Fluorescent Probe of Aminopolymer Mobility in Bulk and in Nanoconfined Direct Air CO 2 Capture Supports
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36 MATERIALS SCIENCE↗
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Structure of Water Adsorbed on Nanocrystalline Calcium Silicate Hydrate Determined from Neutron Scattering and Molecular Dynamics Simulations
Calcium silicate hydrate (C-S-H) is a disordered, nanocrystalline material that acts as a primary binding phase in Portland cement. Thin films of water are present on the surfaces and in nanopores of C-S-H, impacting many of its chemical and mechanical properties, such as ion transport, creep, or thermal behavior. Despite decades of research, a full understanding of the structural details of adsorbed, confined, and bulk water in C-S-H remains elusive. In this work, we applied a multitechnique study involving molecular dynamics (MD) simulations validated by neutron diffraction with isotopic substitution (NDIS) and X-ray scattering methods to investigate the structure of water in C-S-H and C-A-S-H (an Al-bearing, low-CO 2 C-S-H substitute). Direct comparison of NDIS data with the MD results reveals that the structure of confined and interfacial water differs significantly from the bulk water and exhibits a larger degree of mesoscale ordering for more hydrated C-S-H structures. As a result, this observation suggests an important role of water as a stabilizer of the atomistic-level structure of C-S-H.
36 MATERIALS SCIENCE↗
Water Adsorption on Mica Surfaces with Hydrophilicity Tuned by Counterion Types (Na, K, and Cs) and Structural Fluorination
Not Available
36 MATERIALS SCIENCE↗
Large-Scale Molecular Dynamics Simulation of the Dehydration of a Suspension of Smectite Clay Nanoparticles
Fine-grained sediments and sedimentary rocks play important roles in a variety of modern energy technologies from petroleum geology to geological carbon sequestration and radioactive waste management. However, despite their utility and ubiquity, many of their properties remain poorly understood. In particular, the ability to predict the permeability and mechanics of these media remains a persistent fundamental challenge in the geosciences. In the present work, we show how large-scale classical molecular dynamics (MD) simulations can help interpret the properties of fine-grained sedimentary material. All-atom simulations containing 30 discrete clay particles are utilized to understand the evolution of a clay nanoparticle suspension during its progressive dehydration. Microstructural (pore size distribution, tortuosity, anisotropy), thermodynamic (enthalpy and free energy of hydration, anion exclusion), mechanical (total suction), and transport properties (diffusion coefficient tensors of water and sodium) are calculated and compared to the experiment. Overall, our results provide new insight into the coupled chemistry, mechanics, and transport properties of disordered nanoparticle assemblages and shed light upon the important role of water films in controlling these properties.
02 PETROLEUM↗
Electrochemical Hydrogenation of CO on Cu(100): Insights from Accurate Multiconfigurational Wavefunction Methods
Copper (Cu) remains the most efficacious electrocatalyst for electrochemical CO 2 reduction (CO 2 R). Its activity and selectivity are highly facet-dependent. We recently examined the commonly proposed rate-limiting CO hydrogenation step on Cu(111) via embedded correlated wavefunction (ECW) theory and demonstrated that only this higher-level theory yields predictions consistent with potential-dependent experimental kinetics. Here, to understand the differing activities of Cu(111) and Cu(100) in catalyzing CO 2 R, we explore CO hydrogenation on Cu(100) using ECW theory. We predict that the preferred pathway involves the reduction of adsorbed CO (*CO) to *COH via proton-coupled electron transfer (PCET) at working potentials, although *CHO also may form with a kinetically accessible but higher barrier. In contrast, our earlier work on Cu(111) concluded that *COH and *CHO formation via PCET are equally feasible. Furthermore, this work illustrates one possible origin of the facet dependence of CO 2 R mechanisms and products on Cu electrodes and sheds light on how the selectivity of CO 2 R electrocatalysts can be controlled by the surface morphology.
30 DIRECT ENERGY CONVERSION↗
Revisiting Understanding of Electrochemical CO 2 Reduction on Cu(111): Competing Proton-Coupled Electron Transfer Reaction Mechanisms Revealed by Embedded Correlated Wavefunction Theory
Copper (Cu) electrodes, as the most efficacious of CO 2 reduction reaction (CO 2 RR) electrocatalysts, serve as prototypes for determining and validating reaction mechanisms associated with electrochemical CO 2 reduction to hydrocarbons. As in situ electrochemical mechanism determination by experiments is still out of reach, such mechanistic analysis typically is conducted using density functional theory (DFT). The semilocal exchange-correlation (XC) approximations most often used to model such catalysis unfortunately engender a basic error: predicting the wrong adsorption site for CO (a key CO 2 RR intermediate) on the most ubiquitous facet of Cu, namely, Cu(111). This longstanding inconsistency casts lingering doubt on previous DFT predictions of the attendant CO 2 RR kinetics. Here, we apply embedded correlated wavefunction (ECW) theory, which corrects XC functional error, to study the CO 2 RR on Cu(111) via both surface hydride (*H) transfer and proton-coupled electron transfer (PCET). We predict that adsorbed CO (*CO) reduces almost equally to two intermediates, namely, hydroxymethylidyne (*COH) and formyl (*CHO) at –0.9 V vs the RHE. In contrast, semilocal DFT approximations predict a strong preference for *COH. With increasing applied potential, the dominance of *COH (formed via potential-independent surface *H transfer) diminishes, switching to the competitive formation of both *CHO and *COH (both formed via potential-dependent PCET). Furthermore, our results also demonstrate the importance of including explicitly modeled solvent molecules in predicting electron-transfer barriers and reveal the pitfalls of overreliance on simple surface *H transfer models of reduction reactions.
30 DIRECT ENERGY CONVERSION↗
Surface Energy Balance Responses to Radiative Forcing in the Central Arctic From MOSAiC and Models
The Arctic surface energy budget (SEB) couples the atmosphere with the sea ice, making it useful for both studying surface processes as well as evaluating models. Improved understanding of atmosphere-ice interactions is required to improve models, requiring year-round observations to address seasonally dependent biases. This work uses novel observations from the MOSAiC expedition to quantify the responses of surface fluxes to radiative forcing over sea ice throughout a complete annual cycle. We identify two primary regimes of flux response: an ice growth regime in winter and an ice melt regime in summer. In the growth regime, changes in radiative forcing impact upwelling longwave, sensible heat, and subsurface heat fluxes, whereas in the melt regime changes in radiative forcing primarily alter the amount of melt and subsurface transmission because the surface temperature is fixed. These observed responses of surface fluxes to radiative forcing are used to evaluate seven weather forecast models during the ice growth regime. In most models, the responses of surface fluxes to radiative forcing do not match observations. Many models also have biased downwelling longwave. One model (the Coupled Arctic Forecast System; CAFS) adequately captures both the mean radiative forcing and the flux responses in winter. CAFS is further evaluated against observations spanning the full MOSAiC year, demonstrating sufficient agreement to provide a more generalized understanding of these SEB process relationships across the Arctic.
54 ENVIRONMENTAL SCIENCES↗
Recommendations for Comprehensive and Independent Evaluation of Machine Learning‐Based Earth System Models
Abstract Machine learning (ML) is a revolutionary technology with demonstrable applications across multiple disciplines. Within the Earth science community, ML has been most visible for weather forecasting, producing forecasts that rival modern physics‐based models. Given the importance of deepening our understanding and improving predictions of the Earth system on all time scales, efforts are now underway to develop Earth‐system models (ESMs) capable of representing all components of the coupled Earth system (or their aggregated behavior) and their response to external changes over long timescales. Building trust in ESMs is a much more difficult problem than for weather forecast models, not least because the model must represent the alternate (e.g., future or paleoclimatic) coupled states of the system for which there are no direct observations. Given that the physical principles that enable predictions about the response of the Earth system are often not explicitly coded in these ML‐based models, demonstrating the credibility of ML‐based ESMs thus requires us to build evidence of their consistency with the physical system. To this end, this paper puts forward five recommendations to enhance comprehensive, standardized, and independent evaluation of ML‐based ESMs to strengthen their credibility and promote their wider use.
54 ENVIRONMENTAL SCIENCES↗
Trade-offs in land-based carbon removal measures under 1.5 °C and 2 °C futures
Land-based carbon removals, specifically afforestation/reforestation and bioenergy with carbon capture and storage (BECCS), vary widely in 1.5 °C and 2 °C scenarios generated by integrated assessment models. Because underlying drivers are difficult to assess, we use a well-known integrated assessment model, GCAM, to demonstrate that land-based carbon removals are sensitive to the strength and scope of land-based mitigation policies. We find that while cumulative afforestation/reforestation and BECCS deployment are inversely related, they are both typically part of cost-effective mitigation pathways, with forestry options deployed earlier. While the CO 2 removal intensity (removal per unit land) of BECCS is typically higher than afforestation/reforestation over long time horizons, the BECCS removal intensity is sensitive to feedstock and technology choices whereas the afforestation/reforestation removal intensity is sensitive to land policy choices. Finally, we find a generally positive relationship between agricultural prices and removal effectiveness of land-based mitigation, suggesting that some trade-offs may be difficult to avoid.
54 ENVIRONMENTAL SCIENCES↗
Ion correlations drive charge overscreening and heterogeneous nucleation at solid–aqueous electrolyte interfaces
Significance Ion distributions at charged solid–water interfaces, referred to as the electrical double layer (EDL), are poorly understood at high ion concentrations, in part due to the lack of molecular-scale descriptions of the interactions between adsorbed hydrated ions. Here, direct visualization of the salinity-dependent evolution of EDL structure reveals molecular origins of nonclassical transformation of the EDL, in which charge overscreening and heterogeneous nucleation are driven by ion–ion correlations at the interfaces. This manifestation of the atomistic basis of nonclassical behaviors provides a much-needed understanding of the impact of ion cooperativity at charged interfaces for the development of predictive models for element transport in natural environments and advanced technologies for material growth and synthesis in saline environments.
36 MATERIALS SCIENCE↗
Charting C–C coupling pathways in electrochemical CO 2 reduction on Cu(111) using embedded correlated wavefunction theory
The electrochemical CO 2 reduction reaction (CO 2 RR) powered by excess zero-carbon-emission electricity to produce especially multicarbon (C 2+ ) products could contribute to a carbon-neutral to carbon-negative economy. Foundational to the rational design of efficient, selective CO 2 RR electrocatalysts is mechanistic analysis of the best metal catalyst thus far identified, namely, copper (Cu), via quantum mechanical computations to complement experiments. Here, we apply embedded correlated wavefunction (ECW) theory, which regionally corrects the electron exchange-correlation error in density functional theory (DFT) approximations, to examine multiple C–C coupling steps involving adsorbed CO (*CO) and its hydrogenated derivatives on the most ubiquitous facet, Cu(111). We predict that two adsorbed hydrogenated CO species, either *COH or *CHO, are necessary precursors for C–C bond formation. The three kinetically feasible pathways involving these species yield all three possible products: *COH–CHO, *COH–*COH, and *OCH–*OCH. The most kinetically favorable path forms *COH–CHO. In contrast, standard DFT approximations arrive at qualitatively different conclusions, namely, that only *CO and *COH will prevail on the surface and their C–C coupling paths produce only *COH–*COH and *CO–*CO, with a preference for the first product. This work demonstrates the importance of applying qualitatively and quantitatively accurate quantum mechanical method to simulate electrochemistry in order ultimately to shed light on ways to enhance selectivity toward C 2+ product formation via CO 2 RR electrocatalysts.
30 DIRECT ENERGY CONVERSION↗
Demystifying group-4 polyolefin hydrogenolysis catalysis: Gaseous propane hydrogenolysis mechanism over the same catalysts
A kinetic/mechanistic investigation of gaseous propane hydrogenolysis over the single-site heterogeneous polyolefin depolymerization catalysts AlS/ZrNp 2 and AlS/HfNp 2 (AlS = sulfated alumina, Np = neopentyl), is use to probe intrinsic catalyst properties without the complexities introduced by time- and viscosity-dependent polymer medium effects. In a polymer-free automated plug-flow catalytic reactor, propane hydrogenolysis turnover frequencies approach 3,000 h −1 at 150 °C. Both catalysts exhibit approximately linear relationships between rate and [H 2 ] at substoichiometric [H 2 ] with rate law orders of 0.66 ± 0.09 and 0.48 ± 0.07 for Hf and Zr, respectively; at higher [H 2 ], the rates approach zero-order in [H 2 ]. Reaction orders in [C 3 H 8 ] and [catalyst] are essentially zero-order under all conditions, with the former implying rapid, irreversible alkane binding/activation. This rate law, activation parameter, and DFT energy span analysis support a scenario in which [H 2 ] is pivotal in one of two plausible and competing rate-determining transition states—bimolecular metal-alkyl bond hydrogenolysis vs. unimolecular β-alkyl elimination. The Zr and Hf catalyst activation parameters, ΔH ‡ = 16.8 ± 0.2 kcal mol −1 and 18.2 ± 0.6 kcal mol −1 , respectively, track the relative turnover frequencies, while ΔS ‡ = −19.1 ± 0.8 and −16.7 ± 1.4 cal mol −1 K −1 , respectively, imply highly organized transition states. These catalysts maintain activity up to 200 °C, while time-on-stream data indicate multiday activities with an extrapolated turnover number ~92,000 at 150 °C for the Zr catalyst. This methodology is attractive for depolymerization catalyst discovery and process optimization.
03 NATURAL GAS↗
Quantifying and simulating the weather forecast uncertainty for advanced building control
Weather forecast uncertainty is unavoidable despite technological advancements. Accurately quantifying and modelling this uncertainty is essential for developing and comparing advanced building controllers. In this study, we present a structured approach using a first-order autoregressive model (AR(1)) to model uncertainty in ambient temperature and global solar irradiation (GHI) forecasts. We analyzed weather data from four cities and employed Jensen–Shannon divergence (JSD) to evaluate the similarity between synthetic and actual forecast errors. The average JSD values for temperature are 0.027 (Berkeley), 0.021 (Leuven), 0.018 (Berlin), and 0.008 (Oslo), and for GHI, the average JSD values are 0.016 (Berkeley), 0.058 (Leuven), and 0.013 (Berlin). The low JSD values indicate a high similarity between the synthetic and real forecast error distributions. Further, our approach successfully generates synthetic weather forecasts that mirror the statistical properties of actual forecasts. The implementation of our method for uncertain forecast generation is being added to the BOPTEST framework.
54 ENVIRONMENTAL SCIENCES↗
The joys and jitters of high‐temperature calorimetry
Abstract High‐temperature calorimetry (HTC) originated in the 20th century as a niche method to enable measurements not easily accomplished with acid solution calorimetry, combustion calorimetry, vapor pressure, or EMF methods. Over time, HTC has evolved into a versatile approach to accurately quantify formation, phase transition, surface and interfacial enthalpies of a wide range of materials including minerals and refractory inorganic compounds. This evolution has been the result of numerous adjustments to experimental setups and procedures, followed by rigorous testing. The commercial availability and the scientific success of this technique have led to an increase in the number of laboratories applying HTC. However, the knowledge acquired by researchers over the past 70 years is scattered throughout the literature or only available as laboratory internal documentation and personal experience. This publication is a collaborative effort among several leading HTC laboratories to summarize and unify current state‐of‐the‐art HTC techniques and procedures. The text starts by summarizing various HT techniques that are commonly used for readers with an interest in HTC in general. It is then directed toward HTC users and includes a brief section on data evaluation procedures as well as a comprehensive compilation of reference data utilizing molten sodium molybdate and lead borate solvents. Finally, for experienced HTC users, an in‐depth discussion of some common difficulties and a discussion of uncertainties are presented.
Scharrer, Manuel [Navrotsky Eyring Center for Mate↗
Arbuscular mycorrhiza convey significant plant carbon to a diverse hyphosphere microbial food web and mineral‐associated organic matter
Summary Arbuscular mycorrhizal fungi (AMF) transport substantial plant carbon (C) that serves as a substrate for soil organisms, a precursor of soil organic matter (SOM), and a driver of soil microbial dynamics. Using two‐chamber microcosms where an air gap isolated AMF from roots, we 13 CO 2 ‐labeled Avena barbata for 6 wk and measured the C Rhizophagus intraradices transferred to SOM and hyphosphere microorganisms. NanoSIMS imaging revealed hyphae and roots had similar 13 C enrichment. SOM density fractionation, 13 C NMR, and IRMS showed AMF transferred 0.77 mg C g −1 of soil (increasing total C by 2% relative to non‐mycorrhizal controls); 33% was found in occluded or mineral‐associated pools. In the AMF hyphosphere, there was no overall change in community diversity but 36 bacterial ASVs significantly changed in relative abundance. With stable isotope probing (SIP)‐enabled shotgun sequencing, we found taxa from the Solibacterales, Sphingobacteriales, Myxococcales, and Nitrososphaerales (ammonium oxidizing archaea) were highly enriched in AMF‐imported 13 C (> 20 atom%). Mapping sequences from 13 C‐SIP metagenomes to total ASVs showed at least 92 bacteria and archaea were significantly 13 C‐enriched. Our results illustrate the quantitative and ecological impact of hyphal C transport on the formation of potentially protective SOM pools and microbial roles in the AMF hyphosphere soil food web.
13C SIP↗
The status and prospects of materials for carbon capture technologies
In order to combat climate change, carbon dioxide (CO 2 ) emissions from industry, transportation, buildings, and other sources need to be captured and long-term stored. Decarbonization of these sources requires special types of materials that have high affinities for CO 2 . Potassium hydroxide is a benchmark aqueous sorbent that reacts with CO 2 to convert it into K 2 CO 3 and subsequently precipitated as CaCO 3 . Another class of carbon capture materials is solid sorbents that are usually functionalized with amines or have natural affinities for CO 2 . The next wave of materials for carbon capture under investigation includes activated carbon, metal–organic frameworks, zeolites, carbon nanotubes, and ionic liquids. In this issue of MRS Bulletin, some of these materials are highlighted, including solvents and sorbents, membranes, ionic liquids, and hydrides. Other materials that can capture CO2 from low concentrations of gas streams, such as air (direct air capture) are also discussed. Also covered in this issue are machine learning-based computer algorithms developed with the goal to speed up the progress of carbon capture materials development, and to design advanced materials with high CO 2 capacity, improved capture and release kinetics, and improved cyclic durability.
36 MATERIALS SCIENCE↗
Actinide Research Quarterly, First Quarter 2020: 25 Years, Commemorative Issue, 9 Articles from the Archive
This quarter we are celebrating the 25 th anniversary of Actinide Research Quarterly. The publication was established in 1995 by the former Nuclear Materials Technology Division of TA-55 at Los Alamos National Laboratory (LANL), before later becoming part of the Glenn T. Seaborg Institute and the National Security Education Center. A total of 64 issues have been produced, covering the full spectrum of topics related to actinide science and research, including contributions from esteemed scientists such as Glenn Seaborg and Siegfried Hecker. This back catalog is available electronically at www.lanl.gov/arq.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Evaluating Precision of Measured Radionuclide Ambient Air Concentrations
According to AIRNET – Quality Assurance Project Plan for the Radiological Air Sampling Network, SOP-5140, Revision 2 (to become EPC-CP-PIP-5140): “The regulation 40 CFR Part 61.93 requires that the system be able to readily detect a dose of 1.0 mrem above background. Following statistical principles and assuming 95% confidence for such a measurement, we require that 95% of all measurements must fall within two standard deviations of the mean. This represents the minimum acceptable precision for decision making.” An independent assessment of the Rad-NESHAP program completed in early 2019 found that no documentation existed proving that the Airnet data meets the precision defined above. Therefore, to address this particular finding, Airnet concentration data was pulled from the Environmental Information Management (EIM), a cloud-based database maintained by Locus Technologies, for analysis.
54 ENVIRONMENTAL SCIENCES↗