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At least 1,063 records · Page 59

Competition between Hydrogen and Chalcogen Bonding in Homodimers of Chalcogen Hydrides (H 2 X) 2 , X = O, S, Se, Te

The structural and chemical bonding motifs manifested by the competition between hydrogen and chalcogen bonding in the homodimers of chalcogen hydrides (H 2 X) 2 , where X = O, S, Se, Te have been characterized using high-level electronic structure calculations and analysis of the electron density based on Quasi-atomic orbital (QUAO) and the Symmetry-adapted perturbation theory (SAPT) methods. The QUAO analysis clearly identifies a three-center interaction responsible for either hydrogen or chalcogen bonds: in the former, the σ-bond connecting the donor and hydrogen atom participating in the hydrogen bond interacts with the lone pair on the nucleophile acceptor via the hydrogen atom, while in the latter this same σ-bond interacts with the nucleophile lone pair via the donor chalcogen. The number of minimum energy structures increase dramatically from one for (H 2 O) 2 , three for (H 2 S) 2 , four for (H 2 Se) 2 , and finally six for (H 2 Te) 2 . Furthermore, the emergence of the chalcogen-bonded arrangements appears for (H 2 S) 2 with their subsequent energetic stabilization over the hydrogen-bonded minima manifesting in (H 2 Se) 2 and (H 2 Te) 2 . In particular, one of the (H 2 S) 2 , two of the (H 2 Se) 2 , and three of the (H 2 Te) 2 dimers are chalcogen bonded. Induction plays a small but important role in stabilizing hydrogen over chalcogen-bonded structures, while dispersion is more important for chalcogen bonds.

Chemical structure↗

Stability Frontiers in the AM 6 X 6 Kagome Metals: The Ln Nb 6 Sn 6 ( Ln :Ce–Lu,Y) Family and Density-Wave Transition in LuNb 6 Sn 6

The kagome motif is a versatile platform for condensed matter physics, hosting rich interactions between magnetic, electronic, and structural degrees of freedom. In recent years, the discovery of a charge density wave (CDW) in the AV 3 Sb 5 superconductors and structurally-derived bond density waves (BDW) in FeGe and ScV 6 Sn 6 have stoked the search for new kagome platforms broadly exhibiting density wave (DW) transitions. Here, in this work, we evaluate the known AM 6 X 6 chemistries and construct a stability diagram that summarizes the structural relationships among the >125 member family. Subsequently, we introduce our discovery of the broader LnNb 6 Sn 6 (Ln:Ce–Nd,Sm,Gd–Tm,Lu,Y) family of kagome metals and an analogous DW transition in LuNb 6 Sn 6 . Our X-ray scattering measurements clearly indicate a (1/3, 1/3, 1/3) ordering wave vector (√$\bar{3}$ x √$\bar{3}$ x $3$ superlattice) and diffuse scattering on half-integer L-planes. Our analysis of the structural data supports the “rattling mode” DW model proposed for ScV 6 Sn 6 and paints a detailed picture of the steric interactions between the rare-earth filler element and the host Nb–Sn kagome scaffolding. We also provide a broad survey of the magnetic properties within the HfFe 6 Ge 6 -type LnNb 6 Sn 6 members, revealing a number of complex antiferromagnetic and metamagnetic transitions throughout the family. This work integrates our new LnNb 6 Sn 6 series of compounds into the broader AM 6 X 6 family, providing new material platforms and forging a new route forward at the frontier of kagome metal research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding Interfacial Block Copolymer Structure and Dynamics

Here, block copolymer (BCP) structure and dynamics were studied using small-angle neutron scattering (SANS), neutron spin echo (NSE) spectroscopy, and molecular dynamics (MD) simulations to obtain a fundamental understanding of the impact of an interfacial block on chain dynamics. A glassy block acted as the interface, and the dynamics of a rubbery block was studied. The rubbery block was protonated near the interface in one sample and near the chain end in another sample to observe the interfacial effect on the rubbery polymer. Analysis of the structure and dynamics revealed that the interfacial rubbery block was confined in layered morphologies and exhibited much slower dynamics than the chain-end rubbery block that was dispersed in the rubbery matrix. The interfacial rubbery block showed weaker dynamical relaxation than that at the chain end, and it also had critically important length scale dependence. Dynamical slowing was only observed at length scales significantly larger than the characteristic segmental length, and the disparity between interfacial and chain-end dynamics increased with increasing length.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Designing Glass and Crystalline Phases of Metal–Bis(acetamide) Networks to Promote High Optical Contrast

Owing to their high tunability and predictable structures, metal–organic materials offer a powerful platform to study glass formation and crystallization processes and to design glasses with unique properties. In this work, we report a novel series of glass-forming metal–ethylenebis(acetamide) networks that undergo reversible glass and crystallization transitions below 200 °C. The glass-transition temperatures, crystallization kinetics, and glass stability of these materials are readily tunable, either by synthetic modification or by liquid-phase blending, to form binary glasses. Pair distribution function (PDF) analysis reveals extended structural correlations in both single and binary metal–bis(acetamide) glasses and highlights the important role of metal–metal correlations during structural evolution across glass–crystal transitions. Notably, the glass and crystalline phases of a Co–ethylenebis(acetamide) binary network feature a large reflectivity contrast ratio of 4.8 that results from changes in the local coordination environment around Co centers. These results provide new insights into glass–crystal transitions in metal–organic materials and have exciting implications for optical switching, rewritable data storage, and functional glass ceramics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Novel application of the modal strain energy technique for state-of-the-art damping predictions

Structural damping, which measures the energy dissipation of a vibrating structure, is a key modeling input for lightweight structures but is notoriously hard to predict. This work utilizes vibration-based measurements of centimeter-scale coupons and the modal strain energy approach to predict structural damping of a lightly damped structure. The approach was originally validated with panels shorter than a meter in length. This work extends the validation to a 2.75 m beam made of unidirectional and biaxial glass fiber laminates bonded by adhesive. The comparison between three-dimensional finite element model predictions and full-scale experimental measurements of damping show an average error of 5.2% for the first five modes. Additionally, the modal strain energy approach is newly applied with a one-dimensional geometrically exact beam theory model and a two-dimensional sectional analysis solver. This beam approach accurately predicts the damping behavior of the first bending modes but loses accuracy for higher order modes that are dominated by three-dimensional effects. This novel approach provides faster simulations while allowing arbitrary beam cross sections. The paper also investigates traditional and high-force dynamic mechanical analysis to measure structural damping of coupons. Both alternatives show significant errors in attempted validation against the theoretical thermoelastic damping of aluminum coupons.

17 WIND ENERGY↗

Virulence and Genetic Diversity of Puccinia spp., Causal Agents of Rust on Switchgrass (Panicum virgatum L.) in the USA

Switchgrass (Panicum virgatum L.) is an important cellulosic biofuel grass native to North America. Rust, caused by Puccinia spp. is the most predominant disease of switchgrass and has the potential to impact biomass conversion. In this study, virulence patterns were determined on a set of 38 switchgrass genotypes for 14 single-spore rust isolates from 14 field samples collected in seven states. Single nucleotide polymorphism (SNP) variation was also assessed in 720 sequenced cloned amplicons representing 654 base pairs of the elongation factor 1-α gene from the field samples. Five major haplotypes were identified differing by 11 out of the 39 SNP positions identified. STRUCTURE, Principal Coordinate Analysis, and phylogenetic analyses divided the rust population into two genetic clusters. Virginia and Georgia had the highest and lowest rust genetic diversity, respectively. Only nine accessions showed a differential disease response between the 14 isolates, allowing the identification of eight races, differing by 1–3 virulence factors. Overall, the results suggested clonal reproduction of the pathogen and a North–South differentiation via local adaptation. However, similar haplotypes and races were also recovered from several states, suggesting migration events, and highlighting the need to further investigate the switchgrass rust population structure and evolution in the USA.

Bahri, Bochra A. (ORCID:0000000159055880)↗

Identification and characterization of mono- and bifunctional galactan synthases in the pediatric pathogen Kingella kingae

The emerging pediatric pathogen Kingella kingae elaborates a lipopolysaccharide (LPS) that is extended with a galactofuranose homopolymer called galactan, which is a key virulence determinant that contributes to resistance to complement-mediated and neutrophil-mediated killing. Previous work has demonstrated that the pamABCDE locus is required for galactan synthesis. In this study, mutational studies suggested that the pamC gene product is a UDP-galactofuranose (Galf) transferase and is the galactan synthase. Analysis of genome sequence data revealed two distinct pamC alleles designated pamC1 and pamC2, which correlate with the two galactan structures in K. kingae. Examination of isogenic mutants expressing either pamC1 or pamC2 demonstrated that the pamC alleles are the determinants of galactan structure. Experiments with recombinant PamC1 and PamC2 in vitro established that these proteins are galactan synthases capable of extending synthetic Galf disaccharide acceptors in the presence of UDP-Galf. Homology analysis identified critical amino acids that are essential for PamC1 and PamC2 enzymatic activity both in vitro and in K. kingae. Structural analysis of the in vitro-modified synthetic acceptors implicated PamC1 as a monofunctional enzyme capable of generating a β-(1 → 5) Galf linkage and PamC2 as a bifunctional enzyme capable of generating β-(1 → 3) and β-(1 → 6) Galf linkages. This study advances our understanding of the GT2 family of UDP-galactofuranosyltransferases.

60 APPLIED LIFE SCIENCES↗

A Mountaintop View Requires Minimal Sorting: A Faster Contour Tree Algorithm

Consider a scalar field f : M → R, where M is a triangulated simplicial mesh in R d . A level set, or contour, at value v is a connected component of f –1 (v). As v is changed, these contours change topology, merge into each other, or split. Contour trees are concise representations of f that track this contour behavior. The vertices of these trees are the critical points of f, where the gradient is zero. The edges represent changes in the topology of contours. It is a fundamental data structure in data analysis and visualization, and there is significant previous work (both theoretical and practical) on algorithms for constructing contour trees. Suppose M has n vertices, N facets, and t critical points. A classic result of Carr, Snoeyink, and Axen (2000) gives an algorithm that takes O(n log n+Nα(N)) time (where α(·) is the inverse Ackermann function). A further improvement to O(t log t + N) time was given by Chiang et al. All these algorithms involve a global sort of the critical points, a significant computational bottleneck. Unfortunately, lower bounds of Ω(t log t) also exist. We present the first algorithm that can avoid the global sort and has a refined time complexity that depends on the contour tree structure. Intuitively, if the tree is short and fat, we get significant improvements in running time. For a partition of the contour tree into a set of descending paths, P, our algorithm runs in O($\Sigma$ pϵP |p| log |p| + tα(t) + N). This is at most O(t log D + N), where D is the diameter of the contour tree. Moreover, it is O(tα(t) + N) for balanced trees, a significant improvement over the previous complexity. Our algorithm requires numerous ideas: partitioning the contour tree into join and split trees, a local growing procedure to iteratively build contour trees, and the use of heavy path decompositions for the time complexity analysis. There is a crucial use of a family of binomial heaps to maintain priorities, ensuring that any comparison made is between comparable nodes of the contour tree. We also prove lower bounds showing that the $\Sigma$ pϵP |p| log |p| complexity is inherent to computing contour trees.

97 MATHEMATICS AND COMPUTING↗

Forest stand and canopy development unaltered by 12 years of CO2 enrichment*

Abstract Canopy structure—the size and distribution of tree crowns and the spatial and temporal distribution of leaves within them—exerts dominant control over primary productivity, transpiration and energy exchange. Stand structure—the spatial arrangement of trees in the forest (height, basal area and spacing)—has a strong influence on forest growth, allocation and resource use. Forest response to elevated atmospheric CO2 is likely to be dependent on the canopy and stand structure. Here, we investigated elevated CO2 effects on the forest structure of a Liquidambar styraciflua L. stand in a free-air CO2 enrichment experiment, considering leaves, tree crowns, forest canopy and stand structure. During the 12-year experiment, the trees increased in height by 5 m and basal area increased by 37%. Basal area distribution among trees shifted from a relatively narrow distribution to a much broader one, but there was little evidence of a CO2 effect on height growth or basal area distribution. The differentiation into crown classes over time led to an increase in the number of unproductive intermediate and suppressed trees and to a greater concentration of stand basal area in the largest trees. A whole-tree harvest at the end of the experiment permitted detailed analysis of canopy structure. There was little effect of CO2 enrichment on the relative leaf area distribution within tree crowns and there was little change from 1998 to 2009. Leaf characteristics (leaf mass per unit area and nitrogen content) varied with crown depth; any effects of elevated CO2 were much smaller than the variation within the crown and were consistent throughout the crown. In this young, even-aged, monoculture plantation forest, there was little evidence that elevated CO2 accelerated tree and stand development, and there were remarkably small changes in canopy structure. Questions remain as to whether a more diverse, mixed species forest would respond similarly.

59 BASIC BIOLOGICAL SCIENCES↗

Van der Waals heterostructures

The integration of dissimilar materials into heterostructures has become a powerful tool for engineering interfaces and electronic structure. The advent of two-dimensional (2D) materials brought unprecedented opportunities for novel heterostructures in the form of van der Waals stacks, laterally stitched 2D layers, and more complex layered and 3D architectures. This Primer provides an overview of state-of-the-art methodologies for producing such van der Waals heterostructures, focusing on the two fundamentally different strategies, top-down deterministic assembly and bottom-up synthesis. For both approaches, successful techniques, advantages, and limitations are discussed. As important as the fabrication itself is the characterization of the resulting engineered materials, for which a range of analysis techniques covering structure, composition, and emerging functionality are highlighted. Examples of the properties of artificial van der Waals structures include optoelectronics and plasmonics, twistronics, and unique functionality arising from the generalization of van der Waals assembly from 2D- to 3D-crystalline components. Lastly, current issues of reproducibility, limitations, and opportunities for future breakthroughs in terms of enhanced homogeneity, interfacial purity, feature control, and ultimately orders of magnitude increased complexity of van der Waals heterostructures are discussed.

36 MATERIALS SCIENCE↗

Enumeration as a Tool for Structure Solution: A Materials Genomic Approach to Solving the Cation-Ordered Structure of Na 3 V 2 (PO 4 ) 2 F 3

While powder diffraction methods are routinely utilized to optimize structural models for compounds whose crystal structures are known, the determination of unknown structures is far more challenging. When the unknown structure is large, structure solution can become a virtually intractable problem using standard structure solution methodologies, especially when the space group cannot be unambiguously resolved. One such system is the promising Na-ion battery cathode material Na 3 V 2 (PO 4 ) 2 F 3 whose high temperature and room temperature structures were previously solved, but whose more complex low-temperature structure could not be determined. Here, a novel materials genomic approach is demonstrated for the solution of the unknown 100 K structure of Na 3 V 2 (PO 4 ) 2 F 3 in which enumeration methods are first used to generate a large number (~3,000) of trial structures based on plausible orderings of Na ions and then automated Rietveld refinements are carried out to optimize each of these trial structures. Based on both the analysis of the ensemble of optimized trial structures and the density functional theory energy minimization of selected trial structures, the 100 K structure of Na 3 V 2 (PO 4 ) 2 F 3 is best described as belonging to the space group A2 1 am with unit cell dimensions of a = 9.01928(4), b = 27.1379(1), c = 10.73307(5). The 100 K unit cell has a large volume of 2627.07(2) Å 3 with Z = 12 and 33 independent crystallographic sites (9 Na, 3 V, 3 P, 12 O, and 6 F) that is 3x and 6x larger than the room- and high-temperature polymorphs of this phase, respectively. Finally, the novel methods described here will be generally applicable for the solution of the complex cation-ordered structures that commonly occur for battery materials.

36 MATERIALS SCIENCE↗

All-Atom Simulations Uncover Structural and Dynamical Properties of STING Proteins in the Membrane System

Recent studies have shown that the stimulator of interferon gene (STING) protein plays a central role in the immune system by facilitating the production of type I interferons in cells. The STING signaling pathway is also a prominent activator of cancer-killing T cells that initiate a powerful adaptive immune response. Since biomolecular signaling pathways are complicated and not easily identified through traditional experiments, molecular dynamics (MD) has often been used to study structural and dynamical responses of biological pathways. In this work, we carried out MD simulations for full-length chicken and human STING (chSTING and hSTING) proteins. Specifically, we investigated ligand-bound closed (holo) and ligand-unbound open (apo) forms of STING in the membrane system by comparing their conformational and dynamical differences. Our research provides clues for understanding the mechanism of the STING signaling pathway by uncovering detailed insights for the examined systems: the residues from each chain in the binding pocket are strongly correlated to one another in the open STING structure compared with those in the closed STING structure. Ligand-bound closed STING displays ~174° rotation of the ligand-binding domain (LBD) relative to the open STING structure. The dynamical analysis of residue Cys148 located in the linker region of hSTING does not support the earlier hypothesis that Cys148 can form disulfide bonds between adjacent STING dimers. We also demonstrate that using the full-length proteins is critical, since the MD simulations of the LBD portion alone cannot properly describe the global conformational properties of STING.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantifying patterns in optical micrographs of one- and two-dimensional ellipsoidal particle assemblies

Current developments in colloidal science include the assembly of anisotropic colloids with broad geometric diversity. As the complexity of particle assemblies increases, the need for ubiquitous algorithms that quantitatively analyze images of the assemblies to deliver key information such as quantification of crystal structures becomes more urgent. This contribution describes algorithms capable of image analysis for classifying colloidal structures based on abstracted interparticle relationship information and quantitatively analyzing the abundance of each structure in mixed pattern assemblies. The algorithm parameters can be adjusted, allowing for the algorithms to be adapted for different image analyses. Three different ellipsoidal particle assembly images are presented to demonstrate the effectiveness of the algorithms: a one-dimensional (1D) particle chain assembly and two two-dimensional (2D) polymorphic crystals each consisting of assemblies of two distinct plane symmetry groups. Angle relationships between neighbouring particles are calculated and neighbour counts of each particle are determined. Combining these two parameters as rules for classification criteria allows for the labeling and quantification of each particle into a defined symmetry class within an assembly. The algorithms provide a labelled image comprising classification results and particle counts of each defined class. For multiple images or individual frames from a video, the script can be looped to achieve automatic processing. The yielded classification data allow for more in-depth image analysis of mixed pattern particle assemblies. Finally, we envision that these algorithms will have utility in quantitative analysis of images comprising ellipsoidal colloidal materials, nanoparticles, or biological matter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Oxygen Defect Configurations in Single-Phase UO 2.15

Hyperstoichiometric UO 2.15 was characterized by neutron total scattering at high temperature in the single-phase UO 2+x region of the U/O phase diagram. The diffraction data confirmed a single-phase fluorite structure at high temperature. Analysis of the short-range data showed that the same structural model does not fit the pair distribution functions well. Instead, structural models containing specific configurations of oxygen defect clusters best represent the local atomic arrangement. In conclusion, prevalent defect clusters previously proposed were fit to the experimental data, and moderately distorted oxygen cuboctahedra hypothesized by recent molecular dynamics simulations fit the data most accurately.

neutron pair-distribution function analysis↗

Filling the gap with a bulky diaryl boron group: fluorinated and non-fluorinated copper pyrazolates fitted with a dimesityl boron moiety on the backbone

Successful synthesis has been reported of 4-Mes 2 B-3,5-(CF 3 ) 2 PzH and 4-Mes 2 B-3,5-(CF 3 ) 2 PzH bearing sterically demanding diarylboron moieties at the pyrazole ring 4-position, and their corresponding copper(I) pyrazolate complexes. They show visible blue photoluminescence in solution. The X-ray crystal structures revealed that the fluorinated {[4-BMes 2 -3,5-(CF 3 ) 2 Pz]Cu} 3 crystallizes as discrete trinuclear molecules whereas as the non-fluorinated {[4-BMes 2 -3,5-(CH 3 ) 2 Pz]Cu} 3 forms dimers of trimers with two close inter-trimer Cu···Cu separations. The solid {[4-BMes 2 -3,5-(CF 3 ) 2 Pz]Cu} 3 featuring a sterically confined Cu 3 N 6 core displays bright blue phosphorescence while {[4-BMes 2 -3,5-(CH 3 ) 2 Pz]Cu} 3 , which is a dimer of a trimer, is a red phosphor at room temperature. Here, this work illustrates the modulation of photo-physical properties of metal pyrazolates by adjusting the supporting ligand steric features and introducing secondary diarylboron luminophores. Computational analysis of the structures and photophysical properties of copper complexes are also presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of the time-of-flight neutron scattering cross-section data for light water measured at the SEQUOIA spectrometer, Spallation Neutron Source (SNS)

Thermal neutron scattering cross-section data for light water available in the major nuclear data libraries observes significant differences especially at reactor operating temperatures. During the past few years there has been a renewed interest in reviewing the existing thermal scattering models and generating more accurate and reliable thermal scattering cross sections using existing experimental data and in some cases based on Molecular Dynamics (MD) simulations. There is a need for performing new time-of-flight experiments at high temperatures and pressures, to have a better understanding of the physics involved in the scattering process that could help improve the existing TSL data.Lack of experimental thermal scattering data for light water at high temperatures led to a new measurement campaign within the INSIDER project at the Institut de radioprotection et de sûreté nucléaire (IRSN). Double differential scattering cross section for light water have been measured at the SEQUOIA spectrometer based at the Spallation Neutron Source (SNS), Oak Ridge National Laboratory, United States. Several measurements have been carried out at different temperatures and pressures corresponding to liquid light water. Measurements at five different incident neutron energies Ei (8, 60, 160, 280 and 800 meV) have been carried out to help exploring different regions of the frequency spectrum. This paper presents the analysis of the dynamic structure factor and the derived frequency spectrum of light water. The analysis of the experimental data would provide one with better confidence, the behavior of thermal scattering cross sections for light water at high temperatures, knowledge of which is very important for the design of novel reactors as well as existing pressurized water reactors.

Jaiswal, V↗

Applying Gaussian Process Machine Learning and Modern Probabilistic Programming to Satellite Data to Infer CO 2 Emissions

Satellite data provides essential insights into the spatiotemporal distribution of CO 2 concentrations. However, many atmospheric inverse models fail to adequately incorporate the spatial and temporal correlations inherent in satellite observations and often lack rigorous methods for estimating parameters like spatial length scales. We introduce an inference model that processes the spatiotemporal covariance in satellite data and estimates hyperparameters such as covariance length scales. Our approach uses the Gaussian process (GP) machine learning (ML) and modern probabilistic programming languages (PPLs) to perform atmospheric inversions of emissions from satellite data. We develop a GP ML inversion system based on modern PPLs and the GEOS-Chem chemical transport model, simulating atmospheric CO 2 concentrations corresponding to the Orbiting Carbon Observatory-2/3 (OCO-2/3) data for July 2020. In our supervised learning framework, we treat the GEOS-Chem simulated data set as the target, with predictors derived by scaling the target with sector-specific factors hidden from the GP machine. Our results show that the GP model, combined with GPU-enabled PPLs, effectively retrieves true emission scaling factors and infers noise levels concealed within the data. This suggests that our method could be applied over larger areas with more complex covariance structures, enabling comprehensive analysis of the spatiotemporal patterns observed in OCO-2/3 and similar satellite data sets.

54 ENVIRONMENTAL SCIENCES↗

Illinois Storage Corridor CarbonSAFE Phase III: Stakeholder Engagement and Outreach Plan

The Stakeholder Engagement and Outreach Plan provides a comprehensive framework for engaging stakeholders of the Illinois Storage Corridor (ISC) project. The ISC project is a CarbonSAFE Phase III project designed to facilitate commercial deployment of carbon capture, utilization, and storage (CCUS) in Illinois. The project aims to establish a multi-industry carbon storage corridor through development of storage sites near the One Earth Energy (OEE) ethanol production facility in north-central Illinois and the Prairie State Generating Company (PSGC) coal-fired power plant in south-central Illinois, with combined annual CO 2 capture ultimately exceeding 8.6 million tons per year. Stakeholder engagement is recognized as a critical component for successful CCUS deployment, alongside technical and economic considerations. As an emerging technology, CCUS may not be well understood by the general population, and lack of public awareness can lead to opposition that poses significant barriers to project development. This plan addresses this challenge through systematic stakeholder identification, analysis, planning, and implementation of engagement actions. The plan is structured around four main sections: Communication, Stakeholder Analysis, Stakeholder Engagement, and Environmental Justice. Activities will be conducted under Tasks 1 and 4 of the project's Statement of Project Objectives, with two key subtasks: (1) developing a stakeholder analysis and engagement plan through face-to-face meetings, facilitated discussions, and surveys; and (2) implementing stakeholder engagement and public outreach activities including meetings, open houses, and permit hearings. The Illinois State Geological Survey (ISGS) will manage engagement activities following DOE-NETL best practices, focusing on providing objective, fact-based information about CCUS and the ISC project. A comprehensive Communication Plan establishes protocols for media contacts, site visits, and crisis communications. The stakeholder analysis follows a structured workflow process divided into Pre-feasibility and Feasibility phases, incorporating contextual understanding, assessment, data collection, and analysis. Key stakeholder groups include government bodies, educational organizations, conservation and environmental groups, agricultural communities, and religious organizations. The plan addresses common stakeholder questions regarding project risks, benefits, safety, property values, liability, and environmental impacts. Recommendations emphasize developing clear messaging, creating informational materials, and preparing to address both project-specific and broader environmental concerns to ensure transparent communication and build stakeholder support throughout project implementation.

25 ENERGY STORAGE↗