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At least 829 records · Page 46

Kinetics and Reaction Mechanisms of Acetic Acid Hydrodeoxygenation over Pt and Pt–Mo Catalysts

In this work, kinetic measurements for silica-supported Pt and Pt-Mo catalysts were collected in vapor-phase acetic acid hydrodeoxygenation by varying the hydrogen partial pressure between 18 and 72 kPa and acetic acid partial pressure between 7 and 18 kPa at 423-473 K. At all testing conditions, the Pt-Mo catalyst was more active and selective. In addition, the apparent activation energy for Pt-Mo of 76±3 kJ/mol was lower than that of 84±4 kJ/mol for Pt. The apparent reaction orders were also different. The order in hydrogen of 0.8±0.1 for Pt-Mo changed to zero at higher hydrogen partial pressures while that for Pt remained constant at 0.6±0.1. A near-zero order in acetic acid for Pt-Mo changed to -2.1 at higher acetic acid pressures while that for Pt remained constant at -2.9±0.3. These differences in reaction kinetics as well as in selectivity trends with changes in temperature and feed composition indicated a change in the reaction mechanism for Pt-Mo. The catalysts were characterized with hydrogen temperature programmed desorption, oxygen temperature programmed oxidation and transmission electron microscopy with energy-dispersed X-ray spectroscopy elemental mapping. Mo was present in the form of subnanometer-size clusters on the surface of Pt nanoparticles. Both Pt and Pt-Mo catalysts were stable under the reaction conditions for 10 h, and the size and structure of Pt and Pt-Mo particles remained mostly unchanged, without coke accumulation. Density functional theory calculations show that surface acetate is not a major reaction intermediate on both Pt and Pt-Mo and, instead, C-OH bond splitting with the formation of acetyl is the first reaction step in hydrodeoxygenation. The activation energy for this step is dramatically lower on Pt-Mo. Furthermore, the activity of acetyl on Pt-Mo is different. Unlike on pure Pt, the reaction of C-O bond splitting becomes exothermic with a lower activation energy on Pt-Mo, and the reaction of C-C bond splitting, in contrast, becomes endothermic with a higher activation energy, explaining the experimentally observed higher activities and selectivities of Pt-Mo. In addition, the calculations demonstrate that a pair of Pt-Mo surface atoms acts as a single active site where Mo serves as a preferential binding anchor for O atoms. The presence of Mo atoms changes the structure and energy of adsorbed and reacting surface species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the chemical contribution to the enhancement mechanism in SERS: Connection with Hammett parameters

The enhancement mechanism due to the molecule-surface chemical interaction in surface-enhanced Raman scattering (SERS) has been characterized using a theoretical approach based on time dependent density functional theory. This includes a systematic study of the chemical mechanism (CM) to the SERS enhancement for halogen substituted benzenethiols interacting with a silver cluster. Changing the halogen on benzenethiol enables us to systematically modulate interactions between the benzenethiol ring and the metal cluster. We observe a decrease in the CM enhancement factor with an increase in atomic number of the halogen for para- substitutions. For meta- substitutions, there is no such trend. However, the results scale linearly with the Hammett parameters for both meta and para halogens, which provides an important predictive tool for interpreting chemical enhancements. We also study the effect of solvation on the CM, showing that there is a systematic increase in enhancement with increasing solvent dielectric constant. As a result, the correlation of CM with other properties, such as the amount of charge transfer between adsorbate and metal, or the excitation energies of charge transfer states, is much less predictive than the Hammett parameter correlation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The impact of tomographic redshift bin width errors on cosmological probes

ABSTRACT Systematic errors in the galaxy redshift distribution n(z) can propagate to systematic errors in the derived cosmology. We characterize how the degenerate effects in tomographic bin widths and galaxy bias impart systematic errors on cosmology inference using observational data from the Deep Lens Survey. For this we use a combination of galaxy clustering and galaxy–galaxy lensing. We present two end-to-end analyses from the catalogue level to parameter estimation. We produce an initial cosmological inference using fiducial tomographic redshift bins derived from photometric redshifts, then compare this with a result where the redshift bins are empirically corrected using a set of spectroscopic redshifts. We find that the derived parameter S8 ≡ σ8(Ωm/.3)1/2 decreases from $0.841^{+0.062}_{-0.061}$ to $0.781^{0.061}_{0.054}$ upon correcting the n(z) errors in the second method.

79 ASTRONOMY AND ASTROPHYSICS↗

Novel Technique for Developing Linearized Convex System Models from Experimentally Derived Data

This paper presents a novel technique for generating a convex system model from an experimentally derived data set which features variance among repeated measurements. The convex system model developed as a test case characterizes the dynamic system losses of a vanadium redox flow battery as a function of the active power output and the battery state of charge. The technique hinges on a pre-cleaning via clustering procedure which precedes the formation of a planar convex hull comprised of triangular simplices. The clustering procedure efficiently reduces the experimental data set while mitigating variance among repeated measurements and removes outliers. Ultimately, the lower evelope of the planar convex hull serves as the desired convex system model. The proposed technique reduces systematic model error which is otherwise present when directly developing a planar convex hull model based on an unreduced data set.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Physiological Maturation of Regenerating Hair Cells

The bullfrog saccule, a sensor of gravity and substrate-borne vibration, is a model system for hair cell transduction. Saccular hair cells also increase in number throughout adult life and rapidly recover after hair cell damage, making this organ an ideal system for studying hair cell development, repair, and regeneration. We have used of hair cell and supporting cell immunocytochemical markers to identify damaged hair cells and hair cell precursors in organotypic cultures of the bullfrog saccule. We then used an innovative combination of confocal, electron, and time-lapse microscopy to study the fate of damaged hair cells and the origin of new hair cells after gentamicin ototoxicity in normal and mitotically blocked saccular cultures. These studies have shown that gentamicin ototoxicity produces both lethal and sublethal hair cell damage. They have also shown that hair cell recovery in this organ takes place by both the repair of sublethally damaged hair cells and by the replacement of lost hair cells by mitotic regeneration. In parallel studies, we have used biophysical and molecular biological techniques to study the differentiation and innervation of developing, repairing, and regenerating hair cells. More specifically, we have used RT-PCR to obtain the bullfrog homologues of L-type voltage- gated calcium (L-VGCC) and large-conductance Ca(2+)-activated potassium (BK) channel genes. We have then obtained probes for these genes and, using in situ hybridization, begun to examine their expression in the bullfrog saccule and amphibian papilla. We have also used fluorescent-labeled channel toxins and channel toxin derivatives to determine the time of appearance of L-type voltage-gated calcium (L-VGCC) and Ca(2+)-activated potassium (BK) channels and to study dynamic changes in the number, distribution, and co-localization of these proteins in developing, repairing, and regenerating hair cells. Using time-lapse microscopy, we are also studying the dynamic relationship between ion channel clustering and synaptic formation in hair cells and afferent neurons. In future studies, we will determine when hair cell precursors acquire electrical tuning, and, using whole-cell patch-clamp techniques, identify and characterize their L-VGCC and BK currents. We will also use biophysical techniques to determine the number of L-VGCC and BK channels and the size and gating kinetics of their underlying L-VGCC and BK conductances, correlating these variables with the amplitude and frequency of membrane oscillations produced by intracellular current steps. We expect these studies to determine how hair cells regulate ion channel expression to achieve specific physiological responses.

Baird, Richard A.↗

How generic is iodide-tagging photoelectron spectroscopy: An extended investigation on the Gly· X - (Gly = glycine, X = Cl or Br) complexes

We report a joint negative ion photoelectron spectroscopy (NIPES) and quantum chemical computational study on glycine-chloride/bromide complexes (denoted Gly·X - , X = Cl/Br) in close comparison to the previously studied Gly·I - cluster ion. Combining experimental NIPE spectra and theoretical calculations, various Gly·X - complexes were found to adopt the same types of low-lying isomers, albeit with different relative energies. Despite more congested spectral profiles for Gly·Cl - and Gly·Br - , spectral assignments were accomplished with the guidance of the knowledge learned from Gly·I - , where a larger spin–orbit splitting of iodine afforded well-resolved, recognizable spectral peaks. Three canonical plus one zwitterionic isomer for Gly·Cl - and four canonical conformers for Gly·Br - were experimentally identified and characterized in contrast to the five canonical ones observed for Gly·I - under similar experimental conditions. Taken together, this study investigates both genericity and variations in binding patterns for the complexes composed of glycine and various halides, demonstrating that iodide-tagging is an effective spectroscopic means to unravel diverse ion-molecule binding motifs for cluster anions with congested spectral bands by substituting the respective ion with iodide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CsI(Tl) pulse shape discrimination with the Belle II electromagnetic calorimeter as a novel method to improve particle identification at electron–positron colliders

Here we describe the implementation and performance of CsI(Tl) pulse shape discrimination for the Belle II electromagnetic calorimeter, representing the first application of CsI(Tl) pulse shape discrimination for particle identification at an electron–positron collider. The pulse shape characterization algorithms applied by the Belle II calorimeter are described. Control samples of $γ, μ^+, π^±, K^±$ and $ρ/ \bar{ρ}$ are used to demonstrate the significant insight into the secondary particle composition of calorimeter clusters that is provided by CsI(Tl) pulse shape discrimination. Comparisons with simulation are presented and provide further validation for newly developed CsI(Tl) scintillation response simulation techniques, which when incorporated with GEANT4 simulations allow the particle dependent scintillation response of CsI(Tl) to be modelled. Comparisons between data and simulation also demonstrate that pulse shape discrimination can be a new tool to identify sources of improvement in the simulation of hadronic interactions in materials. The $K^0_L$ efficiency and photon-as-hadron fake-rate of a multivariate classifier that is trained to use pulse shape discrimination is presented and comparisons are made to a shower-shape based approach. CsI(Tl) pulse shape discrimination is shown to reduce the photon-as-hadron fake-rate by over a factor of 3 at photon energies of 0.2 GeV and over a factor 10 at photon energies of 1 GeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Kinetic and substrate complex characterization of RamA, a corrinoid protein reductive activase from Methanosarcina barkeri

ABSTRACT In microbial corrinoid-dependent methyltransferase systems, adventitious Co(I)-corrinoid oxidation halts catalysis and necessitates repair by ATP-dependent reductive activases. RamA, an activase with a C-terminal ferredoxin domain with two [4Fe-4S] clusters from methanogenic archaea, has been far less studied than the bacterial activases bearing an N-terminal ferredoxin domain with one [2Fe-2S] cluster. These differences suggest RamA might prove to have other distinctive characteristics. Here, we examine RamA kinetics and the stoichiometry of the corrinoid protein:RamA complex. Like bacterial activases, K+ stimulates RamA. Potassium stimulation had been questioned due to differences in the primary structure of bacterial and methanogen activases. Unlike one bacterial activase, ATP is not inhibitory allowing the first determination of apparent kinetic parameters for any corrinoid activase. Unlike bacterial activases, a single RamA monomer complexes a single corrinoid protein monomer. Alanine replacement of a RamA serine residue corresponding to the serine of one bacterial activase which ligates the corrinoid cobalt during complex formation led to only moderate changes in the kinetics of RamA. These results reveal new differences in the two types of corrinoid activases, and provide direct evidence for the proposal that corrinoid activases act as catalytic monomers, unlike other enzymes that couple ATP hydrolysis to difficult reductions.

Microbiology↗

NMPFamsDB: a database of novel protein families from microbial metagenomes and metatranscriptomes

Abstract The Novel Metagenome Protein Families Database (NMPFamsDB) is a database of metagenome- and metatranscriptome-derived protein families, whose members have no hits to proteins of reference genomes or Pfam domains. Each protein family is accompanied by multiple sequence alignments, Hidden Markov Models, taxonomic information, ecosystem and geolocation metadata, sequence and structure predictions, as well as 3D structure models predicted with AlphaFold2. In its current version, NMPFamsDB hosts over 100 000 protein families, each with at least 100 members. The reported protein families significantly expand (more than double) the number of known protein sequence clusters from reference genomes and reveal new insights into their habitat distribution, origins, functions and taxonomy. We expect NMPFamsDB to be a valuable resource for microbial proteome-wide analyses and for further discovery and characterization of novel functions. NMPFamsDB is publicly available in http://www.nmpfamsdb.org/ or https://bib.fleming.gr/NMPFamsDB.

59 BASIC BIOLOGICAL SCIENCES↗

PDBspheres: a method for finding 3D similarities in local regions in proteins

Abstract We present a structure-based method for finding and evaluating structural similarities in protein regions relevant to ligand binding. PDBspheres comprises an exhaustive library of protein structure regions (‘spheres’) adjacent to complexed ligands derived from the Protein Data Bank (PDB), along with methods to find and evaluate structural matches between a protein of interest and spheres in the library. PDBspheres uses the LGA (Local–Global Alignment) structure alignment algorithm as the main engine for detecting structural similarities between the protein of interest and template spheres from the library, which currently contains >2 million spheres. To assess confidence in structural matches, an all-atom-based similarity metric takes side chain placement into account. Here, we describe the PDBspheres method, demonstrate its ability to detect and characterize binding sites in protein structures, show how PDBspheres—a strictly structure-based method—performs on a curated dataset of 2528 ligand-bound and ligand-free crystal structures, and use PDBspheres to cluster pockets and assess structural similarities among protein binding sites of 4876 structures in the ‘refined set’ of the PDBbind 2019 dataset.

59 BASIC BIOLOGICAL SCIENCES↗

An HMM approach expands the landscape of sesquiterpene cyclases across the kingdom Fungi

Sesquiterpene cyclases (STC) catalyse the cyclization of the C15 molecule farnesyl diphosphate into a vast variety of mono- or polycyclic hydrocarbons and, for a few enzymes, oxygenated structures, with diverse stereogenic centres. The huge diversity in sesquiterpene skeleton structures in nature is primarily the result of the type of cyclization driven by the STC. Despite the phenomenal impact of fungal sesquiterpenes on the ecology of fungi and their potentials for applications, the fungal sesquiterpenome is largely untapped. The identification of fungal STC is generally based on protein sequence similarity with characterized enzymes. This approach has improved our knowledge on STC in a few fungal species, but it has limited success for the discovery of distant sequences. Besides, the tools based on secondary metabolite biosynthesis gene clusters have shown poor performance for terpene cyclases. Here, we used four sets of sequences of fungal STC that catalyse four types of cyclization, and specific amino acid motives to identify phylogenetically related sequences in the genomes of basidiomycetes fungi from the order Polyporales. We validated that four STC genes newly identified from the genome sequence of Leiotrametes menziesii, each classified in a different phylogenetic clade, catalysed a predicted cyclization of farnesyl diphosphate. We built HMM models and searched STC genes in 656 fungal genomes genomes. We identified 5605 STC genes, which were classified in one of the four clades and had a predicted cyclization mechanism. We noticed that the HMM models were more accurate for the prediction of the type of cyclization catalysed by basidiomycete STC than for ascomycete STC.

59 BASIC BIOLOGICAL SCIENCES↗

Understanding grain boundary segregation under irradiation: A mesoscale modeling study

Grain boundaries (GBs) are an important component in the design of irradiation resistant materials as they play a crucial role as point defect sinks for non-equilibrium vacancies and self-interstitials. However, in the presence of sustained point defect fluxes, the coupled transport of atomic components with inherently different diffusivities often leads to radiation-induced segregation (RIS), with undesired effects on properties such as intergranular corrosion and stress-assisted cracking. In this talk, we investigate the fundamental mechanisms leading to GB segregation in BCC FeCr-based alloys using multiscale modeling and experiments. A phase-field model is employed to account for both thermodynamic and kinetic segregation mechanisms. The full Onsager transport matrix is derived using kinetic Monte Carlo, molecular dynamics, and kinetic cluster expansion (KineCluE) calculations. The thermodynamics of GB segregation is described via an atomic density-based modification to the CALPHAD free energy. The modeling predictions are then compared against segregation data from atom probe characterization for various temperatures, compositions, and neutron irradiation conditions. We will conclude by discussing the utility of the multiscale modeling approach to shed light on the fundamental mechanisms leading to solute-GB interaction.

36 MATERIALS SCIENCE↗

Classifying biophysical subpopulations of insulin secretory granules using quantitative whole-cell structure analysis

Pancreatic beta cells contain insulin secretory granules (ISGs), organelles where proinsulin is converted into insulin. As ISGs mature, they undergo extensive biophysical remodeling, producing a spectrum of subpopulations with heterogeneous molecular and spatial characteristics. However, systematic methods to define ISG subpopulations remain underdeveloped. To address this gap in knowledge, we employed soft X-ray tomography (SXT), which can quantitatively measure the biochemical density of ISGs within whole beta cells. Using unsupervised clustering, we classified subpopulations based on molecular density, size, and spatial positioning. Across different insulin secretory stimuli, we observed shifts toward mature and releasable subtypes, demonstrating that exogenous signals can dynamically remodel ISG subpopulation distributions. We extended this methodology to primary beta cells characterized using volume electron microscopy (vEM). Integrating subpopulations from SXT and vEM uncovered insights inaccessible by a single method in isolation. This strategy establishes a framework for defining therapeutic approaches aimed at enriching physiologically beneficial ISG subpopulations.

dense-core granules↗

Surface Fe clusters promote syngas reaction to oxygenates on Rh catalysts modified by atomic layer deposition

Converting syngas to higher oxygenates is a promising strategy for sustainably producing fuels and chemicals used every day. Rh-based catalysts promoted with metal oxides have long been of interest for oxygenate synthesis, but the role of promoters and the structure of the catalyst during reaction are often not well understood. In this work, we characterize a Rh/SiO 2 catalyst modified by Fe 2 O 3 deposited by atomic layer deposition (ALD). Here, we show that Fe 2 O 3 deposits selectively on the Rh nanoparticles and enhances both the turnover frequency and the oxygenate selectivity of the catalysts. A maximum 29% selectivity towards higher oxygenates is achieved with just 1 cycle of Fe 2 O 3 ALD, and we relate the trends in selectivity to the changing availability of surface sites that drive higher alcohol (e.g., ethanol and propanol) formation. Further, we show that the ALD promoter mitigates catalyst sintering, improving the stability of these materials. In-situ X-ray absorption spectroscopy experiments reveal that the Fe 2 O 3 undergoes reduction during the catalyst pretreatment and forms Fe clusters on the surface of the Rh that migrate but remain stable under syngas reaction conditions. We find that modification of the Rh with these surface Fe species is key to the enhanced alcohol production observed in these materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Elucidating the role of $\mathrm{Fe}$-$\mathrm{Mo}$ interactions in the metal oxide precursors for Fe promoted $\mathrm{Mo/ZSM}$-5 catalysts in non-oxidative methane dehydroaromatization

Literature shows that adding Fe as a separate phase to MoO 3 /ZSM-5 catalysts can improve benzene selectivity in methane dehydroaromatization (MDA), but only when added in small quantities, making it difficult to characterize the state of Fe in the catalyst and understand the role of Fe-Mo interactions on the catalytic properties. We explore how the nature of the Mo-Fe interactions in the catalyst precursor can influence the stability and product selectivity in MDA, by employing for the first time Fe 2 (MoO 4 ) 3 /ZSM-5 as a catalyst precursor in MDA. We have compared the activity of Fe 2 (MoO 4 ) 3 /ZSM-5 with monometallic MoO 3 /ZSM-5 and mixed MoO 3 + Fe 2 O 3 /ZSM-5 containing equivalent Mo and Fe loadings and found that Fe 2 (MoO 4 ) 3 /ZSM-5 shows higher benzene selectivity than the mixed MoO 3 + Fe 2 O 3 /ZSM-5 catalyst and exhibits higher stability in reaction compared to the monometallic MoO3/ZSM-5 catalyst. Structural characterization suggests that Fe 2 (MoO 4 ) 3 partially segregates to Fe 2 O 3 and amorphous MoO x during thermal pretreatment. The MoO x species migrate into the zeolite channels during pretreatment, while Fe oxides remain on the external surface of the zeolite. Gas adsorption/desorption techniques and density functional theory calculations demonstrate that the preexisting Fe 2 O 3 phases on the external surface of the zeolite in the mixed MoO 3 + Fe 2 O 3 /ZSM-5 precursor trap (MoO 3 ) 3 clusters preventing them from migrating into the zeolite channels during pretreatment, whereas gradual formation of amorphous MoOx together with the segregation of the Fe 2 O 3 phase when using the Fe 2 (MoO 4 ) 3 precursor diminishes trapping of (MoO 3 ) 3 and consequently enhances migration and anchoring of the MoO x species in the zeolite channels, boosting selectivity to benzene. Characterization of used catalysts suggests that the presence of Fe promotes formation of structured carbon nanofibers which reduce the rate of catalyst deactivation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Novel Co 5 Cluster Based Triazole Bridged Cobalt-Fluorophosphate: Synthesis, Structure, Magnetic and Heterogeneous Catalytic Epoxidation Studies

A novel triazole bridged cobalt fluorophosphate coordination polymer with the formula {Co 5 (1,2,4-triazole) 2 (OH) 2 (PO 3 F) 4 } n has been synthesized. Single crystal X-ray studies reveal that the compound comprises of Co 5 clusters which ultimately build the whole framework, here all cobalt centers are in octahedral geometry established from continuous shape analysis. All the cobalt centers are in Co(II) oxidation state and the results are supported by the bond valence sum (BVS) calculation. The sample has been characterized by single crystal X-ray, powder X-ray, FTIR and TGA analysis. The compound was tested for olefin catalysis performance and magnetism. Magnetization measurements reveal overall antiferromagnetic interactions among the Co(II) ions. The compound is very active in the catalytic transformation of olefins to their corresponding epoxides. In conclusion, catalytic epoxidation studies reveal that cyclohexene and styrene can be converted up to 97% with almost 65% selectivity of products with higher TON numbers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗

RT-EOM-CCSD Calculations of Inner and Outer Valence Ionization Energies and Spectral Functions

Photoelectron spectroscopy (PES) is a standard experimental method for material characterization, but its interpretation can be hampered by its reliance on standard materials. To facilitate the study of unknown systems, theoretical methods are desirable. Here we present a real-time equation-of-motion coupled cluster (RT-EOM-CC) approach for valence PES, extending our core-level development. Here, we demonstrate that RT-EOM-CC yields ionization energies and spectral functions in good agreement with experiment and CI-based methods, even for some more correlated cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗