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At least 721 records · Page 40

Field Demonstration of the Brick Ontology to Scale up the Deployment of ASHRAE Guideline 36 Control Sequences

Many commercial buildings have a vast network of sensors as part of their building automation systems (BAS) that allows opportunities for energy consumption and cost savings by deploying advanced control sequences. However, this resource is often underutilized since BAS are typically programmed with simple control sequences with limited potential to deliver on these opportunities. The recent availability of ASHRAE Guideline 36 (G36) with advanced HVAC control sequences supports control retrofits in existing buildings to unlock much of the savings potential. However, barriers such as the lack of standard naming convention of building assets and data points, proprietary equipment and BAS, and the inherent uniqueness of buildings and their systems prevent building stakeholders from adopting any “plug-and-play” implementation of G36. Instead, control vendors must often undertake the manual and labor-intensive point mapping process to identify a data stream’s functional and spatial relationship within the HVAC system along with other relevant contexts and map it to the new control sequences. The vendor must carry out the point mapping process in each individual building since the mapping is unlikely to port over to another building. Even for the same building, the point mapping process can occur multiple times if various control vendors implement different control retrofits and/or multiple control retrofits happen over the lifecycle of the building. Then, there is the likelihood that G36 control sequences are programmed uniquely to the building, preventing the same implementation from being reused in another. Therefore, this paper presents a field demonstration of how we leveraged the Brick ontology with BACnet, OpenBuildingControl’s Control Description Language (CDL), and open-source support tools to implement scalable and portable advanced building controls. These tools provide standardized semantic descriptions and relationships of the building’s assets and data points (Brick), standardized communication protocol to read from and write to the building’s BAS (BACnet), and standardized code implementations (CDL) of standardized advanced control strategies (G36). We implemented G36’s hot water supply temperature setpoint reset in a Berkeley, CA building for this field demonstration. This field demonstration aims to show how integrating these tools may streamline the deployment of advanced control sequences such as G36 in a consistent manner regardless of differences found across buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Not so HOT Triangulations

Here, we propose primal–dual mesh optimization algorithms that overcome shortcomings of the standard algorithm while retaining some of its desirable features. “Hodge-Optimized Triangulations” defines the “HOT energy” as a bound on the discretization error of the diagonalized Delaunay Hodge star operator. HOT energy is a natural choice for an objective function, but unstable for both mathematical and algorithmic reasons: it has minima for collapsed edges, and its extrapolation to non-regular triangulations is inaccurate and has unbounded minima. We propose a different extrapolation with a stronger theoretical foundation, and avoid extrapolation by recalculating the objective just beyond the flip threshold. We propose new objectives, based on normalizations of the HOT energy, with barriers to edge collapses and other undesirable configurations. We propose mesh improvement algorithms coupling these. When HOT optimization nearly collapses an edge, we actually collapse the edge. Otherwise, we use the barrier objective to update positions and weights and remove vertices. By combining discrete connectivity changes with continuous optimization, we more fully explore the space of possible meshes and obtain higher quality solutions.

97 MATHEMATICS AND COMPUTING↗

nmrrr : A Reproducible Workflow for Binning and Visualizing NMR Spectra From Environmental Samples

Nuclear magnetic resonance (NMR) spectroscopy is a useful tool for detection and identification of molecular structural information, with increasing applications in environmental sciences. NMR instrument outputs are however heterogeneous and require extensive post-processing, creating barriers to their use and application by non-specialists. Here, we report on a new open-source R package, nmrrr, that processes and visualizes spectral data obtained from one-dimensional solution-state and solid-state NMR experiments; the package also performs relevant calculations commonly applied in natural organic matter communities, such as computing the relative abundance of various functional groups. We document the package's installation, dependencies, and functions; and provide a standard workflow for processing NMR data. This package is currently available on CRAN and GitHub, and community contributions are welcome.

54 ENVIRONMENTAL SCIENCES↗

Overcoming efficiency and cost barriers for large-area quantum dot photovoltaics through stable ink engineering

The bottom-up construction of electronics from colloidal quantum dots (CQDs) could innovate nanotechnology manufacturing through printing. However, the unstable and expensive semiconductive CQD inks make the scaling up of CQD electronics challenging. Here, in this study, we develop a strategy for engineering the solution chemistry of lead sulfide (PbS) CQD inks prepared from a low-cost direct synthesis method. By creating an iodine-rich environment in weakly coordinating solvents, we convert the iodoplumbates into functional anions, which condense into a robust surface shell. The fully charged electrostatic surface layer prevents aggregation and epitaxial fusion of CQDs, yielding stable inks. By eliminating the fusion-induced inter-band states, we print a compact CQD film with uniformity in three dimensions, flattened energy landscape and improved carrier transport. We achieved a certified efficiency of 13.40% on 0.04 cm 2 cells, with a 300-fold increase in active area, scaling up to a 12.60 cm 2 module with a certified efficiency of 10%.

14 SOLAR ENERGY↗

Unifying principles for catalytic hydrotreating processes (Final Technical Report)

This project builds on the hypothesis that the hydrotreating processes for the removal of oxygen and sulfur are fundamentally similar at the atomic-scale and existing knowledge from the treatment of petroleum derived feedstock can be leveraged for the design of novel catalysts for the upgrade of bio-oil. We tested this hypothesis by comparing computed potential energy diagrams for hydrodesulfurization (HDS) of thiophene over MoS 2 with hydrodeoxygenation (HDO) of furan over MoO 3 and concluded that certain aspects, such as catalyst promotion with transition metals, are valid strategies for both reactions. On the other hand, we also noticed significant differences in the mechanism for hydrogen (H 2 ) activation, which requires sites with metallic character. While MoS 2 is known to have metallic edge states that can catalyze H 2 dissociation, this elementary step is prohibitively slow on defect-free oxides. Only in the presence of vacancies or by creating metal/oxide interfaces can efficient H 2 activation sites during HDO be formed. The need for bifunctional catalyst when it comes to efficient and selective HDO or dehydrogenation reactions was further corroborated in joint experimental and theoretical studies of the Guerbet reaction for the coupling of biomass derived oxygenates over PdCu alloys, nitrate reduction over In-promoted Pd nanoparticles, and ethylene dehydroaromatization over Ga-exchanged ZSM-5 zeolites. All of these catalytic systems have in common that catalytic sites with distinct functional requirements are needed to create a working catalyst. Detailed computational studies were carried out for HDO of m -cresol and phenol on Ru-modified TiO 2 surfaces, which allowed us to attribute catalytic activity to the metal/oxide interface. A surprising finding was that heterolytic cleavage of the H-H bond across the Ru/TiO 2 interface was critically important, despite lower barriers for homolytic H 2 activation on Ru metal. The explanation lies in the high barriers for hydrogen spillover from Ru to TiO 2 , which becomes unnecessary in the heterolytic activation pathway. Moreover, we also reported that proton transfer steps between metal and oxide sites are mediated by weakly adsorbed surface water. During attempts to develop and validate a kinetic Monte Carlo (kMC) model for HDO reactions at the Ru/TiO 2 interface, it became clear that lateral interactions are paramount to describe realistic surface chemistry and without these interactions, the reduction and hydroxylation behavior from our simulations was inconsistent with reported experiments. To assess the importance of lateral interactions in popular computational catalyst design strategies relying on the identification of reactivity descriptors, which can be used along with Brønsted–Evans–Polanyi (BEP) and scaling relations as input to a microkinetic model (MKM) to make predictions for activity or selectivity trends, we compared predicted trends with those obtained from descriptor-based kMC models. We critically evaluated the benefits of kMC over MKM in terms of trend predictions and computational cost when using only a small set of input parameters. After confirming that in the absence of lateral interactions the kMC and MKM approaches yield identical trends and mechanistic information, we observed substantial differences between the two kinetic models when lateral interactions were introduced. The mean-field implementation applies coverage corrections directly to the descriptors, causing an artificial overprediction of the activity of strongly binding metals. In contrast, the cluster expansion in kMC implementation can differentiate among the highly active metals but it is very sensitive to the set of included interaction parameters. Considering that computational screening relies on a minimal set of descriptors, for which MKM makes reasonable trend predictions at a ca. three orders of magnitude lower computational cost than kMC, we concluded that the MKM approach does provide an overall better entry point for computational catalyst design. Overall, this project has led to 11 peer-reviewed publications, and their scientific is impact is well illustrated by their combined 702 citations.

08 HYDROGEN↗

Catalytic consequences of hydrogen addition events and solvent-adsorbate interactions during guaiacol-H 2 reactions at the H 2 O-Ru(0 0 0 1) interface

Catalytic reactions of biomass-derived phenolics and H 2 occur on transition metal surfaces via competitive C–O cleavage and ring saturation pathways, with both requiring multiple hydrogen addition events before forming their respective rate limiting transition states. These events are markedly affected by solvent chemical identity, with polar protic solvents ionizing hydrogen adatoms (H*) to interfacial protons (H + ) and opening up new catalytic routes. Here, we establish the reaction coordinate space for guaiacol-H 2 reactions on Ru(0 0 0 1) using density functional theory and describe the atomic-scale effect of a polar protic solvent, H 2 O. Coupled H + and H* attack leads to quasi-equilibrated enol and keto intermediates as the precursors for C–O cleavage and ring saturation, respectively. For C–O cleavage, H 2 O solvent enables a lower energy pathway via concomitant transfer of the hydroxyl H + to the methoxy oxygen during C–OCH 3 cleavage, forming a charge separated [Ru(s)–(C 6 H 5 O – )…(H + )…OCH 3 ] transition state and reducing the barrier by up to 0.8 eV as compared to unassisted C–OCH 3 cleavage. For ring saturation, H* attack onto an unsaturated meta carbon is rate limiting with no direct solvent participation, suggesting that protic polar solvents selectively promote the C–O cleavage pathway. Taken together, we show that activating guaiacol for either C–O bond cleavage or ring saturation product formation depends on the reactive hydrogen identity (H* or H + ), enol/keto isomerization equilibrium, and accessibility of the proton assisted Car–OCH 3 cleavage transition state. Here, all such factors are tunable via changes to the solvent or metal identity.

09 BIOMASS FUELS↗

Dramatic Conformer-Dependent Reactivity of the Acetaldehyde Oxide Criegee Intermediate with Dimethylamine Via a 1,2-Insertion Mechanism

The reactivity of carbonyl oxides has previously been shown to exhibit strong conformer and substituent dependencies. Through a combination of synchrotron multiplexed photoionization mass spectrometry experiments (298 K, 4 Torr) and high-level theory (CCSD(T)-F12/cc-pVTZ-F12//B2PLYP-D3/cc-pVTZ with an added CCSDT(Q) correction), we explore the conformer dependence of the reaction of acetaldehyde oxide (CH 3 CHOO) with dimethyl amine (DMA). The experimental data supports the theoretically predicted 1,2-insertion mechanism and the formation of an amine-functionalized hydroperoxide reaction product. Tunable-VUV photoionization probing of anti- or anti- + syn-CH 3 CHOO reveals a strong conformer dependence of the title reaction. Here, the rate coefficient of DMA with anti-CH 3 CHOO is predicted to exceed that for the reaction with syn-CH 3 CHOO by a factor of ~34,000, which is attributed to submerged barrier (syn) vs. barrierless (anti) mechanisms for energetically downhill reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Additive Lithography–Organic Monolayer Patterning Coupled with an Area-Selective Deposition

The combination of area-selective deposition (ASD) with a patternable organic monolayer provides a versatile additive lithography platform, enabling the generation of a variety of nanoscale feature geometries. Stearate hydroxamic acid self-assembled monolayers (SAMs) were patterned with extreme ultraviolet (λ = 13.5 nm) or electron beam irradiation and developed with ASD to achieve line space patterns as small as 50 nm. Density functional theory was employed to aid in the synthesis of hydroxamic acid derivatives with optimized packing density to enhance the imaging contrast and improve dose sensitivity. Near-edge X-ray absorption fine structure spectroscopy and infrared spectroscopy reveal that the imaging mechanism is based on improved deposition inhibition provided by the cross-linking of the SAM to produce a more effective barrier during a subsequent deposition step. With patterned substrates composed of coplanar copper lines and silicon spacers, hydroxamic acids selectively formed monolayers on the metal portions and could undergo a pattern-wise exposure followed by ASD in the first combination of a patternable monolayer with ASD. This material system presents an additional capability compared to traditional ASD approaches that generally reflect a starting patterned surface. Finally, this bottoms-up additive approach to lithography may be a viable alternative to subtractive nanoscale feature generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomistic mechanisms for catalytic transformations of NO to NH3, N2O, and N2 by Pd

The industrial pollutant NO is a potential threat to the environment and to human health. Thus, selective catalytic reduction of NO into harmless N2, NH3, and/or N2O gas is of great interest. Among many catalysts, metal Pd has been demonstrated to be most efficient for selectivity of reducing NO to N2. However, the reduction mechanism of NO on Pd, especially the route of N−N bond formation, remains unclear, impeding the development of new, improved catalysts. We report here the elementary reaction steps in the reaction pathway of reducing NO to NH3, N2O, and N2, based on density functional theory (DFT)-based quantum mechanics calculations. We show that the formation of N2O proceeds through an Eley-Rideal (E−R) reaction pathway that couples one adsorbed NO* with one non−adsorbed NO from the solvent or gas phase. This reaction requires high NO* surface coverage, leading first to the formation of the trans-(NO)2* intermediate with a low N−N coupling barrier (0.58 eV). Notably, trans-(NO)2* will continue to react with NO in the solvent to form N2O, that has not been reported. With the consumption of NO and the formation of N2O* in the solvent, the Langmuir-Hinshelwood (L-H) mechanism will dominate at this time, and N2O* will be reduced by hydrogenation at a low chemical barrier (0.42 eV) to form N2. In contrast, NH3 is completely formed by the L-H reaction, which has a higher chemical barrier (0.87 eV). Our predicted E-R reaction has not previously been reported, but it explains some existing experimental observations. In addition, we examine how catalyst activity might be improved by doping a single metal atom (M) at the NO* adsorption site to form M/Pd and show its influence on the barrier for forming the N−N bond to provide control over the product distribution.

Physics↗

Towards defect engineering in hexagonal MoS 2 nanosheets for tuning hydrogen evolution and nitrogen reduction reactions

Combined computational and experimental approaches were used to evaluate defective 2H-MoS 2 nanosheets for their activity and selectivity for hydrogen evolution reaction (HER) and nitrogen reduction reaction (NRR). Density functional theory calculations were used to understand the relationship between HER and NRR activity on the ideal basal MoS 2 plane, seven grain-boundaries, ten single-/few-atom vacancies and anti-sites, and zigzag and armchair edge sites. The results confirm that 2H-MoS 2 should contain several defects with high activity for HER: armchair and zigzag edges, VS vacancy, MoS 2 anti-site, and S-S and Mo-Mo grain boundaries. Considering Gibbs free energy change for all the steps in the NRR mechanism and kinetic barriers for a key NRR step, we have found that activation of perspective NRR selective sites in 2H-MoS 2 , namely V MoS6 and clusters of S-vacancies, would require large overpotential, conditions at which HER dominates. The DFT conclusions are supported by the electrochemical studies of NRR activity and selectivity under aqueous conditions, which show an increase in NRR activity but a decrease in Faradaic efficiency as applied cell potential becomes more negative. The results of this work therefore highlight the challenges in activating natural 2H-MoS 2 for NRR, which would require additional material engineering or reaction condition optimization as a way to suppress HER, decrease the NRR overpotential or preferentially both.

2H-MoS2↗

Incorporating Coverage-Dependent Reaction Barriers into First-Principles-Based Microkinetic Models: Approaches and Challenges

Mean-field microkinetic models (MKMs) are appealing for their relatively facile construction, computational tractability, and high-throughput catalyst screening capabilities. As such, they will continue to be a valuable tool for materials design in heterogeneous catalysis even as the field aims to describe more complex systems. Numerous prior reports have provided the groundwork for constructing first-principles-based MKMs, including the analysis of strategies for incorporating lateral interactions into thermodynamic parameters (e.g., adsorption energies). Yet, there remains a need for concerted dialogue on methods for calculating and incorporating coverage-dependent kinetic parameters into MKMs. In this Perspective, we assess strategies for doing so, including the corresponding key physical implications and computational challenges. Here, we emphasize that decoupling thermodynamic and kinetic parameters within MKMs can violate thermodynamic consistency and risk unphysical solutions. For some reactions and catalyst materials, scaling relationships can predict coverage-dependent activation energies, but there are several exceptions evident in the literature, indicating that this approach is not universally applicable and that the field could benefit from research aimed at elucidating the limitations. Conducting high-coverage transition state searches is a rigorous but computationally costly strategy, and the effects of various methods for mitigating this cost on resulting energetics have yet to be broadly explored and validated. The goal of this Perspective is to generate discussion on and inspire focused research into the physical relevance of approaches for describing coverage-dependent reaction barriers in MKMs, including the development of computationally tractable methodologies, to advance the applicability of MKMs across diverse reaction chemistries and conditions.

36 MATERIALS SCIENCE↗

External Magnetic Field Suppression of Carbon Diffusion in Iron

External magnetic fields reduce diffusion of carbon in BCC iron, but the physical mechanism is not understood. Using DFT calculations with magnetic moments sampled from a Heisenberg model, we calculate diffusivities of carbon in iron at high temperatures and with field. Our model reproduces the measured suppression of diffusivity from field. Here, we find that increasing magnetic disorder flattens the electron density of states compared with the ferromagnetic case, which distorts the octahedral cages around carbon, lowering the activation barrier to diffusion; an applied field reverses these trends.

36 MATERIALS SCIENCE↗

Synergy of Oxygen Vacancies and Base Sites for Transfer Hydrogenation of Nitroarenes on Ceria Nanorods

CeO 2 nanorod based catalysts for the base-free synthesis of azoxy-aromatics via transfer hydrogenation of nitroarenes with ethanol as hydrogen donor have been synthesized and investigated. The oxygen vacancies (O v ) and base sites are critical for their excellent catalytic properties. The O v , i.e., undercoordinated Ce cations, serve as the sites to activate ethanol and nitroarenes by lowering the energy barrier to transfer hydrogen from α–C sp3 –H in ethanol to the nitro group coupling it to the redox reactions between Ce 3+ and Ce 4+ . At the same time, the base sites catalyze the condensation step to selectively produce azoxy-aromatics. Finally, the catalytic route opens a much improved way to use non-noble metal oxides without additives for the selective functional group reduction and coupling reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Inverse design of two-dimensional graphene/h-BN hybrids by a regressional and conditional GAN

Design of materials with desired properties is currently laborious and heavily relies on intuition of researchers through a trial-and-error process. To tackle this challenge, in this work we propose a novel regressional and conditional generative adversarial network (RCGAN) for inverse design of representative two-dimensional materials, the graphene and boron-nitride (BN) hybrids. RCGAN incorporates a supervised regressor network, thus overcoming the common technical barrier in the traditional unsupervised GANs, which cannot generate data when fed with continuous and quantitative labels. RCGAN can autonomously generate graphene/BN hybrids given any target bandgap values. These structures are distinguished from the ones used for training and exhibit high diversity for a given bandgap. Moreover, they exhibit high fidelity, yielding bandgaps within ~10% MAE F of the desired bandgaps as validated by density functional theory (DFT) calculations. Analysis by the principle component analysis (PCA) and modified locally linear embedding (MLLE) reveals that the generator has successfully generated structures following the statistical distribution of the real structures. It implies the possibility of the RCGAN in recognizing physical rules hidden in the high-dimensional data. The novel strategy for designing regressional GAN architecture together with the successful application to inverse design of materials would inspire further exploration in research fields beyond materials.

36 MATERIALS SCIENCE↗

Unraveling the pathway towards superionic transport in polymer electrolytes

Ionic transport in polymers is critical for Li-ion batteries, fuel cells, flow batteries and many other energy storage and conversion technologies. A significant enhancement of ion conductivity in polymers may be achieved through an increase in the polarity of side chains and their self-organization into specific morphologies, which can potentially act as percolated ionic structures. However, higher polarity increases attractive interactions within a polymer matrix and slows down its segmental dynamics, which conversely hinders ionic transport. To overcome this tradeoff, we designed the functionalization of a Li salt-doped polymer matrix by tailored amounts of zwitterionic (ZI) groups. Our results suggest the emergence of a self-assembled percolation conductivity regime above a specific ZI concentration, in which ion hopping decouples from segmental dynamics by up to ten orders of magnitude. Consequently, in the highly concentrated ZI regime, our polymeric materials exhibit in their glassy state energy barriers for ion hopping similar to, or even smaller than, those reported for superionic ceramics. Our study also reveals that ion dynamics in the poly(zwitterion) with all monomers carrying ZI groups is significantly faster than that of a monomeric ZI compound, although the latter has much faster structural relaxation. Furthermore, this result highlights the crucial role played by the local morphology on the ion transport of polymer electrolytes and opens a new pathway for the design of superionic polymers, significantly expanding the current limited portfolio of solid-state electrolytes for energy applications.

Ion conductivity↗

Ca Cobaltites as Potential Cathode Materials for Rechargeable Ca-Ion Batteries: Theory and Experiment

Rechargeable Ca-based batteries can potentially achieve higher energy capacity than Li-ion batteries. The development of Ca-ion batteries, however, remains in its infancy, especially due to the challenge of finding cathode materials with high reversible capacity. In this work, we investigate properties of Ca cobaltites as Ca-ion intercalation cathodes, by means of density functional theory calculations validated by synthesis and electrochemical measurements. Computationally, we accessed thermodynamic, diffusion properties, energy capacity, and the voltage profiles for four Ca cobaltite compounds of different stoichiometry and Co oxidation states: Ca 3 Co 2 O 6 , CaCo 2 O 4 , Ca 2 Co 2 O 5 , and [Ca 2 CoO 3 ][CoO 2 ] 1.62 . We found good stability and relatively low migration barriers of some Ca cobaltites during cycling with the layered CaCo 2 O 4 having the lowest Ca migration barrier of 0.7 eV and the highest theoretical capacity. To validate our calculations, we synthesized Ca 3 Co 2 O 6 , CaCo 2 O 4 , and [Ca 2 CoO 3 ][CoO 2 ] 1.62 with the Pechini method and, subsequently, to test the electrochemical extraction of Ca.

25 ENERGY STORAGE↗

Machine learning enabling high-throughput and remote operations at large-scale user facilities

Imaging, scattering, and spectroscopy are fundamental in understanding and discovering new functional materials. Contemporary innovations in automation and experimental techniques have led to these measurements being performed much faster and with higher resolution, thus producing vast amounts of data for analysis. These innovations are particularly pronounced at user facilities and synchrotron light sources. Machine learning (ML) methods are regularly developed to process and interpret large datasets in real-time with measurements. However, there remain conceptual barriers to entry for the facility general user community, whom often lack expertise in ML, and technical barriers for deploying ML models. Herein, we demonstrate a variety of archetypal ML models for on-the-fly analysis at multiple beamlines at the National Synchrotron Light Source II (NSLS-II). We describe these examples instructively, with a focus on integrating the models into existing experimental workflows, such that the reader can easily include their own ML techniques into experiments at NSLS-II or facilities with a common infrastructure. The framework presented here shows how with little effort, diverse ML models operate in conjunction with feedback loops via integration into the existing Bluesky Suite for experimental orchestration and data management.

36 MATERIALS SCIENCE↗

Uranium (VI) Adsorbate Structures on Portlandite [Ca(OH)2] Type Surfaces Determined by Computational Modelling and X-ray Absorption Spectroscopy

Portlandite [Ca(OH) 2 ] is a potentially dominant solid phase in the high pH fluids expected within the cementitious engineered barriers of Geological Disposal Facilities (GDF). This study combined X-ray Absorption Spectroscopy with computational modelling in order to provide atomic-scale data which improves our understanding of how a critically important radionuclide (U) will be adsorbed onto this phase under conditions relevant to a GDF environment. Such data are fundamental for predicting radionuclide mass transfer. Surface coordination chemistry and speciation of uranium with portlandite [Ca(OH) 2 ] under alkaline groundwater conditions (ca. pH 12) were determined by both in situ and ex situ grazing incidence extended X-ray absorption fine structure analysis (EXAFS) and by computational modelling at the atomic level. Free energies of sorption of aqueous uranyl hydroxides, [UO 2 (OH) n ] 2–n (n = 0–5) with the (001), (100) and (203) or (101) surfaces of portlandite are predicted from the potential of mean force using classical molecular umbrella sampling simulation methods and the structural interactions are further explored using fully periodic density functional theory computations. Although uranyl is predicted to only weakly adsorb to the (001) and (100) clean surfaces, there should be significantly stronger interactions with the (203/101) surface or at hydroxyl vacancies, both prevalent under groundwater conditions. The uranyl surface complex is typically found to include four equatorially coordinated hydroxyl ligands, forming an inner-sphere sorbate by direct interaction of a uranyl oxygen with surface calcium ions in both the (001) and (203/101) cases. In contrast, on the (100) surface, uranyl is sorbed with its axis more parallel to the surface plane. The EXAFS data are largely consistent with a surface structural layer or film similar to calcium uranate, but also show distinct uranyl characteristics, with the uranyl ion exhibiting the classic dioxygenyl oxygens at 1.8 Å and between four and five equatorial oxygen atoms at distances between 2.28 and 2.35 Å from the central U absorber. These experimental data are wholly consistent with the adsorbate configuration predicted by the computational models. These findings suggest that, under the strongly alkaline conditions of a cementitious backfill engineered barrier, there would be significant uptake of uranyl by portlandite to inhibit the mobility of U(VI) from the near field of a geological disposal facility.

36 MATERIALS SCIENCE↗