using a finite element model implementation of the Biot poro-elastic material theory. Those parameters were then used to predict the sound transmission loss of a double panel system lined with polyimide foam, and the predictions were compared with full-scale transmission loss measurements. The agreement between the two was reasonable, especially in the high and low frequency limits; however, it was found that the SEA model resulted in an under-prediction of the transmission loss in the mid-frequency range. Nonetheless, it was concluded that the performance of polyimide foam could be predicted using conventional poro-elastic material models and that polyimide foam may offer an attractive alternative to other double wall linings in certain situations: e.g., when fire resistance is a key issue. Future work will concentrate on reducing the density of the foam to values similar to those used in current aircraft sidewall treatments, and developing procedures to improve the performance of the foam in transmission loss applications.

Hong, Kwanwoo↗
DOE OSTI2023

Magnetocaloric Effect in Lightly‐Doped Fe 5 Si 3 Single Crystals

Abstract Development of promising new materials for above room temperature magnetic cooling applications relies on careful balancing of structure and composition to maximize accessible metastable phases that can drive a strong magnetocaloric effect (MCE). However, the working temperatures of these materials may fall outside of desired application windows. In this work, it is shown that it is possible to control metastable phase stability temperatures of Fe 5 Si 3 through selection of appropriate spin and charge doping. Here, the parent material's desired structure appears only within a narrow temperature range from 1098 to 1303 K. Doping with Mn and P is shown to allow stabilization of the parent's high temperature phase and resulting MCE to room temperature. The structural and magnetic properties, and the magnetocaloric effect of single crystal Fe 4.83 Mn 0.16 Si 2.91 P 0.09 (FMSP) are investigated experimentally and theoretically. A first‐order magneto‐elastic transition is observed at 348 K, where magnetic onset is accompanied by a change in lattice volume without an apparent change in crystal symmetry. Although the trace Mn and P doping are found to decrease the T C , the maximum magnetic entropy change Δ S Max ( T ) and the relative cooling power (RCP) of FMSP are enhanced compared to polycrystalline Fe 5 Si 3 . As a result, an intrinsically broader entropy change over a larger temperature span is generated in the lightly doped single crystal of Fe 5 Si 3 . The magnetic moment of the system is also enhanced. Density functional theory (DFT) calculations are performed to gain microscopic insights into the experimental findings. The results suggest that the hexagonal Fe 5 Si 3 is a new giant room temperature MCE material that is on par with La–Fe–Si and Fe‐Mn‐P‐Si systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Soft and transferable pseudopotentials from multi-objective optimization

Ab initio pseudopotentials are a linchpin of modern molecular and condensed matter electronic structure calculations. In this work, we employ multi-objective optimization to maximize pseudopotential softness while maintaining high accuracy and transferability. To accomplish this, we develop a formulation in which softness and accuracy are simultaneously maximized, with accuracy determined by the ability to reproduce all-electron energy differences between Bravais lattice structures, whereupon the resulting Pareto frontier is scanned for the softest pseudopotential that provides the desired accuracy in established transferability tests. We employ an evolutionary algorithm to solve the multi-objective optimization problem and apply it to generate a comprehensive table of optimized norm-conserving Vanderbilt (ONCV) pseudopotentials (https://github.com/SPARC-X/SPMS-psps). Here, we show that the resulting table is softer than existing tables of comparable accuracy, while more accurate than tables of comparable softness. The potentials thus afford the possibility to speed up calculations in a broad range of applications areas while maintaining high accuracy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

High entropy alloys as catalysts: A focused review

A brief literature review of recent experimental and computational efforts on the use of high entropy alloys (HEAs) as catalysts is presented, while also sharing some perspectives and future insights. To fully broach the vast compositional possibilities of HEA materials, integrating computational modeling with high-throughput experimental synthesis and validation is necessary to accelerate their design and development. Once identified, specific HEAs can be a class of materials for the next generation of catalysts when addressing global challenges related to energy independence, commodity chemical production, environmental remediation, abating emissions, and modernized domestic supply chain resilience.

42 - ENGINEERING↗
DOE OSTI2023

Exploring Ligand-to-Metal Charge-Transfer States in the Photo-Ferrioxalate System Using Excited-State Specific Optimization

The photo-ferrioxalate system (PFS), [Fe(III)(C 2 O 4 )] 3– , more than an exact chemical actinometer, has been extensively applied in wastewater and environment treatment. Despite many experimental efforts to improve clarity, important aspects of the mechanism of ferrioxalate photolysis are still under debate. In this paper, we employ the recently developed WΓ-CASSCF to investigate the ligand-to-metal charge-transfer states that are key to ferrioxalate photolysis. This investigation provides a qualitative picture of these states and key potential energy surface features related to the photolysis. Furthermore, our theoretical results are consistent with the prompt charge-transfer picture seen in recent experiments and clarify some features that are not visible in experiments. Two ligand-to-metal charge-transfer states contribute to the photolysis of ferrioxalate, and the avoided crossing barrier between them is low compared with the initial photoexcitation energy. Our data also clarify that one Fe–O bond cleaves first, followed by the C–C bond and the other Fe–O bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Classification of Adsorbed Hydrocarbons Based on Bonding Configurations of the Adsorbates and Surface Site Stabilities

The design of heterogeneous catalysts can be accelerated by identifying relevant descriptors that accurately and effectively link the binding and activation energies to reactivity. Herein, we investigated scaling relations between binding energies of various hydrocarbon-based adsorbates on three different Pt surfaces and metal binding energies estimated via the recently developed α-scheme model. In this study, we find that the scaling slopes are similar for certain groups of adsorbates, which then can be classified based on their spatial and electronic structure enabling fast description of binding strengths for each member of the class. Hence, our findings show that the binding energies of simple hydrocarbons CH x , x = {0,1,2,3,4}, and CHCH 2 can be used to identify the binding energies of more complex hydrocarbon-based adsorbates. We introduce this classification to establish a generalizable scheme in which complex hydrogenation/dehydrogenation processes of higher hydrocarbons can be predicted via the binding energies of simpler hydrocarbon-based species and ultimately through surface site stabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗