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At least 487 records · Page 27

Grid Forming Fast Frequency Response for PMSG-Based Wind Turbines

Electric power systems are undergoing a rapid transition from fuel-based generation using synchronous generators to renewable generation interfaced by power electronics. In this context, a key challenge is using renewable generation with limited controllability to contribute to power system stability. In this work, we investigate grid-forming control of permanent magnet synchronous generator (PMSG) wind turbines. The proposed control and curtailment strategy supports the entire spectrum of standard functions of grid-following (e.g. maximum power point tracking (MPPT) and grid-forming control (e.g., primary frequency control) without explicit mode switching. A detailed case study is used to compare the performance of the proposed control at operating points corresponding to MPPT and frequency control with standard grid-forming and grid-following controls. Further, the results demonstrate that (i) the proposed energy balancing grid forming control is self-synchronizing in MPPT mode, (ii) the (limited) energy storage and controllability of wind turbines can be adequately utilized to provide grid support, and (ii) the proposed control exhibits good performance under variable wind speeds and does not result in a significant increase of wind turbine fatigue loads.

17 WIND ENERGY↗

SNPeffect: identifying functional roles of SNPs using metabolic networks

Genetic sources of phenotypic variation have been a focus of plant studies aimed at improving agricultural yield and understanding adaptive processes. Genome-wide association studies identify the genetic background behind a trait by examining associations between phenotypes and single-nucleotide polymorphisms (SNPs). Although such studies are common, biological interpretation of the results remains a challenge; especially due to the confounding nature of population structure and the systematic biases thus introduced. Here, we propose a complementary analysis (SNPeffect) that offers putative genotype-to-phenotype mechanistic interpretations by integrating biochemical knowledge encoded in metabolic models. SNPeffect is used to explain differential growth rate and metabolite accumulation in A. thaliana and P. trichocarpa accessions as the outcome of SNPs in enzyme-coding genes. To this end, we also constructed a genome-scale metabolic model for Populus trichocarpa, the first for a perennial woody tree. As expected, our results indicate that growth is a complex polygenic trait governed by carbon and energy partitioning. The predicted set of functional SNPs in both species are associated with experimentally characterized growth-determining genes and also suggest putative ones. Functional SNPs were found in pathways such as amino acid metabolism, nucleotide biosynthesis, and cellulose and lignin biosynthesis, in line with breeding strategies that target pathways governing carbon and energy partition.

54 ENVIRONMENTAL SCIENCES↗

Defending the Homeland: Growing Foreign Challenges to the U.S. Missile Defense Posture

The Office of the Secretary of Defense (OSD) for Policy requested that Lawrence Livermore National Laboratory conduct a Congressionally directed study on homeland missile defense, pursuant to Section 1692 of the fiscal year 2020 National Defense Authorization Act. In accordance with the statutory language, this study considers whether the security benefits obtained by deployment of homeland missile defenses of the United States are undermined or counterbalanced by adverse reactions of potential adversaries, and considers the effectiveness of homeland missile defense efforts of the United States to deter the development of ballistic missiles. Almost a half-century has elapsed since the United States and the Soviet Union signed the Anti-Ballistic Missile (ABM) Treaty, and almost two decades since the former withdrew. Since withdrawing, the United States has sought to develop and deploy a layered missile defense system to defend against regional threats to U.S. and allied interests abroad and to counter limited threats to the U.S. homeland. As such, missile defense supports key national defense policy objectives. Protecting the U.S. homeland, forces abroad, allies, and partners. Deterring attacks against the United States, its allies, and partners. Assuring allies an strengthening U.S. diplomatic activities in peacetime and crisis. We offer five key findings: 1. The primary benefit of the Ground-based Midcourse Defense (GMD) system is the protection it provides the U.S. homeland against a limited but evolving rogue-state missile threat. While this system has never been tested in combat, it appears thus far to have effectively paced North Korea’s development and deployment of intercontinental ballistic missiles (ICBMs). In the absence of such a defensive capability, the United States would likely have been more heavily exposed to North Korean actions, would have operated at a much higher-risk posture, and would have had less negotiating room with which to navigate coercive tactics and crises. Its allies would have been more concerned about U.S. willingness in time of crisis and war to run the risks of protecting them. The GMD system also serves as a hedge against Iranian breakout. 2. Potential adversaries continue to develop long-range ballistic missiles despite deployment of a U.S. homeland missile defense system. This includes both rogue states and major power rivals whose long-range missile programs predated the deployment of U.S. missile defenses. While North Korea has continued its long-range missile developments and achieved an intercontinental capability, Iran has not yet reached this threshold. The broader proliferation of long-range missiles anticipated in the late 1990s has not materialized. 3. While Russia has used the existence of a U.S. homeland missile defense system as a justification for its substantial and continuing weapon modernization program, neither Russian force modernization nor the limited U.S. homeland missile defense system has altered the strategic balance. Russia has long considered U.S. missile defenses—both theater and homeland—as directed against its strategic forces and as a capability that could rapidly advance, thereby eroding Russian confidence in its nuclear deterrent. Russia’s political and military actions appear excessive and negatively impact areas such as arms control, but they do not undermine the primary benefit of the U.S. system cited in Key Finding 1. 4. China’s expansion and diversification of nuclear and missile forces has been influenced by its concerns about U.S. homeland missile defense, but those concerns are only one of many factors in China’s force planning. Although China’s actions to preserve and expand its assured retaliation prospects have not fundamentally altered the strategic balance, its buildup and lack of transparency about its force modernization goals are troubling. Taken together, the aggregate pattern of China’s modernization activities over the past two decades strongly suggests a concerted effort to develop a modern military force commensurate with its intended geopolitical status. Whatever China’s legacy concerns over the survivability of its strategic nuclear forces, its ability to overwhelm the GMD system appears intact today and will be further strengthened in the years ahead as it continues its long-term modernization program. China’s political and military actions negatively affect U.S. security interests but do not undermine the primary benefit of the U.S. system cited in Key Finding 1. 5. The basic finding that benefits have not so far been undermined by adverse reactions is a function of circumstances that are increasingly in flux. The existing GMD-centered system is under increasing pressure from the pace and scope of North Korean missile deployments. The proposed “layered” system seeks to mitigate this impending capability gap in the near term and to complement future capabilities, such as the Next Generation Interceptor, when they come online. Given the pace of U.S. missile defense developments since 2000, it is possible that adversary advances in capability will outpace the U.S. system’s ability to adapt. Additionally, because this layered system is in principle more readily scaled, it will almost certainly be viewed skeptically by China and Russia. In a context of growing great-power security competition, the Department of Defense (DoD) should consider undertaking a broader net assessment of the U.S., Russian, and Chinese force balance.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Mesoscale Frank–Kasper Crystal Structures from Dendron Assembly by Controlling Core Apex Interactions

Single-component polymeric materials open up a great potential for self-assembly into mesoscale complex crystal structures that are known as Frank-Kasper (FK) phases. Predicting the packing structures of the soft-matter spheres, however, remains a challenge even when the molecular design is precisely known. Here, we investigate the role of the molecules' enthalpic interaction in determining the low-symmetry crystal structures. To this end, we synthesize architecturally asymmetric dendrons by varying their apex functionalities and examine the packing structures of the second-generation (G2) dendritic wedges. Our work shows that weakening the hydrogen bonding of the dendron apex makes the particles softer and smaller, and leads to the formation of various FK structures at lower temperatures, including the new observation of a FK C14 phase in the cone-shaped dendron systems. As a consequence of the free energy balance between the particle's interfacial tension and the chain's stretching, various packing structures are mainly tuned by designing the hydrogen bonding interaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The concept of spin ice graphs and a field theory for their charges

Originally detected in rare earth pyrochlores, spin ice physics is now being artificially extended to a variety of geometries that control collective behavior and exotic properties, making graph theory their proper framework. We relate spin ice notions, such as ice rule, ice manifold, Coulomb phases, charges, and monopoles, to graph-theoretical notions, such as balance, in/out-degrees, and Euler paths. We then propose a field-theoretical treatment in which topological charges and monopoles are the degrees of freedom, while the binary spins are subsumed in an entropic interaction among charges. We show that for a spin ice on a graph in a Gaussian approximation, the kernel of the entropic interaction is the inverse of the graph Laplacian, and we compute screening functions from the graph spectra as Green operators for the screened Poisson problem on a graph. We then apply the treatment to star graphs, tournaments, cycles, and regular spin ice in different dimensions. Our aim is twofold: to set spin ice physics in a proper graph setting, where only topological rather than geometrical notions hold, and to invite graph theorists to contribute their powerful tools to the field of spin ice.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ab Initio Design of High-Entropy Thermal/ Environmental Barrier Coatings

Next generation thermal/environmental barrier coatings (TEBC) require carefully balancing various properties including phase stability, thermal conductivity, coefficient of thermal expansion (CTE), mechanical properties, and resistance against hot corrosion and water vapor recession. This work mainly focuses on rapid design of cost-effective high entropy rare-earth disilicates and aluminum garnets to protect SiC-based ceramic matrix composites and nickel-based superalloys in the hot section of gas turbine engines using density functional theory methods. Our calculations identify several low-cost high entropy TEBC exhibiting ultralow thermal conductivity at 1500 K and desirable CTE while maintaining good mechanical properties, including Er1/2Y3/4Yb3/4Si2O7, Gd1/4Er1/4Y3/4Yb3/4Si2O7, Eu1/4Er1/4Y3/4Yb3/4Si2O7, and (Y1/4Gd1/4Er1/4Yb1/4)3Al5O12. This work also aims to gain fundamental understanding of oxygen diffusion in model disilicates. Minimizing oxidizer (such as water vapor and oxygen) permeability through the EBC layer can significantly decrease the growth rate of thermally grown oxide and extend the service life of the coating system. Oxygen diffusion mechanisms including formation energy of defects under varying oxygen conditions and defect migration energy barriers will be presented.

coefficient of thermal expansion↗

Ground Heat Flux Reconstruction Using Bayesian Uncertainty Quantification Machinery and Surrogate Modeling

Ground heat flux (G 0 ) is a key component of the land-surface energy balance of high-latitude regions. Despite its crucial role in controlling permafrost degradation due to global warming, G 0 is sparsely measured and not well represented in the outputs of global scale model simulation. In this study, an analytical heat transfer model is tested to reconstruct G 0 across seasons using soil temperature series from field measurements, Global Climate Model, and climate reanalysis outputs. The probability density functions of ground heat flux and of model parameters are inferred using available G 0 data (measured or modeled) for snow-free period as a reference. When observed G 0 is not available, a numerical model is applied using estimates of surface heat flux (dependent on parameters) as the top boundary condition. These estimates (and thus the corresponding parameters) are verified by comparing the distributions of simulated and measured soil temperature at several depths. Aided by state-of-the-art uncertainty quantification methods, the developed G 0 reconstruction approach provides novel means for assessing the probabilistic structure of the ground heat flux for regional permafrost change studies.

54 ENVIRONMENTAL SCIENCES↗

Rigidity of MHD equilibria to smooth incompressible ideal motion near resonant surfaces

In ideal MHD, the magnetic flux is advected by the plasma motion, freezing flux-surfaces into the flow. An MHD equilibrium is reached when the flow relaxes and force balance is achieved. We ask what classes of MHD equilibria can be accessed from a given initial state via smooth incompressible ideal motion. It is found that certain boundary displacements are formally not supported. This follows from yet another investigation of the Hahm–Kulsrud–Taylor (HKT) problem, which highlights the resonant behaviour near a rational layer formed by a set of degenerate critical points in the flux-function. When trying to retain the mirror symmetry of the flux-function with respect to the resonant layer, the vector field that generates the volume-preserving diffeomorphism vanishes at the identity to all order in the time-like path parameter.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeling Intercalation Chemistry with Multiredox Reactions by Sparse Lattice Models in Disordered Rocksalt Cathodes

Modern battery materials can contain many elements with substantial site disorder, and their configurational state has been shown to be critical for their performance. The intercalation voltage profile is a critical parameter to evaluate the performance of energy storage. The application of commonly used cluster expansion techniques to model the intercalation thermodynamics of such systems ab initio is challenged by the combinatorial increase in configurational degrees of freedom as the number of species grows. Such challenges necessitate the efficient generation of lattice models without overfitting and proper sampling of the configurational space under the requirement of charge balance in ionic systems. In this work, we introduce a combined approach that addresses these challenges by (1) constructing a robust cluster expansion Hamiltonian using the sparse regression technique, including -norm regularization and structural hierarchy; and (2) implementing semigrand-canonical Monte Carlo to sample charge-balanced ionic configurations using the table-exchange method and an ensemble average approach. These techniques are applied to a disordered rocksalt oxyfluoride (LMNOF) that is part of a family of promising earth-abundant cathode materials. The simulated voltage profile is found to be in good agreement with experimental data and particularly provides a clear demonstration of the and oxygen contributions to the redox potential as a function of content.

25 ENERGY STORAGE↗

Smart Preprocessing & Robust Integration Emulator

To achieve the desired particle size of biomass feedstocks during preprocessing for trouble-free handling and conversion to produce biofuels and bioproducts, the raw materials must undergo a crucial milling process. The particle size of biomass plays a critical role in subsequent biofuel manufacturing, where a larger area-to-volume ratio facilitates efficient synthesis while balancing the impact of moisture on biomass storage. To optimize biofuel production efficiency and overcome these challenges, it is imperative to accurately predict the particle size distribution (PSD) of the biomass in the design of efficient preprocessing systems. The population balance model (PBM), upon empirical calibration and validation, can provide rapid prediction of post-milling PSD of granular biomass. However, PSD has limitations related to mass conservation and the absence of moisture considerations. To overcome these drawbacks, a deep learning model called the enhanced deep neural operator (DNO+) is implemented in the code. This model not only retains the capabilities of the PBM in handling complex mapping functions but also incorporates additional factors influencing the system. By considering various experimental conditions such as sieve size and moisture content, the trained DNO+ model can effectively predict the PSD after milling for any given feed PSD. To further reduce the reliance on experimental data, the PBM is integrated into the DNO+ model, resulting in a physics-informed DNO+ (PIDNO+). The PIDNO+ model addresses the non-conservation of quality exhibited by the PBM while inheriting the advantages of the DNO+ model in considering multiple influencing factors. Moreover, the PIDNO+ model significantly reduces the amount of data required for model training. Both deep learning models, i.e., DNO+ and PIDNO+, are excellent in predictive performance, offering swift and accurate machine learning-based predictions. The use of this code that contains these models will assist in guiding the proper milling equipment selection and operational conditions to achieve the desired biomass particle sizes, ensuring the efficiency of subsequent biofuel and bioproduct production processes.

Xia, Yidong [Idaho National Laboratory (INL), Idah↗

A thermodynamic model of integrated liquid-to-liquid thermoelectric heat pump systems

Thermoelectric (TE) heat pumps (TEHPs) are advantageous for heating and cooling in various applications because of their modularity and simple design. A TEHP system includes the TE modules with p- and n-type materials bonded to substrates, plus heat exchangers, thermal interfaces to the heat exchangers, and heat transfer fluids. Although modeling an individual TE module has been extensively studied, limited studies have reported performance at the larger system-level. Furthermore, no prior study has addressed the impact of temperature-dependent TE material properties (e.g., electric resistivity, thermal conductivity, and Seebeck coefficient) on overall heat-pump-system-level performance. Here, this work presents a mathematical model for TEHP system performance based on Goldsmid's approach for TE material performance, “effective” TE material properties, Gnielinski's correlation for convective heat transfer, and thermal balance theory for a heat exchange network. This combined approach provides an accurate model of the liquid-to-liquid TEHP system. Three different approaches—one empirical, one based on the manufacturer's specifications, and one drawn from the literature—were then used to determine values for TE material properties. The first two methods treated properties as constants, while the last approach treated properties as surface-temperature-based functions. Finally, experimental TEHP data was used to validate the models, all with relative absolute deviations of approximately 10% when predicting heating capacity and 10%–25% when forecasting cooling capacity up to a 30 K surface temperature lift. The results demonstrated that, at the TEHP system level, the TE material properties could be treated as constants, avoiding solver iterations and reducing the performance uncertainty by up to 95%.

42 ENGINEERING↗

Photodriven electron-transfer dynamics in a series of heteroleptic Cu(I)–anthraquinone dyads

Solar fuels catalysis is a promising route to efficiently harvesting, storing, and utilizing abundant solar energy. To achieve this promise, however, molecular systems must be designed with sustainable components that can balance numerous photophysical and chemical processes. To that end, here we report on the structural and photophysical characterization of a series of Cu(I)–anthraquinone-based electron donor–acceptor dyads. The dyads utilized a heteroleptic Cu(I) bis-diimine architecture with a copper(I) bis-phenanthroline chromophore donor and anthraquinone electron acceptor. We characterized the structures of the complexes using x-ray crystallography and density functional theory calculations and the photophysical properties via resonance Raman and optical transient absorption spectroscopy. The calculations and resonance Raman spectroscopy revealed that excitation of the Cu(I) metal-to-ligand charge-transfer (MLCT) transition transfers the electron to a delocalized ligand orbital. The optical transient absorption spectroscopy demonstrated that each dyad formed the oxidized copper–reduced anthraquinone charge-separated state. Unlike most Cu(I) bis-phenanthroline complexes where increasingly bulky substituents on the phenanthroline ligands lead to longer MLCT excited-state lifetimes, here, we observe a decrease in the long-lived charge-separated state lifetime with increasing steric bulk. The charge-separated state lifetimes were best explained in the context of electron-transfer theory rather than with the energy gap law, which is typical for MLCT excited states, despite the complete conjugation between the phenanthroline and anthraquinone moieties.

14 SOLAR ENERGY↗

Analysis of Transformer Magnetizing Reactance Using Describing Function in Direct Power Control of Back-to-Back Modular Multilevel Converter with Advanced Grid Support

This paper presents a Port Controlled Hamiltonian based direct power control architecture for a back-to-back modular multilevel converter system connecting two ac sources at different frequencies. The system features advanced grid support functionalities based on IEEE 1547-2018, implemented on the inverter side. The rectifier side controller ensures reference following for active and/or reactive powers and maintains the commanded dc bus voltage. The inverter side controller ensures power command following for active and reactive powers.The proposed control architecture is designed to suppress second harmonic oscillations in powers during unbalanced grid voltage sags by dynamically adjusting the currents on each ac side. This also ensures effective elimination of any second harmonic oscillations in the equivalent dc bus voltage. Validation is performed on an OPAL-RT real-time platform with case studies on unbalanced and balanced sags, demonstrating the controller's effectiveness during real time implementation. A reduced-scale laboratory prototype further verifies these case studies, with experimental results for balanced sags due to grid simulator limitations. The results confirm the robustness and efficiency of the proposed control strategy in ensuring stable and reliable operation under various grid conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electrochemical Corrosion and Catalysis Dynamics of Tin Oxide during Water Oxidation

Metal oxide corrosion severely limits anodic electrocatalysis, particularly at high potentials in acidic environments, where degradation pathways remain poorly defined. This study establishes explicit connections between corrosion and electrocatalysis on tin oxide during water oxidation by examining the roles of lattice defects, reactive oxygen species, interfacial pH variations, and speciation of corroded tin in acid. We first demonstrate the presence of structural defects such as oxygen vacancies and substoichiometric Sn(II) species by integrating electron paramagnetic resonance spectroscopy, ultraviolet photoelectron spectroscopy, and Mott–Schottky analysis. Kohn–Sham density functional theory calculations reveal that explicit water structures thermodynamically stabilize reaction intermediates and lower reaction overpotentials. Moreover, we propose that water dissociation leads to hydrogen-bonding networks formed by H* and OH* intermediates, which may span the entire catalyst surface and decrease the interfacial pH to drive corrosion. In contrast, the electrochemical generation of reactive oxygen species is shown to play a minor role in catalyst corrosion during water oxidation using inductively coupled plasma mass spectrometry coupled with selective chemical scavengers. Square-wave voltammetry combined with rotating ring-disk electrodes is used to reveal that under open-circuit conditions, only Sn(IV) cations chemically dissolve from tin oxide, while both Sn(IV) and Sn(II) species electrochemically corrode during water oxidation. Our results unveil a dynamic and complicated interplay between corrosive and catalytic pathways on metal oxide electrocatalysts: a decrease in interfacial pH due to water oxidation exacerbates Sn(II)/Sn(IV) corrosion. Subsequently, the electrochemical corrosion of Sn(II)/Sn(IV) facilitates product formation from lattice oxygen, while the redeposition of corroded Sn(II) as Sn(IV) can enable oxygen exchange with water. By elucidating the roles of defects and interfacial chemistry, this work provides a roadmap for engineering improved electrocatalysts that balance activity and stability, a critical step toward scalable and durable energy technologies.

36 MATERIALS SCIENCE↗

Distinctive features of fluorescence and waveguides in magnesium aluminate spinel crystals driven by structural discrepancy

Transparent polycrystalline ceramics are of significant importance for a wide range of scientific and industrial applications. Developing a deeper understanding of their thermodynamic behavior is essential for achieving their maximum output performance in technological applications. This study provides a systematic investigation into the thermal excitation-induced fluorescence kinetics and waveguide characteristics of Magnesium Aluminate Spinel (MgAl 2 O 4 ) single crystals, with a focus on the intricate relationship between structure and properties. High-temperature extreme environments through irradiation with swift heavy ions 645.0 MeV Xe and 352.8 MeV Fe ions were created; the atomic deposition energy threshold (E th ) associated with disorder morphologies was assessed between 0.91 and 0.99 eV atom –1 . The track prediction model was developed to support the theoretical prediction of track formation. Electronic energy loss (E ele ) disrupts the balance of the initial structure through the thermal spike effect, leading to the formation of absorption-related F and F + color centers. These defects enhance photoluminescence in the visible spectrum and result in an effective modulation of the intrinsic bandgap. Moreover, as ion beams penetrate into the material, the uneven damage distribution induces the formation of waveguide structures. In conclusion, these findings provide valuable insights into the fabrication of functional devices through irradiation technologies and the structural changes of MgAl 2 O 4 at high temperatures within extreme environments.

36 MATERIALS SCIENCE↗

Thermo-hydraulic steam pipe models for district heating simulations: Simplifications to balance accuracy and simulation speed

Steam piping networks are essential for optimizing performance in industrial processes and district heating systems. However, dynamic models that balance thermo-hydraulic accuracy with computational efficiency remain limited. In response, this paper presents a new discretized steam pipe model based on the plug flow approach, capturing key thermo-hydraulic behaviors while simplifying steam phase change processes. Implemented in Modelica, the model accurately calculates temperature and pressure distributions along steam pipelines. To improve computational efficiency for district-scale simulations, five model simplifications are introduced: lumped thermo-hydraulic functions, empirical correlations, fluid state approximations, steady-state dynamics and inclusion of flow derivatives. These simplified models achieve 85%-98% accuracy in predicting pressure drop and condensation losses, including dynamic condensate behavior during pipe warm-up—a factor often overlooked in existing models. The models support diverse network configurations, scaling effectively to systems with multiple distribution pipes and connected building loads. Discrete models provide detailed insights but exhibit a cubic increase in simulation time as the network scales by N connected building O(N 2.42 ). In contrast, lumped models simulate 10–28 times faster than discrete, offering quadratic scaling of simulation time O(N 1.73 ). However, they still require 6 times more computation time than a lossless network, highlighting the inherent computational challenges of modeling compressible fluid flow. In conclusion, the steady-state lumped variant, with its near-linear scalability in computational time O(N 1.01 ), emerges as an efficient solution for preliminary design evaluations and extensive parametric studies.

15 GEOTHERMAL ENERGY↗

Bayesian Active Learning for Scanning Probe Microscopy: From Gaussian Processes to Hypothesis Learning

Recent progress in machine learning methods and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs) have propelled automated and autonomous microscopies to the forefront of attention of the scientific community. However, enabling automated microscopy requires the development of task-specific machine learning methods, understanding the interplay between physics discovery and machine learning, and fully defined discovery workflows. This, in turn, requires balancing the physical intuition and prior knowledge of the domain scientist with rewards that define experimental goals and machine learning algorithms that can translate these to specific experimental protocols. Here, we discuss the basic principles of Bayesian active learning and illustrate its applications for SPM. We progress from the Gaussian process as a simple data-driven method and Bayesian inference for physical models as an extension of physics-based functional fits to more complex deep kernel learning methods, structured Gaussian processes, and hypothesis learning. These frameworks allow for the use of prior data, the discovery of specific functionalities as encoded in spectral data, and exploration of physical laws manifesting during the experiment. Here, the discussed framework can be universally applied to all techniques combining imaging and spectroscopy, SPM methods, nanoindentation, electron microscopy and spectroscopy, and chemical imaging methods and can be particularly impactful for destructive or irreversible measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A new generation of effective core potentials: Selected lanthanides and heavy elements

Here, we construct correlation-consistent effective core potentials (ccECPs) for a selected set of heavy atoms and ƒ-elements that are of significant current interest in materials and chemical applications, including Y, Zr, Nb, Rh, Ta, Re, Pt, Gd, and Tb. As is customary, ccECPs consist of spin orbit averaged relativistic effective potential (AREP) and effective spin-orbit (SO) terms. For the AREP part, our constructions are carried out within a relativistic coupled-cluster framework while also taking into account objective function one-particle characteristics for improved convergence in optimizations. The transferability is adjusted using binding curves of hydride and oxide molecules. We address the difficulties encountered with ƒ-elements, such as the presence of large cores and multiple near-degeneracies of excited levels. For these elements, we construct ccECPs with core valence partitioning that includes 4ƒ-subshell in the valence space. The developed ccECPs achieve an excellent balance between accuracy, size of the valence space, and transferability and are also suitable to be used in plane wave codes with reasonable energy cutoffs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗