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At least 991 records · Page 55

Learning interpretable surface elasticity properties from bulk properties via neural network equation learners

Surface elasticity is central to understanding the mechanics and stability of surfaces and interfaces. It is characterized by quantities such as surface tension, residual surface stress, and surface stiffness. However their analytical expressions are typically difficult to derive from atomistic data, and depend strongly on modeling choices. This work presents a neural network-based equation learner which combines customized activation functions and connection-based pruning to discover parsimonious, closed-form equations for surface elasticity from atomistic simulations. Applying the method to seven face-centered cubic (FCC) metals, our equation learner uncovers interpretable equations that describe both low-Miller index and high-Miller index surface properties, capturing long-tail property distributions accurately. The discovered expressions are decoupled into two components: a universal, geometry-driven orientation function, and material-specific baseline coefficients. We find that lower-order properties such as surface tension are fundamentally geometry dependent, while higher-order properties such as surface stress and elasticity show more complex geometry and material dependence. We also relate material dependent coefficients to bulk properties, forming a clear map from bulk material properties to surface elasticity. Overall, this approach demonstrates that interpretable neurosymbolic machine learning can bridge the gap between atomistic simulations and physical laws, enabling the discovery of generalizable structure–property relationships for materials science phenomena such as surface elasticity.

Equation learning↗

Size- and concentration-dependent Eu 2+ /Eu 3+ mixed luminescent characteristics of rare-earth-doped CaF 2 nanoparticles and their monolithic epoxy nanocomposites

CaF 2 is a promising luminescent host material for a wide range of applications, due to its high transparency, non-hygroscopy, low refractive index, low density, low backscattering efficiency, and abundance in nature. Here we report the photoluminescence (PL) and cathodoluminescence (CL) characteristics of rare-earth-doped CaF 2 nanoparticles and their composite monoliths with epoxy with visible emissions. The CaF 2 nanoparticles of ca. 36, 108 and 305 nm were prepared by a facile solution-mixing process and subsequent hydrothermal treatment. As the particle size decreases, the luminescence intensity increases for single-doped particles, while oppositely decreases for codoped particles because of energy transfer. Further, Eu 2+ - and Tb 3+ -codoped CaF 2 nanoparticles exhibit red emission, providing an efficient path for red emission through an energy transfer by Tb 3+ bridging without direct Eu 3+ doping. The effects of size and concentration are found to be pronounced in CL than PL, as the charge transfer between Eu 2+ and Eu 3+ reduces the concentration quenching in CL. The luminescence emission characteristics of epoxy/CaF 2 monoliths are different from those of particles due to the interactions with the epoxy molecules, and thus the energy transfer is hindered in PL while not in CL, enabling them for high-energy irradiation applications.

36 MATERIALS SCIENCE↗

Metal forming and working of stabilized nanocrystalline Cu-Ta for electrical contacts

The commercialization of nanocrystalline metals and alloys is currently entering a renaissance period. Many of the processing and consolidation challenges that have haunted them are now more fully understood, opening the doors for stabilized nanocrystalline metals to be produced on a bulk scale. While challenges remain, the increased volume at which these materials are being supplied is for the first time allowing for investigations into more traditional methods of metal working, such as extruding, rolling, forming, and forging. Recently, the manufacturing science has been developed to allow nanocrystalline Cu-Ta alloys to progress to this point. This article therefore builds upon the last decade of evolutionary progression within the family of stabilized nanocrystalline Cu-Ta alloys by presenting some of the first findings related to scaled powder synthesis, production of billets, thin sheets, and foils. Here, the mechanical performance and physical properties relevant to forming electrical contacts and pins including, tensile, J-integral fracture toughness, Charpy Impact, bi-axial tension, and conductivity are reported. This introductory investigation into forming such a novel material, provides evidence to these alloys potential at bridging the gap between being a scientific curiosity to that of a real engineering material.

36 MATERIALS SCIENCE↗

Nitrogen: A promising doping strategy for high-performance ovonic threshold switching selectors

The Ovonic Threshold Switching (OTS) selector serves as an essential component in the development of three-dimensional high-density memory integration technology. Nevertheless, the state-of-the-art high-performance OTS materials usually contain toxic elements such as arsenic (As), posing significant risks to both environmental and human health. Nitrogen (N), which belongs to the same group as arsenic (As), has emerged as a highly promising alternative for As doping. However, the underlying mechanisms that govern N-based OTS materials have not yet been extensively investigated. In this study, we delve into the effects of N doping on the structural, bonding, and electronic properties of amorphous GeSe (a-GeNSe) by ab initio molecular dynamics simulations to bridge the knowledge gap. Our findings indicate that upon N doping in a-GeSe, the formation of robust Ge-N bonds, along with N-centered tetrahedral and triangular structures, resulting in the sluggish atomic movement that enhances the thermal stability and endurance of a-GeNSe. The OTS characteristics are significantly influenced by the material’s electronic band structure, and thus the relatively slow performance drift can be attributed to the stabilization of mid-gap states, a result of N doping which effectively slows down the aging process of chalcogenide glass. Moreover, the increased mobility gap in a-GeNSe raises the threshold voltage (V th ), making it more compatible with commercially available phase-change memory materials. Furthermore, our findings reveal the extensive impact of the N element on a typical OTS material and offer valuable perspectives for alternative doping strategies that could potentially supplant As practices.

36 MATERIALS SCIENCE↗

Hierarchical microstructural parameters governing electrical and thermal conductivity in Al-based eutectic systems

Enhancing conductivity properties of aluminum alloys can drive superior performance and efficiency across diverse engineering applications, yet currently commercially available Al casting alloys are severely limited in electrical and thermal conductivity. There is a general understanding that the presence of any defects and alloying elements within Al will inevitably lower conductivity properties. However, there is a lack of comparative studies evaluating the intricate interplay between the microstructural parameters and conductivity properties across cast Al-based eutectic systems. Therefore, this study bridges this gap by conducting a comparative study across hypoeutectic alloy compositions consisting of 50 % primary Al and 50 % eutectic region to elucidate the key parameters that dictate conductivity properties. This research contributes to advancing the understanding of alloy design opportunities for high conductivity, high strength castable Al alloys.

36 MATERIALS SCIENCE↗

The crystal structure of Vibrio cholerae (6-4) photolyase reveals interactions with cofactors and a DNA-binding region

Photolyases (PLs) reverse UV-induced DNA damage using blue light as an energy source. Of these PLs, (6-4) PLs repair (6-4)-lesioned photoproducts. We recently identified a gene from Vibrio cholerae (Vc) encoding a (6-4) PL, but structural characterization is needed to elucidate specific interactions with the chromophore cofactors. Here, we determined the crystal structure of Vc (6-4) PL at 2.5 Å resolution. Our high-resolution structure revealed that the two well-known cofactors, flavin adenine dinucleotide and the photoantenna 6,7-dimethyl 8-ribityl-lumazin (DMRL), stably interact with an α-helical and an α/β domain, respectively. Additionally, the structure has a third cofactor with distinct electron clouds corresponding to a [4Fe-4S] cluster. Moreover, we identified that Asp106 makes a hydrogen bond with water and DMRL, which indicates further stabilization of the photoantenna DMRL within Vc (6-4) PL. Further analysis of the Vc (6-4) PL structure revealed a possible region responsible for DNA binding. The region located between residues 478 to 484 may bind the lesioned DNA, with Arg483 potentially forming a salt bridge with DNA to stabilize further the interaction of Vc (6-4) PL with its substrate. Our comparative analysis revealed that the DNA lesion could not bind to the Vc (6-4) PL in a similar fashion to the Drosophila melanogaster (Dm, (6-4)) PL without a significant conformational change of the protein. The 23rd helix of the bacterial (6-4) PLs seems to have remarkable plasticity, and conformational changes facilitate DNA binding. In conclusion, our structure provides further insight into DNA repair by a (6-4) PL containing three cofactors.

(6-4) lesioned photoproduct↗

Structure of a dimeric photosystem II complex from a cyanobacterium acclimated to far-red light

Photosystem II (PSII) is the water-splitting enzyme central to oxygenic photosynthesis. To drive water oxidation, light is harvested by accessory pigments, mostly chlorophyll (Chl) a molecules, which absorb visible light (400–700 nm). Some cyanobacteria facultatively acclimate to shaded environments by altering their photosynthetic machinery to additionally absorb far-red light (FRL, 700–800 nm), a process termed far-red light photoacclimation or FaRLiP. During far-red light photoacclimation, FRL-PSII is assembled with FRL-specific isoforms of the subunits PsbA, PsbB, PsbC, PsbD, and PsbH, and some Chl-binding sites contain Chls d or f instead of the usual Chl a. The structure of an apo-FRL-PSII monomer lacking the FRL-specific PsbH subunit has previously been determined, but visualization of the dimeric complex has remained elusive. Here, we report the cryo-EM structure of a dimeric FRL–PSII complex. The site assignments for Chls d and f are consistent with those assigned in the previous apo-FRL-PSII monomeric structure. All sites that bind Chl d or Chl f at high occupancy exhibit a FRL-specific interaction of the formyl moiety of the Chl d or Chl f with the protein environment, which in some cases involves a phenylalanine sidechain. The structure retains the FRL-specific PsbH2 subunit, which appears to alter the energetic landscape of FRL-PSII, redirecting energy transfer from the phycobiliprotein complex to a Chl f molecule bound by PsbB2 that acts as a bridge for energy transfer to the electron transfer chain. Collectively, these observations extend our previous understanding of the structure-function relationship that allows PSII to function using lower energy FRL.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Designer molecules of the synaptic organizer MDGA1 reveal 3D conformational control of biological function

MDGAs (MAM domain-containing glycosylphosphatidylinositol anchors) are synaptic cell surface molecules that regulate the formation of trans-synaptic bridges between neurexins (NRXNs) and neuroligins (NLGNs), which promote synaptic development. Mutations in MDGAs are implicated in various neuropsychiatric diseases. MDGAs bind NLGNs in cis on the postsynaptic membrane and physically block NLGNs from binding to NRXNs. In crystal structures, the six immunoglobulin (Ig) and single fibronectin III domains of MDGA1 reveal a striking compact, triangular shape, both alone and in complex with NLGNs. Whether this unusual domain arrangement is required for biological function or other arrangements occur with different functional outcomes is unknown. Here, we show that WT MDGA1 can adopt both compact and extended 3D conformations that bind NLGN2. Designer mutants targeting strategic molecular elbows in MDGA1 alter the distribution of 3D conformations while leaving the binding affinity between soluble ectodomains of MDGA1 and NLGN2 intact. In contrast, in a cellular context, these mutants result in unique combinations of functional consequences, including altered binding to NLGN2, decreased capacity to conceal NLGN2 from NRXN1β, and/or suppressed NLGN2-mediated inhibitory presynaptic differentiation, despite the mutations being located far from the MDGA1-NLGN2 interaction site. Thus, the 3D conformation of the entire MDGA1 ectodomain appears critical for its function, and its NLGN-binding site on Ig1-Ig2 is not independent of the rest of the molecule. As a result, global 3D conformational changes to the MDGA1 ectodomain via strategic elbows may form a molecular mechanism to regulate MDGA1 action within the synaptic cleft.

MDGAs↗

Tuning acidity in silica-overcoated oxides for hydroalkoxylation

Mixed oxides are ubiquitious solid acid catalysts for a number of transformations. Here, the chemistry of mixed oxide interfaces was experimentally probed by constructing model SiO 2 on MO x interfaces using a liquid-phase, stoichiometrically-controlled deposition of tetraethyl orthosilicate (TEOS). Catalytically active Brønsted sites were generated in four series of overcoated SiO 2 on metal oxide materials prepared by depositing TEOS onto Al 2 O 3 , anatase TiO 2 , Nb 2 O 5 , and ZrO 2 . Pyridine DRIFTS studies indicate that the acidity of deposited silanol groups was enhanced by interaction with the metal oxide surface, suggesting that pseudo-bridging silanol type structures were formed. Trimethylphosphine oxide (TMPO) 31 P NMR experiments showed that Brønsted acid strength varied in the overcoated materials, with increasing strength in the following order: SiO 2 /ZrO 2 < SiO 2 /TiO 2 < SiO 2 /Nb 2 O 5 < SiO 2 /Al 2 O 3 . This order correlated with the Lewis acidity and chemical hardness of the underlying metal oxides. The catalytic performance of the materials was evaluated in the liquid-phase hydroalkoxylation of dihydropyran with n-octanol, revealing that activity was highly dependent on SiO 2 loading, which impacted the density of acid sites, and scaled exponentially with Brønsted acid strength, determined by the core metal oxide identity. Brønsted acid strength appears to be the key driver of the materials’ activity, with the highest areal rate of 2.2 mmol / m 2 – h being measured over SiO 2 /Al 2 O 3 . Furthermore, this study shows that SiO 2 -overcoated materials are a systematically tunable class of catalysts that can be applied to acid catalyzed reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanistic insights into nitrogen activation on atomic Ru clusters in self-pillared pentasil using operando atomistic models and experimental kinetics

Alternative catalysts to the industrial Haber Bosch process have been of significant interest in the field of heterogeneous catalysis, yet realizing ammonia synthesis under mild conditions (e.g., 300 °C and 10 bar) is challenging due to the low per-pass conversion. One strategy is to promote the associative ammonia synthesis mechanism which eschews direct N-N bond cleavage. Here, in this work, we use self-pillared pentasil, a self-pillared hierarchical zeolite built by thin MFI zeolite nanosheets, as a support for subnanometric Ru clusters to synthesize ammonia. We show that Ru remains well-dispersed during reaction and further demonstrate that ammonia synthesis rates are higher than Cs-Ru/MgO. Reaction kinetics show a positive order in H 2 providing evidence for the associative mechanism, which then becomes negative in H 2 if Ru is allowed to aggregate into nanoparticles. Operando Density Functional Theory models for Ru speciation in SPP, free energy diagrams, and microkinetic modeling were then applied to develop a reaction mechanism that involves sequential hydrogenation of N 2 from metallic Ru clusters. For this hydrogenation to occur, there are site requirements for N 2 to adopt a bridge-bound configuration that facilitates sequential hydrogenation on single sites and metal clusters. These site requirements in turn inform the design of improved zeolite-supported ammonia synthesis catalysts.

36 MATERIALS SCIENCE↗

Protonation Dynamics of Confined Ethanol–Water Mixtures in H-ZSM-5 from Machine Learning-Driven Metadynamics

Zeolites are indispensable heterogeneous catalysts in industrial chemical processes, valued for their strong Brønsted acidity, well-defined microporous frameworks, and tunable pore structures. Their catalytic activity arises primarily from Brønsted acid sites (BAS), typically present as bridging hydroxyl groups (Si–OH–Al). Under aqueous reaction conditions, these protons interact dynamically with water and alcohol molecules, leading to complex solvation and protonation behavior within confined pores. In this study, we investigate the protonation equilibrium occurring between ethanol and water at the BAS of acidic zeolites under varying hydration levels, i.e., C2H5OH–(H2O)n, n=1–4. Local structure was analyzed through an adaptive-learning global optimization algorithm, while enhanced sampling molecular dynamics simulations with Well-Tempered Metadynamics (WMetaD) and machine learning interatomic potentials (MLPs) provide free-energy surfaces (FES) at variable hydration levels. The results reveal a strong dependence of proton localization on the degree of hydration. At low hydration (1 water molecule), the proton resides predominantly on ethanol; with 2 water molecules, it shifts toward water, and at higher hydration (3 or more water molecules), it becomes extensively delocalized over the water cluster. These findings underscore the critical role of solvation in modulating acid site behavior and suggest that a minimum of three water molecules is necessary to fully stabilize the proton on water within the zeolite framework. This solvation threshold has significant implications for catalytic processes, particularly in biomass conversion reactions where alcohol protonation is a key step in dehydration mechanisms.

machine learning↗

Disordered interfaces of alkaline aluminate salt hydrates provide glimpses of Al 3+ coordination changes

Hypothesis: The precipitation and dissolution of aluminum-bearing mineral phases in aqueous systems often proceed via changes in both aluminum coordination number and connectivity, complicating molecular-scale interpretation of the transformation mechanism. Here, the thermally induced transformation of crystalline sodium aluminum salt hydrate, a phase comprised of monomeric octahedrally coordinated aluminate which is of relevance to industrial aluminum processing, has been studied. Because intermediate aluminum coordination states during melting have not previously been detected, it is hypothesized that the transition to lower coordinated aluminum ions occurs within a highly disordered quasi-two-dimensional phase at the solid-solution interface. Experiments and simulations: In this work, in situ X-ray diffraction (XRD), Raman and 27 Al nuclear magnetic resonance (NMR) spectroscopy were used to monitor the melting transition of nonasodium aluminate hydrate (NSA, Na 9 [Al(OH) 6 ] 2 ·3(OH)·6H 2 O). A mechanistic interpretation was developed based on complementary classical molecular dynamics (CMD) simulations including enhanced sampling. A reactive forcefield was developed to bridge speciation in the solution and in the solid phase. Findings: In contrast to classical dissolution, aluminum coordination change proceeds through a dynamically stabilized ensemble of intermediate states in a disordered layer at the solid-solution interface. In both melting and dissolution of NSA, octahedral, monomeric aluminum transition through an intermediate of pentahedral coordination. The intermediate dehydroxylates to form tetrahedral aluminate (Al(OH)$_4^–$) in the liquid phase. This coordination change is concomitant with a breaking of the ionic aluminate-sodium ion linkages. The solution phase Al(OH)$_4^–$ ions subsequently polymerize into polynuclear aluminate ions. However, there are some differences between bulk melting and interfacial dissolution, with the onset of the surface-controlled process occurring at a lower temperature (~30 °C) and the coordination change taking place more gradually as a function of temperature. This work to determine the local structure and dynamics of aluminum in the disordered layer provides a new basis to understand mechanisms controlling aluminum phase transformations in highly alkaline solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Variations in proton transfer pathways and energetics on pristine and defect-rich quartz surfaces in water: Insights into the bimodal acidities of quartz

Hypothesis. Understanding the mechanisms of proton transfer on quartz surfaces in water is critical for a range of processes in geochemical, environmental, and materials sciences. The wide range of surface acidities (>9 pKa units) found on the ubiquitous mineral quartz is caused by the structural variations of surface silanol groups. Molecular scale simulations provide essential tools for elucidating the origin of site-specific surface acidities. Simulations. Here, we used density-functional tight-binding-based molecular dynamics combined with rare-event metadynamics simulations to probe the mechanisms of deprotonation reactions from ten representative surface silanol groups found on both pristine and defect-rich quartz (1 0 1) surfaces with Si vacancies. Findings. The results show that deprotonation is a highly dynamic process where both the surface hydroxyls and bridging oxygen atoms serve as the proton acceptors, in addition to water. Deprotonation of embedded silanols through intrasurface proton transfer exhibited lower pKa values with less H-bond participation and higher energy barriers, suggesting a new mechanism to explain the bimodal acidity observed on quartz surface. Defect sites, recently shown to comprise a significant portion of the quartz (1 0 1) surface, diversify the coordination and local H-bonding environments of the surface silanols, changing both the deprotonation pathways and energetics, leading to a wider range of pKa values (2.4 to 11.5) than that observed on pristine quartz surface (10.4 and 12.1).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vibrational sum frequency generation spectroscopy reveals the inertness of chromium oxide (001) surfaces

Nanoengineered metal oxides such as Cr(III)-oxide (chromia) films have diverse potential applications in corrosion inhibition, remediation, energy generation, catalysis, data storage, and biological and environmental systems. Concerns about material degradation or oxidation to toxic chromate necessitate an understanding of chromia/aqueous interfaces, beginning with their hydroxylation and hydration behavior. Vibrational sum-frequency generation spectroscopy (vSFG) provides specific molecular-level information about water at the oxide/aqueous junction with high surface selectivity. To overcome the strong absorber problem typical of certain metal oxides in the UV–visible range during nonlinear optical studies, we employed molecular beam epitaxy to deposit transparent, epitaxial nanofilms of Cr 2 O 3 with (001) crystalline orientation on sapphire (Al 2 O 3 (001)) substrates, as confirmed by atomic force microscopy and X-ray diffraction. vSFG spectra of the air and water interfaces of the Cr 2 O 3 (001) films reveal hydroxyl features corresponding to both dissociated and molecular water on the surface. In contrast to the dangling hydroxyls found on the bare Al 2 O 3 (001) substrate, the hydroxyl groups on the deposited Cr 2 O 3 (001) nanofilm do not readily undergo isotopic H/D exchange when exposed to varying forms of D 2 O under ambient conditions. When considering the chemistries of the corresponding trivalent cations in aqueous solution, the finding is at variance with their similar acidities and proton exchange dynamics but consistent with markedly slower inner-sphere water ligand exchange of hexaquo Cr 3+ . This finding challenges the idea that proton and water exchange at the water/Cr₂O₃(001) interface are solely correlated, driven by the strength of metal-bridging oxygen bonds and surface hydroxyl distribution, without direct causation.

Boamah-Agyemang, Mavis D. [Pacific Northwest Natio↗

Building energy efficiency and load flexibility optimization using phase change materials under futuristic grid scenario

This work investigates the energy savings and load flexibility capacity of phase change material (PCM) integrated into building envelope under a future energy generation scenario, where 80% of the energy load comes from renewable sources. Using community-scale modeling, we first determine the net thermal storage required to fully manage the demand variability at a utility grid, and then using whole-building simulations we optimize operating parameters - such as PCM thickness, latent heat, interior setpoint profile, PCM distribution, and heat transfer coefficient - to determine the optimal conditions required for maximum energy reduction and load flexibility without compromising occupants' thermal comfort. The optimal PCM-integrated envelope proposed in this study can provide annual load flexibility up to 33.6% and annual energy savings up to 10.8% in a lightweight residential building located in Baltimore, MD. This study is relevant given the increasing contributions of renewable energy in the total energy generation mix, leading to a significant time-imbalance between peak energy demand and peak energy production. While thermal energy storage using PCM is a recognized technique, there is no known prior study dedicated to examining the thermal performance of PCM-integrated envelope under future energy generation scenarios. This study bridges the research gap by investigating a practical way to implement PCMs in the buildings and maximize the energy efficiency as well as load flexibility related benefits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An economic analysis of the role of materials, system engineering, and performance in electrochemical carbon dioxide conversion to formate

The development of technologies that utilize carbon dioxide is important to mitigating climate change. The electrochemical reduction of carbon dioxide is one technology that can utilize greenhouse gasses that would be otherwise be emitted to the atmosphere by producing chemicals and fuels from carbon dioxide and electricity. Significant progress has been made in the experimental performance of carbon dioxide reduction systems with novel catalyst designs, new materials, and systems engineering; however, no work has linked such changes in stack design and materials to capital costs for the stack itself. In this study, we present an analysis that accounts for and analyzes the impacts of alternative materials and system architectures on manufactured costs of carbon dioxide reduction stacks, thus providing a framework to understand exactly how these advances impact the at-scale capital costs of these systems. Specifically, we consider the impact that the addition of a catholyte buffer layer has on an electrolyzer reducing carbon dioxide to formate, finding that the cost of manufacturing this part only increases stack costs by about $30/m 2 at high manufacturing rates, while previous work finds that this part improves system performance. This work shows that the links between system performance, materials, and costs are nonlinear, and that achieving low-cost scalability requires optimization of not just performance parameters but also the use of low-cost and highly scalable materials. These results bridge experimental and techno-economic analysis of processes for carbon dioxide reduction, informing researchers by providing a quantifiable estimate of the impact of advances in electrochemical carbon dioxide reduction technology on manufactured stack capital costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Passive and active peer effects in the spatial diffusion of residential solar panels: A case study of the Las Vegas Valley

This research analyzes the role of peer influences on the adoption of residential rooftop solar photovoltaic panels (PV) within the context of the Diffusion of Innovation Theory. PV literature indicates that adopters are influenced by word of mouth (WOM) information exchange with peers, i.e., active peer effects, while other studies suggest that living near households with visible rooftop PV installations influences adoption, i.e., passive peer effects. We bridge the gap in this literature by conducting a mixed methods analysis. We develop and administer a survey to Las Vegas Valley (LVV) residents to identify current and potential PV adopters' perceptions of peer-effects and consumer intention variables. We conduct a spatial analysis of Google's Project Sunroof data to identify LVV neighborhoods in the later stages of the PV diffusion process, i.e., those with the highest PV adoption rates. Key results show that current PV adopters living in early diffusion areas report significantly higher active and passive peer effects compared to adopters in later diffusion areas. Potential adopters in later diffusion areas report higher passive peer effects than those in early diffusion areas. Overall, because LVV has a low PV adoption rate (<3%), short term strategies aimed at increasing PV adoption should emphasize WOM active peer effects. Here, we caution against long-term green marketing strategies focusing solely on peer-effects as the PV market matures.

14 SOLAR ENERGY↗

Mesoscale informed parameter estimation through machine learning: A case-study in fracture modeling

Scale bridging is a critical need in computational sciences, where the modeling community has developed accurate physics models from first principles, of processes at lower length and time scales that influence the behavior at the higher scales of interest. However, it is not computationally feasible to incorporate all of the lower length scale physics directly into upscaled models. This is an area where machine learning has shown promise in building emulators of the lower length scale models, which incur a mere fraction of the computational cost of the original higher fidelity models. We demonstrate the use of machine learning using an example in materials science estimating continuum scale parameters by emulating, with uncertainties, complicated mesoscale physics. Additionally, we describe a new framework to emulate the fine scale physics, especially in the presence of microstructures, using machine learning, and showcase its usefulness by providing an example from modeling fracture propagation. Our approach can be thought of as a data-driven dimension reduction technique that yields probabilistic emulators. Our results show well-calibrated predictions for the quantities of interests in a low-strain simulation of fracture propagation at the mesoscale level. Furthermore, on average, we achieve ~10% relative errors on time-varying quantities like total damage and maximum stresses. Successfully replicating mesoscale scale physics within the continuum models is a crucial step towards predictive capability in multi-scale problems.

36 MATERIALS SCIENCE↗