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At least 1,405 records · Page 78

Analysis of mechanical, thermodynamic, and thermoelectric properties of ferromagnetic SrFe{sub 4}As{sub 12} skutterudite

In the present work, the electronic, mechanical, thermal and thermoelectric properties of Sr-filled skutterudite have been investigated in the framework of density functional theory. SrFe{sub 4}As{sub 12} shows a ferromagnet character with a magnetic moment of 1.76 μ{sub B} at an optimized lattice parameter of 8.38 Å. The effect of high-pressures on thermodynamic properties viz. thermal expansion coefficient, specific heat capacity and Grüneisen parameter is also carried out by employing the quasi-harmonic Debye model. Temperature dependence of Seebeck coefficient, electrical conductivity, thermal conductivity, power factor, and figure of merit is observed up to 800 K. The lattice thermal conductivity decreases with temperature due to rattling behavior of the filler atom. SrFe{sub 4}As{sub 12} exhibits the high value of the figure of merit equal to 0.76 at 800 K. The present results clearly signify that SrFe{sub 4}As{sub 12} may be a good choice for thermoelectric applications due to its high-power factor and figure of merit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microstructural, chemical and textural characterization of ZnO nanorods synthesized by aerosol assisted chemical vapor deposition

ZnO nanorods were synthesized by aerosol assisted chemical vapor deposition onto TiO{sub 2} covered borosilicate glass substrates. Deposition parameters were optimized and kept constant. Solely the effect of different nozzle velocities on the growth of ZnO nanorods was evaluated in order to develop a dense and uniform structure. The crystalline structure was characterized by conventional X-ray diffraction in grazing incidence and Bragg–Brentano configurations. In addition, two-dimensional grazing incidence synchrotron radiation diffraction was employed to determine the preferred growth direction of the nanorods. Morphology and growth characteristics analyzed by electron microscopy were correlated with diffraction outcomes. Chemical composition was established by X-ray photoelectron spectroscopy. X-ray diffraction results and X-ray photoelectron spectroscopy showed the presence of wurtzite ZnO and anatase TiO{sub 2} phases. Morphological changes noticed when the deposition velocity was lowered to the minimum, indicated the formation of relatively vertically oriented nanorods evenly distributed onto the TiO{sub 2} buffer film. By coupling two-dimensional X-ray diffraction and computational modeling with ANAELU it was proved that a successful texture determination was achieved and confirmed by scanning electron microscopy analysis. Texture analysis led to the conclusion of a preferred growth direction in [001] having a distribution width Ω = 20° ± 2°. - Highlights: • Uniform and pure single-crystal ZnO nanorods were obtained by AACVD technique. • Longitudinal and transversal axis parallel to the [001] and [110] directions, respectively. • Texture was determined by 2D synchrotron diffraction and electron microscopy analysis. • Nanorods have its [001] direction distributed close to the normal of the substrate. • Angular spread about the preferred orientation is 20° ± 2°.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Direct sensitivity analysis on the parameterization of crystal plasticity models

Various methods for calibrating crystal plasticity finite element (CPFE) models lead to non-unique input parameter values, which subsequently introduce uncertainty in the predicted mechanical response. Sensitivity analysis (SA) conducted on crystal plasticity models is used to identify how variability in these parameters contribute to output uncertainty. Traditional SA on CPFE parameters uses simplified surrogate models to save computational time. However, the accuracy of the surrogate models depends on the quantity of training data used, and any modeling error can propagate into the SA results, potentially affecting their reliability. In this work, the elementary effects test (EET) method, a global SA technique using direct CPFE simulations was employed, and the results obtained were compared with the First Order Second Moment (FOSM) method. ExaConstit, an open-source GPU-enabled CPFE code, was used to perform the simulations and direct SA. The EET method was accurately able to capture the non-linear effects of all the input parameters on the output and is a valuable approach for reliably attributing parameter sensitivities in CPFE models. Based on the results, efficient strategies to perform future parameter calibration and SA are discussed. Additionally, the SA trends observed in different single crystal orientations closely mirrored the activity of the slip systems.

Elementary Effects Test↗

Preparation of aluminum hydroxide and oxide nanostructures with controllable morphology by wet oxidation of AlN/Al nanoparticles

Highlights: • Aluminum hydroxide nanoparticles were synthesized by wet oxidation methods. • The oxidation conditions of AlN/Al affect the morphologies of the reaction products. • No changes in the synthesized materials morphology occurred up to 1000 °C. • The maxima specific surface areas for the nanostructures were achieved at 500 °C. - Abstract: A simple and environmentally friendly method to prepare aluminum oxyhydroxide and trihydroxide nanostructures by wet oxidation of AlN/Al composite nanoparticles was developed. The AlN/Al nanoparticles used were produced by electrical explosion of an aluminum wire in nitrogen atmosphere. The obtained nanostructures were characterized employing X-ray diffraction (XRD), transmission and high-resolution scanning electron microscopy (TEM and HRSEM), thermogravimetric analysis (TGA) and N{sub 2} adsorption-desorption technique (BET). By changing the wet oxidation conditions, aluminum hydroxides with different phase composition, morphology and texture characteristics were synthesized. After calcination at different temperatures, a range of transition and stable alumina nanostructures were obtained that preserved the morphology of the aluminum hydroxide precursors - agglomerated nanosheets, nanoplates or hexagonal nanorods, up to 1000 °C. Optimal process parameters for maximum surface area development for all the precursor materials have been established.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Multiwalled carbon nanotubes in titania based nanocomposite as trap for photoexcitons for enhanced photocatalytic hydrogen production under solar light irradiation

Highlights: • Facile synthesis of FCNTs-TiO{sub 2} composite through wet impregnation method. • Parameters were optimized for enhanced photocatalytic hydrogen production under sunlight irradiation. • At optimal conditions nanocomposite showed 8 folds higher hydrogen efficiency than pristine TiO{sub 2}. • Functionalized carbon nanotubes acts as cocatalyst in this study. - Abstract: The impact of functionalized multiwalled carbon nanotubes in titania based nanocomposite for photocatalytic hydrogen production was investigated. Founctionalization experiments were carried out to remove amorphous carbon atttached to carbon nanotubes by strong acid treatment followed by calcination at desired temperature and time intervals. Materials characterization revealed that anatase TiO{sub 2} nanoparticles randomly dispersed onto the walls of one dimensional multiwalled carbon nanotubes with surface hydroxyl and carbonyl groups besides significant change in optical absorption. Photocatalytic activity was performed in aqueous glycerol solution under solar light and volume of hydrogen production was quantified using gas chromatography. Highest hydrogen production rate of 13,107 μmol·h{sup −1}·g{sup −1} of catalyst was recorded under optimized conditions due to cocatalyst role of functionalized carbon nanotubes. Here, photo electrons were trapped by carbon nanotubes for continuous hydrogen production through reduction reaction.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Thermodynamic properties of ZrCl 4 with LiCl, NaCl, KCl, CsCl, MgCl 2 , and UCl 3 for molten salt reactor applications

Here, a set of self-consistent Gibbs energy functions has been developed to describe the thermochemical behavior of the major reactive fission product ZrCl 4 with key components in chloride molten salt reactors (MSRs): LiCl–ZrCl 4 , NaCl–ZrCl 4 , KCl–ZrCl 4 , CsCl–ZrCl 4 , MgCl 2 –ZrCl 4 and UCl 3 –ZrCl 4 . Low ZrCl 4 concentration phase equilibria most relevant to MSR applications have been confirmed via differential scanning calorimetry for NaCl–ZrCl 4 , and X-ray diffraction analysis performed on equilibrated samples of NaCl–ZrCl 4 , KCl–ZrCl 4 , MgCl 2 –ZrCl 4 , and UCl 3 –ZrCl 4 . Within the framework of the modified quasi-chemical model in the quadruplet approximation, extrapolations of pseudo-binary models were generated to represent KCl–MgCl 2 –ZrCl 4 , KCl–NaCl–ZrCl 4 , and MgCl 2 –NaCl–ZrCl 4 , which show agreement with phase equilibria data where available without the use of ternary interaction parameters. The optimized thermodynamic descriptions for these systems and others are available in the open-source compendium Molten Salt Thermal Properties Database – Thermochemical (MSTDB–TC).

CALPHAD↗

Laser powder bed fusion of oxide dispersion-strengthened IN718 alloys: A complementary study on microstructure and mechanical properties

In this study, two new grades of oxide dispersion strengthened (ODS) Inconel 718 (IN718) alloys were designed by the thermochemical CALPHAD method and produced by laser powder bed fusion (LPBF) technique. Alloys designated as IN718-YF and IN718-YFH, that consist Y 2 O 3 –FeO and Y 2 O 3 –FeO–Hf, respectively, were fabricated with >99.9 % densification using optimized process parameters. CALPHAD calculations were highly consistent with experimental findings, highlighting the formation of Al-containing Y–Ti–O and Y–Hf–O nano-oxides in both alloy types. Texture analyzes revealed no significant texture development in as-built (AB) or heat-treated (HT) alloys. Heat treatment was applied at 1050 °C for 1 h to enhance nano-oxide density. Further, the nano-oxide number density remained similar in IN718-YF while it decreased in IN718-YFH alloy as a result of carbide formation after the heat treatment. Besides, formation of secondary γ' particles was observed in the IN718-YFH/HT alloy. Even though the yield strengths of IN718-YF and IN718-YFH alloys in both AB and HT conditions were similar, the ductility of IN718-YFH was ~50 % less in almost all conditions compared to the ductility of IN718-YF. This has been shown to be as a result of irregular shaped micron-sized Y-Hf-O oxides, martensite formation in AB condition, increased amount of carbides and existence of secondary γ' particles in HT condition in IN718-YFH. High density of stacking faults (SF) forming at the interface of the nano-oxides have been detected in IN718-YF alloys. Besides dislocation/nanoparticle interactions, SFs which are responsible for the delocalization of the deformation improve the ductility of IN718-YF alloys. Overall, high temperature mechanical tests exhibit that both alloys have higher strength with improved ductility compared to the standard IN718 alloys, indicating the contribution of the nano-oxides.

36 MATERIALS SCIENCE↗

Computational investigation of arranged scintillating particle composites for fast neutron detection

Composite materials have the potential to play an important role in enabling high-performance and cost-effective neutron detectors for fundamental science, global security, and dosimetry applications. This work presents neutron and gamma transport simulation results on composites consisting of 6 Li-containing GS20 scintillator glass particles arranged in an organic matrix. These composites achieve high sensitivity for neutrons while suppressing signals from gamma rays. The simulations successfully identified optimal composite parameters such as particle size, geometry, and inter-particle pitch. This information is key to the subsequent fabrication and scale-up of the desired GS20-in-acrylic composite. Finally, the simulation results presented in this paper demonstrate that arranged composites can provide high neutron detection efficiency with gamma misidentification values of <1 in 10 6 gamma rays, assuming irradiation with a 252 Cf spontaneous fission source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The influence of thermochemistry on the reactivity of propane, the pentane isomers and $n$-heptane in the low temperature regime

In this study, the influence of thermochemistry on the reactivity of fuels at low temperatures (600–1000 K) is studied here. Specifically, the effect of different sets of thermochemistry on chemical model predictions is explored, where various sets are calculated at different levels of theory in addition to recently updated group additivity values. Experimentally measured ignition delay times for propane, the pentane isomers and n-heptane are simulated using NUIGMech1.2 and replacing the thermochemistry of the low-temperature species with the calculated values. For propane, three different thermochemistry sets were calculated, namely CCSD(T)-F12/TZ-F12//B2PLYP-D3/TZ//B2PLYP-D3/TZ (QM1), CCSD(T)-F12/TZ-F12//B2PLYP-D3/TZ//ωB97X-D/TZ (QM2) and B2PLYP-D3/TZ/ωB97X-D/6-31G*//ωB97X-D/6-31G* (QM3). The QM2 results provide parameters to optimize new group additivity (NGA) values which are used to calculate the fourth set of thermochemistry. The model predictions using these four sets are compared to those using NUIGMech1.2 for propane. As the QM1 and QM2 calculations are expensive, the thermochemistry calculated from the QM3 and NGA calculations are used in the pentane isomer and n-heptane models. For all of the models, it is found that the thermochemistry of the species involved in the low-temperature reaction sequence ($RH$, $\dot{R}$, $RO_2H$, $R\dot{O}_2$, $\dot{Q}OOH$ and $\dot{O}_2QOOH$ species) significantly affect fuel reactivity. The NGA values were developed based on all of these species except $\dot{O}_2QOOH$ radicals. The thermochemistry of $\dot{O}_2QOOH$ species cannot be accurately calculated with the NGA representations due to the importance of non-next-nearest neighbor interactions of –OOH substitution. Further development of the NGA method to capture such interactions is in progress. Overall, the model developed using the NGA thermochemistry shows better agreement with experimental data than the model using thermochemistry from affordable and prominent QM methods, such as QM3. Based on the results presented for propane, the pentane isomers and n-heptane, the thermochemistry calculated using the NGA method can be used to model the oxidation of higher order hydrocarbons at low temperatures.

33 ADVANCED PROPULSION SYSTEMS↗

Novel ammonia recovery from anaerobic digestion by integrating biogas stripping and gypsum absorption

Recovering ammonia from anaerobic digestion (AD) effluent offers the opportunity to produce a renewablefertilizer and reduce environmental impact. A novel process developed for such an application was evaluatedduring this study. The feature of the process is integrating biogas stripping and gypsum (CaSO 4 •2H 2 O) absorption. The result revealed that the lower CO 2 content and the absorption temperature contributed the higherefficiency of ammonia recovery. The gypsum solution recovered around 95% of the stripped ammonia when thestripping gas contained 10% CO 2 and it rose to 100% when the gas contained more than 30% CO 2 . Furthermore,a statistical model and genetic algorithm were applied to estimate the total ammonia recovery and optimize theoperating parameters. The experimental and modeling results indicated that integrating biogas stripping withgypsum absorption can effectively harvest ammonia nitrogen and reduce CO 2 emissions while producing(NH 4 ) 2 SO 4 fertilizer from AD effluent.

59 BASIC BIOLOGICAL SCIENCES↗

Towards low-carbon low-energy concrete alternatives: Life cycle assessment of carbonated cementitious material-based precast panels

Cement is responsible for 22 % of all global CO 2 emissions from industrial processes. Technological innovation for developing and deploying of alternative materials will be required to decarbonize the cement industry. Carbonated cementitious materials (CCMs) are building materials that rely on carbon mineralization for their strength. A process-based cradle-to-gate life cycle assessment (LCA) was conducted to evaluate the global warming potential (GWP), cumulative energy demand, and water consumption of a lab-scale CCM-based precast panel compared to a conventional precast concrete panel. Since the CCM process is currently a lab-scale early-stage process, the CCM panel showed higher environmental impacts compared to the conventional panel. However, scenario analyses include mature production process scenarios. In conclusion, a sensitivity analysis revealed that the GWP of CCM can be lowered to below that of the conventional panel using polymers, fillers, low-carbon electricity sources, and optimized carbonation parameters.

36 MATERIALS SCIENCE↗

Drug discovery efforts at George Mason University

With over 39,000 students, and research expenditures in excess of $200 million, George Mason University (GMU) is the largest R1 (Carnegie Classification of very high research activity) university in Virginia. Mason scientists have been involved in the discovery and development of novel diagnostics and therapeutics in areas as diverse as infectious diseases and cancer. Below are highlights of the efforts being led by Mason researchers in the drug discovery arena. To enable targeted cellular delivery, and non-biomedical applications, Veneziano and colleagues have developed a synthesis strategy that enables the design of self-assembling DNA nanoparticles (DNA origami) with prescribed shape and size in the 10 to 100 nm range. The nanoparticles can be loaded with molecules of interest such as drugs, proteins and peptides, and are a promising new addition to the drug delivery platforms currently in use. The investigators also recently used the DNA origami nanoparticles to fine tune the spatial presentation of immunogens to study the impact on B cell activation. These studies are an important step towards the rational design of vaccines for a variety of infectious agents. To elucidate the parameters for optimizing the delivery efficiency of lipid nanoparticles (LNPs), Buschmann, Paige and colleagues have devised methods for predicting and experimentally validating the pKa of LNPs based on the structure of the ionizable lipids used to formulate the LNPs. These studies may pave the way for the development of new LNP delivery vehicles that have reduced systemic distribution and improved endosomal release of their cargo post administration. To better understand protein-protein interactions and identify potential drug targets that disrupt such interactions, Luchini and colleagues have developed a methodology that identifies contact points between proteins using small molecule dyes. The dye molecules noncovalently bind to the accessible surfaces of a protein complex with very high affinity, but are excluded from contact regions. When the complex is denatured and digested with trypsin, the exposed regions covered by the dye do not get cleaved by the enzyme, whereas the contact points are digested. The resulting fragments can then be identified using mass spectrometry. The data generated can serve as the basis for designing small molecules and peptides that can disrupt the formation of protein complexes involved in disease processes. For example, using peptides based on the interleukin 1 receptor accessory protein (IL-1RAcP), Luchini, Liotta, Paige and colleagues disrupted the formation of IL-1/IL-R/IL-1RAcP complex and demonstrated that the inhibition of complex formation reduced the inflammatory response to IL-1B. Working on the discovery of novel antimicrobial agents, Bishop, van Hoek and colleagues have discovered a number of antimicrobial peptides from reptiles and other species. DRGN-1, is a synthetic peptide based on a histone H1-derived peptide that they had identified from Komodo Dragon plasma. DRGN-1 was shown to disrupt bacterial biofilms and promote wound healing in an animal model. The peptide, along with others, is being developed and tested in preclinical studies. Other research by van Hoek and colleagues focuses on in silico antimicrobial peptide discovery, screening of small molecules for antibacterial properties, as well as assessment of diffusible signal factors (DFS) as future therapeutics. The above examples provide insight into the cutting-edge studies undertaken by GMU scientists to develop novel methodologies and platform technologies important to drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗

Simulation and fitting of complex reaction network TPR: The key is the objective function

In this research, a method has been developed for finding improved fits during simulation and fitting of data from complex reaction network temperature programmed reactions (CRN-TPR). It was found that simulation and fitting of CRN-TPR presents additional challenges relative to simulation and fitting of simpler TPR systems. The method used here can enable checking the plausibility of proposed chemical mechanisms and kinetic models. The most important finding was that when choosing an objective function, use of an objective function that is based on integrated production provides more utility in finding improved fits when compared to an objective function based on the rate of production. The response surface produced by using the integrated production is monotonic, suppresses effects from experimental noise, requires fewer points to capture the response behavior, and can be simulated numerically with smaller errors. For CRN-TPR, there is increased importance (relative to simple reaction network TPR) in resolving of peaks prior to fitting, as well as from weighting of experimental data points. Using an implicit ordinary differential equation solver was found to be inadequate for simulating CRN-TPR. Lastly, the method employed here was capable of attaining improved fits in simulation and fitting of CRN-TPR when starting with a postulated mechanism and physically realistic initial guesses for the kinetic parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanistic Insights into Dinitrogen Reduction to Ammonia in Light-Controlled Nanocrystal:Nitrogenase Complexes

Developing systems that can efficiently capture photon energy and convert this energy into fuels and chemicals requires understanding how to assemble molecular components with diverse functions into complete systems possessing selectivity and efficiency in directing charge carriers to catalytic reactions. There are many challenges to achieving this goal. One promising approach is the development of hybrid systems that combine semiconductor nanocrystals (NCs) for light capture and enzymes as efficient catalysts. Such biohybrid systems capitalize on the tunable electronic and optical properties of NCs while leveraging the unmatched specificity and efficiency of enzymes in catalyzing chemical reactions, thereby offering opportunities to surpass the limitations of each component alone. Here, we focus on recent progress in developing a biohybrid system that combines CdS NCs for photon capture with the enzyme nitrogenase to accomplish light-driven dinitrogen (N 2 ) reduction to ammonia (NH 3 ). Integrating light-harvesting materials with biological catalysts requires a deep understanding of NC properties, protein stability, and electron transfer (ET), making it an inherently multidisciplinary problem. The reduction of N 2 to NH 3 is a challenging reaction, with a high demand in both agriculture and industrial chemical production. This reaction is intrinsically energy intensive, due to the need to activate the N≡N triple bond. The current standard industrial approach to N 2 reduction, the Haber−Bosch reaction, obtains the necessary energy input from fossil fuels, whereas biological systems capable of N 2 reduction utilize the hydrolysis of ATP as their energy source. Replacing these costly, energy-intensive inputs with renewable light energy represents a critical step toward sustainable NH 3 production. Recent progress has demonstrated that semiconductor CdS NCs can be coupled to the catalytic component of nitrogenase, the MoFe protein, to form a biohybrid CdS NC:MoFe protein complex, enabling light-driven N 2 reduction rather than energy input from fossil fuels or ATP. This illustrates how inorganic NCs can functionally replace the natural Fe protein partner, yielding a biohybrid catalyst that enables controlled electron delivery and provides not only light-driven NH 3 production but also new approaches for probing enzyme catalytic function. The CdS NC:MoFe protein biohybrid system enables light-initiated electron delivery at ambient temperature, as well as temperatures below freezing, allowing for stabilization and spectroscopic characterization of key reaction intermediates. These findings highlight how photochemical biohybrids can serve as both functional catalysts and mechanistic probes. Beyond studies of the nitrogenase mechanism, studies of the CdS NC:MoFe system reveal how variables such as NC size, electrostatic binding interactions, and sacrificial electron donors (SEDs) govern complex stability, charge transfer efficiency, and catalytic performance. In addition, studies of nitrogenase and the high activation barrier for N 2 reduction are enabling investigations of new and interesting questions regarding the properties and limitations of NC biocatalysis. In this Account, we describe the key features of CdS NC:MoFe protein biohybrids and the parameters for optimal light-driven N 2 reduction, and how controlling ET with light illuminates the path to new insights into the nitrogenase mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Single-Particle Isotopic Analysis Using the Liquid Sampling-Atmospheric Pressure Glow Discharge Microplasma Coupled to an Orbitrap Mass Spectrometer

Isotope ratio (IR) determinations on individual particles can provide valuable information relative to the sample, including processing and dating, which could be valuable to geological and nuclear material analysis communities. In comparison to “bulk” measurements, in which all particle information is lost and homogenized within a sample, “particle” measurements allow for fingerprinting and can provide unique insights related to the sample’s nano- and micro- compositions. Furthermore, the complex nature of particles, with potential isobaric interferences from either the matrix or other elements within the same particle, poses a significant analytical challenge for conventional mass spectrometry platforms employed for elemental analysis due to their limited mass resolution. Presented here is the first demonstration of an ultrahigh resolution method for single particle (SP) isotopic analysis using the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma ionization source coupled to an Orbitrap mass spectrometer and FTMS Booster X2T acquisition/processing system. For proof of concept, well-characterized CeO 2 microparticles with a nominal diameter of 1.0 μm were analyzed at a mass resolution of ∼330,000. Important instrumental parameters were optimized to enable the detection of single particles. The 142 Ce/ 140 Ce ratio of individual particles and the population average were determined and compared to an SP inductively coupled plasma time-of-flight mass spectrometry (ICP-TOF-MS) analysis. The isotopic accuracy and precision were determined by two methods and found to be in good agreement with the SP-ICP-TOF-MS method, with the linear regression slope method providing a more accurate ratio, showing a ∼1.4% relative difference from the ratio determined from a particle digest. The encouraging performance of the method was further supported by a determined detection limit of 2.9 fg ( 142 Ce). The developed method is anticipated to overcome many of the challenges posed by isobaric interferences encountered in conventional mass spectrometry techniques when analyzing real-world samples for particle isotopic composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Multireference Quantum Krylov Algorithm for Strongly Correlated Electrons

We introduce a multireference selected quantum Krylov (MRSQK) algorithm suitable for quantum simulation of many-body problems. MRSQK is a low-cost alternative to the quantum phase estimation algorithm that generates a target state as a linear combination of non-orthogonal Krylov basis states. This basis is constructed from a set of reference states via real-time evolution; thus, avoiding the numerical optimization of parameters. An efficient algorithm for the evaluation of the off-diagonal matrix elements of the overlap and Hamiltonian matrices is discussed and a selection procedure is introduced to identify a basis of orthogonal references that ameliorates the linear dependency problem. Preliminary benchmarks on linear H 6 , H 8 , and BeH 2 indicate that MRSQK can predict the energy of these systems accurately using very compact Krylov bases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗