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DOE OSTI2024

The Average Spectrum Norm and Near-Optimal Tensor Completion

We propose the average spectrum norm to study the minimum number of measurements required to approximate a multidimensional array (i.e., sample complexity) via low-rank tensor recovery. Our focus is on the tensor completion problem, where the aim is to estimate a multiway array using a subset of tensor entries corrupted by noise. Our average spectrum norm-based analysis provides near-optimal sample complexities, exhibiting dependence on the ambient dimensions and rank that do not suffer from exponential scaling as the order increases.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Measurement and Analysis of Beam Phase-Space Distributions for the Fermilab Muon Campus Accelerator Complex

The Muon g-2 experiment at Fermilab is tasked with measuring the muon’s anomalous magnetic moment with high precision. Since the experiment requires large amounts of muons, it is imperative to systematically study the behavior of the beam along the transport line. Unfortunately, the available diagnostics only provide beam information in X-Y space. For a complete evaluation, information of the phase-space is required. This paper demonstrates a technique to measure the beam phase-direction distribution by using a set of beam profiles. First, we establish the theoretical framework that describes the principle of the technique. Next, we apply the technique at four different locations along the accelerator delivery line. Finally, we compare our findings to predictions from tracking simulations.

43 PARTICLE ACCELERATORS↗

DOE OSTI2019

Energy Decomposition Analysis for Interactions of Radicals: Theory and Implementation at the MP2 Level with Application to Hydration of Halogenated Benzene Cations and Complexes between CO 2 -· and Pyridine and Imidazole

To study intermolecular interactions involving radicals at the correlated level, the energy decomposition analysis scheme for second-order Møller-Plesset perturbation theory based on absolutely localized molecular orbitals (ALMO-MP2-EDA) is generalized to unrestricted and restricted open-shell MP2. The benefit of restricted open-shell MP2 is that it can provide accurate binding energies for radical complexes where density functional theory can be error-prone due to delocalization errors. As a model application, the open-shell ALMO-MP2-EDA is applied to study the first solvation step of halogenated benzene radical cations, where both halogen- and hydrogen-bonded isomers are possible. We determine that the lighter halogens favor the hydrogen-bonded form, while the iodine-substituted species prefers halogen bonding due to larger polarizability and charge transfer at the halogen. As a second application, relevant to the activation of CO 2 in photoelectrocatalysis, complexes of CO 2 -· interacting with both pyridine and imidazole are analyzed with ALMO-MP2-EDA. The results reveal the importance of charge transfer into the π* orbital of the heterocycle in controlling the stability of the carbamate binding mode, which is favored for pyridine but not for imidazole.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

The roles of 4f- and 5f-orbitals in bonding: A magnetochemical, crystal field, density functional theory, and multi-reference wavefunction study

The electronic structures of 4f 3 /5f 3 Cp" 3 M and Cp" 3 M·alkylisocyanide complexes, where Cp" is 1,3-bis-(trimethylsilyl)cyclopentadienyl, are explored with a focus on the splitting of the f-orbitals, which provides information about the strengths of the metal–ligand interactions. While the f-orbital splitting in many lanthanide complexes has been reported in detail, experimental determination of the f-orbital splitting in actinide complexes remains rare in systems other than halide and oxide compounds, since the experimental approach, crystal field analysis, is generally significantly more difficult for actinide complexes than for lanthanide complexes. In this study, a set of analogous neodymium(III) and uranium(III) tris-cyclopentadienyl complexes and their isocyanide adducts was characterized by electron paramagnetic resonance (EPR) spectroscopy and magnetic susceptibility. The crystal field model was parameterized by combined fitting of EPR and susceptibility data, yielding an accurate description of f-orbital splitting. The isocyanide derivatives were also studied using density functional theory, resulting in f-orbital splitting that is consistent with crystal field fitting, and by multi-reference wavefunction calculations that support the electronic structure analysis derived from the crystal-field calculations. The results highlight that the 5f-orbitals, but not the 4f-orbitals, are significantly involved in bonding to the isocyanide ligands. The main interaction between isocyanide ligand and the metal center is a σ-bond, with additional 5f to π* donation for the uranium complexes. As a result, while interaction with the isocyanide π*-orbitals lowers the energies of the 5f xz 2 and 5f yz 2- orbitals, spin–orbit coupling greatly reduces the population of 5f xz 2 and 5f yz 2 in the ground state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Evaluation of global teleconnections in CMIP6 climate projections using complex networks

In climatological research, the evaluation of climate models is one of the central research subjects. As an expression of large-scale dynamical processes, global teleconnections play a major role in interannual to decadal climate variability. Their realistic representation is an indispensable requirement for the simulation of climate change, both natural and anthropogenic. Therefore, the evaluation of global teleconnections is of utmost importance when assessing the physical plausibility of climate projections. We present an application of the graph-theoretical analysis tool δ-MAPS, which constructs complex networks on the basis of spatio-temporal gridded data sets, here sea surface temperature and geopotential height at 500 hPa. Complex networks complement more traditional methods in the analysis of climate variability, like the classification of circulation regimes or empirical orthogonal functions, assuming a new non-linear perspective. While doing so, a number of technical tools and metrics, borrowed from different fields of data science, are implemented into the δ-MAPS framework in order to overcome specific challenges posed by our target problem. Those are trend empirical orthogonal functions (EOFs), distance correlation and distance multicorrelation, and the structural similarity index. δ-MAPS is a two-stage algorithm. In the first place, it assembles grid cells with highly coherent temporal evolution into so-called domains. In a second step, the teleconnections between the domains are inferred by means of the non-linear distance correlation. We construct 2 unipartite and 1 bipartite network for 22 historical CMIP6 climate projections and 2 century-long coupled reanalyses (CERA-20C and 20CRv3). Potential non-stationarity is taken into account by the use of moving time windows. The networks derived from projection data are compared to those from reanalyses. Our results indicate that no single climate projection outperforms all others in every aspect of the evaluation. But there are indeed models which tend to perform better/worse in many aspects. Differences in model performance are generally low within the geopotential height unipartite networks but higher in sea surface temperature and most pronounced in the bipartite network representing the interaction between ocean and atmosphere.

58 GEOSCIENCES↗

DOE OSTI2017

Fractal Analysis of Visual Search Activity for Mass Detection During Mammographic Screening

Purpose: The objective of this study was to assess the complexity of human visual search activity during mammographic screening using fractal analysis and to investigate its relationship with case and reader characteristics. Methods: The study was performed for the task of mammographic screening with simultaneous viewing of four coordinated breast views as typically done in clinical practice. Eye-tracking data and diagnostic decisions collected for 100 mammographic cases (25 normal, 25 benign, 50 malignant) and 10 readers (three board certified radiologists and seven radiology residents), formed the corpus data for this study. The fractal dimension of the readers’ visual scanning patterns was computed with the Minkowski–Bouligand box-counting method and used as a measure of gaze complexity. Individual factor and group-based interaction ANOVA analysis was performed to study the association between fractal dimension, case pathology, breast density, and reader experience level. The consistency of the observed trends depending on gaze data representation was also examined. Results: Case pathology, breast density, reader experience level, and individual reader differences are all independent predictors of the visual scanning pattern complexity when screening for breast cancer. No higher order effects were found to be significant. Conclusions: Fractal characterization of visual search behavior during mammographic screening is dependent on case properties and image reader characteristics.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Structural and functional analysis of the human cone‐rod homeobox transcription factor

Abstract The cone‐rod homeobox (CRX) protein is a critical K50 homeodomain transcription factor responsible for the differentiation and maintenance of photoreceptor neurons in the vertebrate retina. Mutant alleles in the human gene encoding CRX result in a variety of distinct blinding retinopathies, including retinitis pigmentosa, cone‐rod dystrophy, and Leber congenital amaurosis. Despite the success of using in vitro biochemistry, animal models, and genomics approaches to study this clinically relevant transcription factor over the past 25 years since its initial characterization, there are no high‐resolution structures in the published literature for the CRX protein. In this study, we use bioinformatic approaches and small‐angle X‐ray scattering (SAXS) structural analysis to further understand the biochemical complexity of the human CRX homeodomain (CRX‐HD). We find that the CRX‐HD is a compact, globular monomer in solution that can specifically bind functional cis‐regulatory elements encoded upstream of retina‐specific genes. This study presents the first structural analysis of CRX, paving the way for a new approach to studying the biochemistry of this protein and its disease‐causing mutant protein variants.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Symmetry in Seeded Metal Nanocrystal Growth

Symmetry underpins the structure and function of the world around us and is also captured in modern nanomaterials, where changing the symmetry of a nanocrystal or the interparticle spacing and orientation of nanocrystal building blocks in a superlattice can give new function. However, the synthesis and assembly of nanocrystals have been limited largely to simple compositions and structures. It remains a grand challenge to achieve nanocrystals with compositional and structural complexity while maintaining the monodispersity required for their use. This Account will illustrate through recent examples that seeded methods enable the synthesis of compositionally and structurally complex multimetallic crystals with defined and predictable symmetries for applications in plasmonics and catalysis. This outcome arises because the barrier for heterogeneous nucleation (i.e., seeded) is lower than that of homogeneous nucleation, where seeds can serve as preferential sites for the growth of complex structures and crystal phases. Our analysis begins by considering metal overgrowth from single-crystalline seeds of different shapes and symmetries, where the kinetics of adatom addition to seeds relative to their diffusion across seeds accounts for the expressed nanocrystal shapes. These results are then compared to overgrowth from seeds with different internal structures (i.e., planar defects), where the relationships between nanocrystal size and volumetric strain energy and surface energy are discussed. A major finding from this analysis is that often the underlying symmetry of seeds can be predictably transferred to the final crystals during overgrowth processes. Consequences of this finding are the predictable syntheses of crystals with different hierarchies akin to snowcrystals as well as nanocrystals with complex compositions (e.g., quaternary nanoparticles). Yet, there are subtle aspects to seeded growth that pave a path toward examples where nanocrystal symmetry has been reduced compared to the original seeds in a controlled manner. As we found, both the concentrations of metal precursors and capping agents can impact whether symmetry is transferred or reduced during overgrowth. Examples from our laboratory will be placed in context to other reported strategies for symmetry breaking. As will be argued, understanding what conditions favor symmetry preservation versus symmetry reduction during seeded crystal growth is central to accessing next-generation crystal forms. The Account concludes by outlining synthetic challenges associated with forming nanoscale heterostructures with precise 3-D placement of different materials within a given nanocrystal as well as facet control within different material domain and interface engineering. Furthermore, we envision meeting these challenges through regioselective and chemoselective seeded syntheses for which a foundation is outlined herein.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Chemical assembly of the heteronuclear pivalate complex with the Li{sup I} and Fe{sup III} ions

The heteronuclear complex [Fe{sub 4}Li{sub 2}(O){sub 2}(Piv)10(H{sub 2}O){sub 2}] (1, Piv is the pivalic acid anion) was obtained by refluxing Fe{sup III} pivalates with Li{sup I} pivalates in toluene and isolated as the 1•PhCH{sub 3} solvate with a toluene molecule. According to X-ray diffraction data, complex 1 contains the {Fe_4Li_2O_2} core. The Mössbauer spectroscopy data indicate that the core comprises para magnetic Fe{sup III} ions in the high-spin state located in the symmetric octahedral environment of oxygen atoms. Thermolysis of 1 studied by simultaneous thermal analysis demonstrated thermal stability of the complex up to 225 °С. The main end product of thermolysis at 600 °С is the mixed oxide LiFe{sub 5}O{sub 8}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Influence of Rare-Earth Ion Radius on Metal–Metal Charge Transfer in Trinuclear Mixed-Valent Complexes

We report the synthesis and characterization of a highly conjugated bisferrocenyl pyrrolediimine ligand, Fc 2 PyrDIH (1), and its trinuclear complexes with rare earth ions—(Fc 2 PyrDI)M(N(TMS) 2 ) 2 (2-M, M = Sc, Y, Lu, La). Crystal structures, NMR spectra, and UV/Vis-NIR data are presented. The latter are in good agreement with DFT calculations, illuminating the impact of the rare earth ionic radius on NIR charge transfer excitations. For [2-Sc] + , the charge transfer is at 11500 cm -1 , while for [2-Y] + only a d-d transition at 8000 cm -1 is observed. Lu has an ionic radius in between Sc and Y, and the [2-Lu] + complex exhibits both transitions. From TDDFT analysis we assign the 11500 cm -1 transition as a mixture of MLCT and MMCT, rather than pure metal-to-metal CT, because it has significant ligand character. Typically, the ferrocenes have high rotational freedom in bis-ferrocenyl mixed valent complexes. However, in the present (Fc 2 PyrDI)M(N(TMS) 2 ) 2 complexes, ligand-ligand repulsions lock the rotational freedom, so that rare earth ionic radius-dependent geometric differences increasingly influence orbital overlap as the ionic radius falls. The Marcus-Hush coupling constant HAB trends as: [2-Sc] + >[2-Lu] + >[2-Y] +

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Comparative Analysis of Model Predictive Control and MPC-Informed Rule-Based Control for Thermal Storage Operation in Ultra-Low Temperature 4th Generation District Heating Networks

The integration of thermal storage and heat pumps in district heating networks (DHNs) can significantly enhance operational flexibility and energy efficiency; however, the practical deployment of advanced control strategies is often hindered by forecasting requirements and computational complexity. This study presents a comparative analysis of thermal storage control strategies in an ultra-low-temperature fourth-generation DHN, focusing on the development of a simplified rule-based control (RBC) explicitly informed by Model Predictive Control (MPC) behavior. The proposed methodology systematically analyzes the charging and discharging decisions of an MPC-controlled system under ideal forecasting conditions and extracts recurrent control patterns as a function of key system variables, including outdoor temperature, thermal demand, and electricity price. These patterns are translated into a set of structured time- and condition-based rules, resulting in an MPC-informed RBC that embeds predictive insights while preserving implementation simplicity and operational transparency. The approach is validated on a realistic mixed-use urban district in Denver, Colorado, USA, equipped with a centralized air-source heat pump, distributed water-to-water heat pumps, and a central thermal storage unit. Results show that the tuned RBC attains approximately 96% of ideal MPC economic performance (-27% of costs), preserves values of technical and environmental indicators (reduction only of 2-3%), and substantially reduces complexity. Sensitivity analyses further demonstrate the robustness of the RBC under varying operational conditions (i.e., ambient temperature, electricity price). Overall, the study demonstrates that MPC-informed rule-based control represents an effective trade-off between control performance and real-world applicability, enabling the integration of additional system components while maintaining simplicity, robustness, and ease of implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Metal–organic coordination architectures of tetrazole heterocycle ligands bearing acetate groups: Synthesis, characterization and magnetic properties

Two new coordination complexes with tetrazole heterocycle ligands bearing acetate groups, [Co(L){sub 2}]{sub n} (1) and [Co{sub 3}(L){sub 4}(N{sub 3}){sub 2}·2MeOH]{sub n} (2) (L=tetrazole-1-acetate) have been synthesized and structurally characterized. Single crystal structure analysis shows that the cobalt-complex 1 has the 3D 3,6-connected (4{sup 2}.6){sub 2}(4{sup 4}.6{sup 2}.8{sup 8}.10)-ant topology. By introducing azide in this system, complex 2 forms the 2D network containing the [Co{sub 3}] units. And the magnetic properties of 1 and 2 have been studied. - Graphical abstract: The synthesis, crystal structure, and magnetic properties of the new coordination complexes with tetrazole heterocycle ligands bearing acetate groups are reported. - Highlights: • Two novel Cobalt(II) complexes with tetrazole acetate ligands were synthesized. • The magnetic properties of two complexes were studied. • Azide as co-ligand resulted in different structures and magnetic properties. • The new coordination mode of tetrazole acetate ligand was obtained.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Transmutation approximations for the application of hybrid Monte Carlo/deterministic neutron transport to shutdown dose rate analysis

In fusion energy systems (FES) neutrons born from burning plasma activate system components. The photon dose rate after shutdown from resulting radionuclides must be quantified. This shutdown dose rate (SDR) is calculated by coupling neutron transport, activation analysis, and photon transport. The size, complexity, and attenuating configuration of FES motivate the use of hybrid Monte Carlo (MC)/deterministic neutron transport. The Multi-Step Consistent Adjoint Driven Importance Sampling (MS-CADIS) method can be used to optimize MC neutron transport for coupled multiphysics problems, including SDR analysis, using deterministic estimates of adjoint flux distributions. When used for SDR analysis, MS-CADIS requires the formulation of an adjoint neutron source that approximates the transmutation process. In this work, transmutation approximations are used to derive a solution for this adjoint neutron source. It is shown that these approximations are reasonably met for typical FES neutron spectra and materials over a range of irradiation scenarios. When these approximations are met, the Groupwise Transmutation (GT)-CADIS method, proposed here, can be used effectively. GT-CADIS is an implementation of the MS-CADIS method for SDR analysis that uses a series of single-energy-group irradiations to calculate the adjoint neutron source. For a simple SDR problem, GT-CADIS provides speedups of 200 100 relative to global variance reduction with the Forward-Weighted (FW)-CADIS method and 9 ± 5 • 10 4 relative to analog. As a result, this work shows that GT-CADIS is broadly applicable to FES problems and will significantly reduce the computational resources necessary for SDR analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Artificial intelligence in cryo-EM protein particle picking: recent advances and remaining challenges

Abstract Cryo-electron microscopy (cryo-EM) has revolutionized structural biology by enabling the determination of high-resolution 3-Dimensional (3D) structures of large biological macromolecules. Protein particle picking, the process of identifying individual protein particles in cryo-EM micrographs for building protein structures, has progressed from manual and template-based methods to sophisticated artificial intelligence (AI)-driven approaches in recent years. This review critically examines the evolution and current state of cryo-EM particle picking methods, with an emphasis on the impact of AI. We conducted a comparative evaluation of popular AI-based particle picking methods, using both general machine learning metrics and specific cryo-EM structure determination metrics. This analysis involved constructing the 3D density map from the picked protein particles and assessing the obtained resolution and particle orientation diversity, underscoring the significant impact of AI on cryo-EM particle picking. Despite the advancements, we also identified key obstacles, such as handling complex micrographs with small proteins. The analysis provides insights into the future development of more sophisticated and fully automated AI methods in cryo-EM particle recognition.

Biochemistry & Molecular Biology↗

DOE OSTI2020

Experimental determination of electron attenuation lengths in complex materials by means of epitaxial film growth: advantages and challenges

Accurate electron attenuation lengths are of critical importance in using electron spectroscopic methods to quantitatively characterize complex materials. Here we show that analysis of core-level and valence-band x-ray photoelectron spectra excited with monochromatic AlK? x-rays from the substrate and measured as a function of film thickness can be used to determine electron attenuation lengths in epitaxial SrTiO3 films on Ge(001). Closely lattice-matched epitaxial heterojunctions are ideal systems for determining attenuation lengths provided the films grow in a layer-by-layer fashion, leading to atomically flat surfaces, and the buried interfaces are atomically abrupt. In principle, either the rate of attenuation of substrate peak intensities or the rate of increase of film peak intensities can be used for this purpose. However, we find that structural nonuniformities in the films reduce the accuracy of electron attenuation lengths determined from photoelectrons that originate within the films. A more reliable source of information is found in photoelectrons from the substrate which traverse the film. By using the energy dependence of calculated electron attenuation lengths from the NIST database in combination with Ge 3d core and Ge-derived valence band intensities, we determine electron attenuation length as a function of kinetic energy for SrTiO3.

Chambers, Scott A.↗

DOE OSTI2016

First comprehensive structural and biophysical analysis of MAPK13 inhibitors targeting DFG-in and DFG-out binding modes

Background: P38 MAP kinases are centrally involved in mediating extracellular signaling in various diseases. While much attention has previously been focused on the ubiquitously expressed family member MAPK14 (p38α), recent studies indicate that family members such as MAPK13 (p38δ) display a more selective cellular and tissue expression and might therefore represent a specific kinase to target in certain diseases. Methods: To facilitate the design of potent and specific inhibitors, we present in this paper the structural, biophysical, and functional characterization of two new MAPK13-inhibitor complexes, as well as the first comprehensive structural, biophysical, and functional analysis of MAPK13 complexes with four different inhibitor compounds of greatly varying potency. Results: These inhibitors display IC 50 values either in the nanomolar range or micromolar range (> 800-fold range). The nanomolar inhibitors exhibit much longer ligand-enzyme complex half-lives compared to the micromolar inhibitors as measured by biolayer interferometry. Crystal structures of the MAPK13 inhibitor complexes reveal that the nanomolar inhibitors engage MAPK13 in the DFG-out binding mode, while the micromolar inhibitors are in the DFG-in mode. Detailed structural and computational docking analyses suggest that this difference in binding mode engagement is driven by conformational restraints imposed by the chemical structure of the inhibitors, and may be fortified by an additional hydrogen bond to MAPK13 in the nanomolar inhibitors. Conclusions: These studies provide a structural basis for understanding the differences in potency exhibited by these inhibitors. General significance: They also provide the groundwork for future studies to improve specificity, potency, pharmacodynamics, and pharmacokinetic properties.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

[Sb{sub 4}Au{sub 4}Sb{sub 4}]{sup 2−}: A designer all-metal aromatic sandwich

We report on the computational design of an all-metal aromatic sandwich, [Sb{sub 4}Au{sub 4}Sb{sub 4}]{sup 2−}. The triple-layered, square-prismatic sandwich complex is the global minimum of the system from Coalescence Kick and Minima Hopping structural searches. Following a standard, qualitative chemical bonding analysis via canonical molecular orbitals, the sandwich complex can be formally described as [Sb{sub 4}]{sup +}[Au{sub 4}]{sup 4−}[Sb{sub 4}]{sup +}, showing ionic bonding characters with electron transfers in between the Sb{sub 4}/Au{sub 4}/Sb{sub 4} layers. For an in-depth understanding of the system, one needs to go beyond the above picture. Significant Sb → Au donation and Sb ← Au back-donation occur, redistributing electrons from the Sb{sub 4}/Au{sub 4}/Sb{sub 4} layers to the interlayer Sb–Au–Sb edges, which effectively lead to four Sb–Au–Sb three-center two-electron bonds. The complex is a system with 30 valence electrons, excluding the Sb 5s and Au 5d lone-pairs. The two [Sb{sub 4}]{sup +} ligands constitute an unusual three-fold (π and σ) aromatic system with all 22 electrons being delocalized. An energy gap of ∼1.6 eV is predicted for this all-metal sandwich. The complex is a rare example for rational design of cluster compounds and invites forth-coming synthetic efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗