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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Assessing the use of portable air cleaners for reducing exposure to airborne diseases in a conference room with thermal stratification

The COVID-19 pandemic has highlighted the need for strategies that mitigate the risk of aerosol disease transmission in indoor environments with different ventilation strategies. It is necessary for building operators to be able to estimate and compare the relative impacts of different mitigation strategies to determine suitable strategies for a particular situation. Using a validated CFD model, this study simulates the dispersion of exhaled contaminants in a thermally stratified conference room with overhead heating. The impacts of portable air-cleaners (PACs) on the room airflow and contaminant distribution were evaluated for different PAC locations and flow rates, as well as for different room setups (socially distanced or fully occupied). To obtain a holistic view of a strategy's impacts under different release scenarios, we simultaneously model the steady-state distribution of aerosolized virus contaminants from eight distinct sources in 18 cases for a total of 144 release scenarios. The simulations show that the location of the source, the PAC settings, and the room set-up can impact the average exposure and PAC effectiveness. For this studied case, the PACs reduced the room average exposure by 31%-66% relative to the baseline case. Some occupant locations were shown to have a higher-than-average exposure, particularly those seated near the airflow outlet, and occupants closest to sources tended to see the highest exposure from said source. We found that these PACs were effective at reducing the stratification caused by overhead heating, and also identified at least one sub-optimal location for placing a PAC in this space.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Application of reference-free natural background–oriented schlieren photography for visualizing leakage sites in building walls

Air leakage in buildings can cause health and comfort concerns for occupants and can contribute to mold growth on building materials, or in extreme conditions, rot of building materials. Unwanted air leakage through the building envelope also contributes to approximately 4 quadrillion Btu (1172 TWh) of energy consumption per year in the building sector in the United States. Locating and sealing leakage sites can improve the energy efficiency, comfort, air quality, and moisture durability of the building stock. Typical methods of finding leakage sites, such as infrared imaging and smoke tracing, rely on concurrent blower door operation, which can also measure the total leakage rate of the building. Smoke tracing can be disruptive to occupants, and infrared imaging and smoke tracing cannot measure the contribution of individual leaks to prioritize sealing efforts. Here, an optical fluid flow imaging technique, reference-free natural background–oriented schlieren imaging, was adapted to visualize air exfiltration. This is the first step in developing a method to noninvasively locate and measure exfiltration or infiltration sites so that sealing efforts can be prioritized. Experimental results of this technique are presented, demonstrating the method's applicability to visualizing exfiltration through three common building claddings in an outdoor environment. Key variables impacting the performance of this technique when applied to building leakage are also discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Field validation of isotropic analytical models for simulating fabric shades

Fabric roller shades are common shading materials used in commercial and residential buildings. Accurately characterizing and modeling shades helps practitioners select the appropriate product and its control strategy based on climate and occupants' priorities, such as visual comfort and view to outdoors. Previous studies established a generalized method for modeling complex fenestration systems using data-driven tabulated bidirectional scattering distribution functions. However, deploying such a method at scale to all fabric shading products on the market is too costly and time-consuming. Analytical models that are based on a limited set of measurements (e.g., normal-normal and normal-hemispherical visible transmittance and reflectance, and directional cut-off angles) can be used to model the wide variety of shading products on the market. This study evaluates the performance of two isotropic analytical models, Roos-Wienold and Modified-Kotey, for modeling fabric roller shades, with a focus on the model's ability to predict occupant visual comfort. The performance evaluation was conducted through laboratory and field measurements and simulations. The results showed that both models are sufficient for predicting vertical illuminance at seated eye-level. Roos-Wienold model was able to predict binary visual comfort classification (glare/no-glare) under a wide range of luminance conditions, while Modified-Kotey model did not perform as well under high-contrast low-adaptation conditions. Both models are insufficient in predicting visual comfort at a four-point scale (e.g., imperceptible, perceptible, disturbing, intolerable). The two isotropic models become less accurate when the fabric exhibits high anisotropy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Influence of overhead HVAC and aerosol control strategies on coarse mode particle dispersion and exposure in a full-scale room experiment

Coarse mode respiratory aerosols can carry viral loads over long distances and have very different dynamics than submicron particles, but experimental studies under realistic conditions remain limited. Here, to study the differential impacts on exposure under different mixing conditions, we co-released 7–10 µm particles and carbon dioxide (CO 2 )—which served as an indicator of gas and submicron particle dynamics—in a 158 m 3 room at LBNL's FLEXLAB facility with an overhead heating, ventilation, and air conditioning (HVAC) system. The room was arranged as a distanced meeting then a classroom with eight heated manikins and a researcher. Spatial variability was measured using 16 particle counters and 22–26 CO 2 sensors throughout the space. Conditions included: HVAC off or supply air at 1000-1060 m 3 h -1 at neutral, cooling, or heating temperatures; with and without 20% outdoor air; and added HVAC filtration, portable air cleaners (PACs), or a physical barrier between the speaker and occupants. We found that good mixing via neutral or cooling supply air or use of PACs under heating lowered coarse particle exposure at some locations, but increased exposure for one-quarter to two-thirds of manikins compared to poor mixing under heating. A physical barrier reduced direct transfer of coarse particles during heating, but less during cooling. High spatial variability shows that a single measurement cannot represent occupant exposure. Instantaneous air mixing assumptions overstate the effectiveness of ventilation, HVAC filtration, and upper-room germicidal ultraviolet disinfection for coarse particles, as relatively few particles reach the return grille or upper room under most conditions.

Air mixing↗
DOE OSTI2021

Multisublattice cluster expansion study of short-range ordering in iron-substituted strontium titanate

Owing to the challenges in obtaining realistic atomic configurations in large chemical phase spaces, it is not straightforward to describe structure–property relations in materials exhibiting configurational disorder. One example is iron-substituted strontium titanate (SrTi 1–x Fe x O 3–d , STF), a promising perovskite-derivative cathode material in solid oxide fuel cells that exhibits full solid solubility 0 ≤ x ≤ 1 and a tendency to exhibit short-range order. Here we demonstrate a multisublattice cluster expansion (CE) framework and apply it to STF across the full composition range. The CE approach is distinct from more traditional CE formulations in that clusters are defined explicitly by the chemical species distributed among multiple sublattices, rather than via cluster functions of occupation variables with decoration. The modified CE approach makes it easy to distinguish meaningful chemical interactions that are harder to extract from conventional CE, since for the latter chemical identity in a cluster is expressed as a product of site occupations. The least absolute shrinkage and selection operator (LASSO) is implemented as a regression analysis tool to select key clusters and avoid overfitting. We demonstrate this formulation on STF, and show that it can accurately predict configurational energies in comparison to conventional CE. From the key clusters, we identify that short-range ordering between substitutional Fe and oxygen vacancies (V O ) results in the formation of Fe–VO strings. In addition, we consider the stability of STF through CE-based Monte Carlo (MC) simulations and confirm the presence of superstructures that were previously observed in transmission electron microscopy. In this work, analysis of atomic configurations from MC samples reveals variations in the oxidation state of Fe atoms, which can be explained by the ordering tendency of Fe and V O . The cluster description and selection formalism described here may be applied to other disordered multisublattice systems for accurate and efficient material modeling.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics

In recent years deep neural networks have been proposed as a lightweight data-driven model to capture high-dimensional, nonlinear physical processes to predict building thermal responses. However, the need of a large amount of data for the training process of deep neural networks clashes with the potential limited data availability in most existing or new buildings. Transfer learning aims to enhance the performance of a target learner exploiting knowledge from related and similar environments. This study conducted a suite of experiments that leveraged 250 data-driven models based on a synthetic dataset of a building archetype to study the influence of data availability, energy efficiency level, occupancy and climate for the transfer process of thermal dynamics. The performance of the transfer learning process was compared against a classical machine learning approach. Here, the results suggest that building thermal dynamics can be effectively transferred under the same climatic conditions, increasing performance when dealing with different occupancy schedules, efficiency levels and low data availability. Furthermore, the paper compares the performance of both transfer learning and machine learning approaches in an online fashion, to support the implementation in real-world deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Decarbonizing residential buildings in the United States: A comparative analysis of households and construction professionals

In this study, we present a comparative analysis of surveys distributed to home occupants and construction professionals in the U.S., focused on energy upgrades and electrification retrofits that support residential building decarbonization. The surveys were executed by separate research groups and combined for this study. The study examines the decision-making, sentiments, perceptions, experiences, and practices of both groups by analyzing data from three separate surveys. These surveys assess technologies, attitudes, awareness, motivations, barriers, and opportunities related to energy retrofits and electrification. The analysis highlights key differences in the perceptions and behaviors of households and construction professionals, revealing substantial barriers to achieving decarbonization goals. For example, households cite climate change and sustainability as key motivators for pursuing energy retrofits (89%), while construction industry professionals view these themes as less important for their clients (44%). This suggests an opportunity for the construction industry to align its messaging with the values that households prioritize, helping to advance residential decarbonization. Overall, the study identifies challenges faced by both groups, factors influencing the adoption of energy-efficient practices, and inconsistencies between occupant and construction industry professionals' views. These insights contribute to the development of targeted strategies and policies to accelerate the decarbonization of residential buildings in the U.S.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Effect of Si/Al ratio of ZSM-5 support on structure and activity of Mo species in methane dehydroaromatization

The effect of the Si/Al ratio of the ZSM-5 support on the structure and activity of Mo/HZSM-5 catalysts in methane dehydroaromatization (MDA) was studied. ZSM-5 (with Si/Al = 15, 25, and 40) supported Mo oxide catalysts (MoOx/ZSM-5) with 3 and 10 wt% Mo loading were prepared by incipient wetness impregnation followed by calcination in air at 500 °C. The as-prepared catalysts were activated by temperature programmed reduction in hydrogen in order to maximize Mo dispersion. To understand the structure-activity relationship, the fresh and spent samples were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), N2 adsorption isotherms, Scanning Transmission Electron Microscopy with Energy Dispersive X-Ray Spectroscopy (STEM-EDS), X-ray absorption spectroscopy (EXAFS and XANES), thermogravimetric analysis (TGA), and Raman spectroscopy. The results show that the Si/Al ratio does not influence the the local structure around the Mo centers. It does however affect the number of available Brønsted acid sites in the support and the amount of Mo species entering the zeolite channels. A lower Si/Al ratio and higher Mo loading resulted in a higher Mo occupation within the zeolite channels. The higher channel occupation directly correlated with higher benzene selectivity and yield, as well as a lower catalyst deactivation rate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Advances in Desiccant Wheels for Dehumidification, VOC Mitigation, and CO 2 Removal for Energy-Efficient IAQ Management

Humidity control is pivotal to maintain occupant thermal comfort and suppress mold growth in indoor environments. Furthermore, poor indoor air quality (IAQ) due to the presence of volatile organic compounds (VOCs) and high concentrations (>1,000 ppm) of CO 2 can cause health issues and negatively affect cognitive performance. Therefore, providing high-quality indoor air has gained significant attention over the past decade. Conventional cooling coil and filter-based HVAC systems have limited capability to meet the augmented demand for occupant thermal comfort and high indoor air quality. Moreover, modern buildings are increasingly airtight to save energy, and increasing ventilation to mitigate VOC and CO 2 concentration is discouraged. Separate sensible and latent cooling technology using a rotary desiccant wheel presents a promising solution in this respect. Because of the development of desiccant materials with high water vapor, VOC, and CO 2 uptake, desiccant wheels can be used as an integrated technology option for IAQ management. Here, to promote desiccant wheel use for energy-efficient management of IAQ in buildings, this article reviews recent advancements in using desiccant wheels for dehumidification, VOC mitigation, and CO 2 capture from outdoor air. Finally, the article presents the authors’ perspective by summarizing the key research gaps in the field and discussing the future direction of research to address these gaps from two different aspects, namely, suitable adsorbent material development and desiccant wheel design.

CO2 capture↗
DOE OSTI2021

Crystal structure of the $τ_{11}$ Al 4 Fe 1.7 Si phase from neutron diffraction and ab initio calculations

The intermetallic τ 11 Al 4 Fe 1.7 Si phase is of interest for high-temperature structural application due to its combination of low density and high strength. We determine the crystal structure of the τ 11 phase through a combination of powder neutron diffraction and density functional theory calculations. Using Pawley and Rietveld refinements of the neutron diffraction data provides an initial crystal structure model. Since Al and Si have nearly identical neutron scattering lengths, we use density-functional calculations to determine their preferred site occupations. The τ 11 phase exhibits a hexagonal crystal structure with space group P6 3 /mmc and lattice parameters of a = 7.478 Å and c = 7.472 Å. The structure comprises five Wyckoff positions; Al occupies the 6h and 12k sites, Fe the 2a and 6h sites, and Si the 2a sites. Here we observe site disorder and partial occupancies on all sites with a large fraction of 80% Fe vacancies on the 2d sites, indicating an entropic stabilization of the τ 11 phase at high temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A density functional theory and neutron diffraction study of the ambient condition properties of sub-stoichiometric yttrium hydride

Several mechanical and thermophysical properties are required as a function of non-stoichiometry for the successful implementation of YH 2-x for nuclear reactor moderator applications. Density functional theory calculations, in combination with neutron diffraction experiments, were used to study the structural and mechanical properties of YH 2-x . Point defect analysis indicated H occupation primarily at the tetrahedral site within an fcc Y sub-lattice, confirming a fluorite YH 2 structure. The small positive formation energy for H vacancies under Y-rich conditions predicted that hypo-stoichiometry is accommodated by Y+YH 2 at ambient conditions and by H vacancies in the YH 2-x single phase that is relevant to high temperatures. Neutron diffraction studies were used to confirm both the occupation of H on tetrahedral sites and the near-stoichiometric composition of the hydride phase in the two-phase Y+YH 2 region of the phase diagram that dominates at room temperature. Energy minimized special-quasirandom-structures of H vacancies were used to calculate lattice parameters, elastic constants, and several other properties as a function of composition for the single phase YH 2-x . The lattice parameter of YH 2-x decreased by only 0.004 Å with increasing H/Y for the range 1.31 ≤ H / Y ≤ 2.0 indicating a negligible effect on lattice parameters due to vacancy formation. In the two-phase region, however, calculations predicted the density of z Y + ( 1 - z ) Y H 2 - x to increase with decreasing H/Y at lower temperatures due to the increased fraction of high-density Y metal. Additionally, for the high temperature single phase, decreasing H/Y reduced the density as a consequence of the lattice expansion associated with vacancy formation. All elastic constants and moduli increased with increasing hydrogen content in single-phase YH 2-x .

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evaluation of thermostat location for multizone commercial building performance

In multi-zone buildings, it is often found that a single shared thermostat controls more than one conditioned zones. Although these shared zones are supposed to have similar thermal needs (e.g., cooling and heating load), in reality, they are not mainly due to different orientations, sizes of windows, occupancy, space types, etc. This can cause unnecessary energy waste or thermal discomfort for the occupants. How to quantify this impact in multizone buildings remains a research gap. Therefore, this study aims to evaluate the impact of different sensor (i.e., thermostat) locations for multizone commercial buildings through a comprehensive modeling study. Here, two different scenarios for the sensor locations were selected to evaluate the impact in terms of energy and thermal comfort. The scenario (1) is that one to five sensors distributed among the five zones, but the sensor readings from selected zones will be used for no-sensor zones, which is no-mean sensor scenario. The scenario (2) is that one to five sensors distributed among the five zones, but the average temperature from the shared zones will be used for each of the shared zones, which is a mean sensor scenario. The uncertainty analysis was performed for different sensor location scenarios.(a)The major findings from an energy perspective, for scenario (1), the differences of cooling energy go as high as 17% more or 12% less, compared with the baseline. For heating energy consumption, the discrepancies go as high as 51% more or 52% less, compared with baseline. For site energy consumption, the discrepancies go as high as 3.2% more or 3.2% less, compared with baseline. For fan energy consumption, the discrepancies go as high as 3.2% more or as low as 1.0% less, compared with baseline. For scenario (2), the discrepancies of cooling energy go as high as 3% more, or 0.5% less, compared with the baseline. For heating energy consumption, the discrepancies, are go as high as 10.1% more or as low as 3.0% less, compared with baseline. For site energy consumption, the discrepancies go as high as 1.3% more or 0.3% less, compared with baseline. For fan energy consumption, the discrepancies go as high as 3.1% more or as low as 1.0% less, compared with baseline.(b) In terms of the indoor thermal comfort, for the no-mean-sensor scenarios, the discrepancies of unmet hours for cooling mode can be as high as 1,200 h, compared with the baseline. The discrepancies of unmet hours for heating mode can be as high as 740 h, compared with the baseline. For the mean-sensor scenarios, the discrepancies of unmet hours for cooling mode can be as high as 750 h, compared with the baseline. The discrepancies of unmet hours for heating mode can be as high as 50 h, compared with the baseline.

42 ENGINEERING↗
DOE OSTI2021

A General Strategy for Batch Development of High-Performance and Cost-Effective Sodium Layered Cathodes

High-performance and low-cost transition metal (TM) layered oxides using earth abundant elements are promising cathodes for Na-ion batteries. However, it is challenging to obtain desired materials because the large Na size, different Na occupations and various layer stacking sequences multiply the complication in determining the structure of a given composition and exacerbate uncertainty to the structure-property correlation. In this work, we use the attainment of desired NaxMnyNiZTM1-y-zO2-based cathode materials as an example to demonstrate a general roadmap for batch development of sodium layered cathodes towards practical applications. A synthesis phase diagram of NaxMnyNi1-yO2 was created for pre-screening and rational selection of the platform material of P2/O3-structured Na0.85Mn0.6Ni0.4O2. Cationic potential was leveraged in elemental substitution to further promote the material structural stability and electrochemical performance. Several cost-effective O3 and P2/O3 hybrid cathode materials have been obtained, all of which demonstrate excellent performance. In particular, the Na0.85Mn0.5Ni0.4Ti0.1O2 delivers a high specific capacity of ~130 mAh/g between 2-4 V and 91% retention after 500 cycles. The work discovers multiple materials as high-performance and cost-effective Na-ion battery cathodes and offers critical guidance to the rational design of future layered cathode materials.

Xiao, Biwei↗
DOE OSTI2021

An overview of data tools for representing and managing building information and performance data

Building information modeling (BIM) has been widely adopted for representing and exchanging building data across disciplines during building design and construction. However, BIM's use in the building operation phase is limited. With the increasing deployment of low-cost sensors and meters, as well as affordable digital storage and computing technologies, growing volumes of data have been collected from buildings, their energy services systems, and occupants. Such data are crucial to help decision makers understand what, how, and when energy is consumed in buildings—a critical step to improving building performance for energy efficiency, demand flexibility, and resilience. However, practical analyses and use of the collected data are very limited due to various reasons, including poor data quality, ad-hoc representation of data, and lack of data science skills. To unlock value from building data, there is a strong need for a toolchain to curate and represent building information and performance data in common standardized terminologies and schemas, to enable interoperability between tools and applications. This study selected and reviewed 24 data tools based on common use cases of data across the building life cycle, from design to construction, commissioning, operation, and retrofits. The selected data tools are grouped into three categories: (1) data dictionary or terminology, (2) data ontology and schemas, and (3) data platforms. The data are grouped into ten typologies covering most types of data collected in buildings. This study resulted in five main findings: (1) most data representation tools can represent their intended data typologies well, such as Green Button for smart meter data and Brick schema for metadata of sensors in buildings and HVAC systems, but none of the tools cover all ten types of data; (2) there is a need for data schemas to represent the basis of design data and metadata of occupant data; (3) standard terminologies such as those defined in BEDES are only adopted in a few data tools; (4) integrating data across various stages in the building life cycle remains a challenge; and (5) most data tools were developed and maintained by different parties for different purposes, their flexibility and interoperability can be improved to support broader use cases. Finally, recommendations for future research on building data tools are provided for the data and buildings community based on the FAIR principles to make data Findable, Accessible, Interoperable, and Reusable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Adsorption of Ar into zeolite Al-MFI (NH 4 )

The crystal structure of anhydrous Al-MFI (NH 4 ) containing adsorbed Ar has been determined and refined using synchrotron X-ray powder diffraction data taken at 90 K, and optimized using density functional theory techniques. Six highly occupied Ar sites almost completely fill the pore volume of the zeolite. Changing the gas flow from Ar to He at 90 K decreases the Ar occupancies of all six sites, but two decrease more than the others. Warming the sample from 90 to 295 K in Ar flow results in further decreases in site occupancies, but five of the original six sites persist.

Materials Science↗
DOE OSTI2021

Lithium thiostannate spinels: air-stable cubic semiconductors.

Lithium chalcogenide materials have been studied less than other alkali metal analogs and are of interest as ion conductors and semiconductors capable of thermal neutron detection. Herein, we describe the structural, thermal, magnetic, electronic, and ionic properties of a new family of cubic lithium thiospinels Li2MSn3S8 (M = Mg, Fe, Mn, Ni, Co) and Li1.66CuSn3.33S8. All compounds crystallize in the Fd (3) over barm space group and exhibit site occupancy disorder with Sn and M on the octahedral site for M = Mg, Fe, Mn, Ni, Co. The Li1.66CuSn3.33S8 compound also exhibits occupancy disorder on the tetrahedral sites between Li and Cu, as well as on the octahedral sites between Li and Sn. We demonstrate the ability to tune the physical properties of the compounds by changing their composition. By tuning the identity of the transition metal in the structure, the optical band gaps can vary between 0.91(2) and 2.19(2) eV, and electrical resistivities between 2.8 x 10(3) Omega-cm and 2.2 x 10(7)Omega-cm can be achieved. Density functional theory calculations for Li2MgSn3S8 and Li1.66CuSn3.33S8 suggest that both materials have indirect band gaps and significantly dispersive conduction bands. A bandwidth dispersion of 0.75 and 0.70 eV along the Gamma -> M direction in the conduction band are predicted for Li2MgSn3S8 and Li1.66CuSn3.33S8, respectively, with an electron effective mass of 0.49 and 0.55 m(e) at the Gamma point. The hole effective mass in the valence band is calculated to be 1.25 me at the M point and 0.75 me at the L point for Li2MgSn3S8 and Li1.66CuSn3.33S8, respectively. The ionic/electronic conductivity of each compound was determined using AC electrochemical impedance spectroscopy.

Quintero, Michael A.↗
DOE OSTI2023

Electrochemical Control of Magnetism on the Breathing Kagome Network of Li x ScMo 3 O 8

Controlling properties within a given functional inorganic material structure type is often accomplished through tuning the electronic occupation, which is in turn dictated by the elemental composition determined at the time of material preparation. We employ electrochemical control of the lithium content, with associated electronic occupancy control, to vary the magnetic properties of a material where a kagome-derived network of Mo 3 triangles carry the spin. In this case, Li is electrochemically inserted into LiScMo 3 O 8 , a layered compound containing a breathing Mo kagome network. Up to two additional Li can be inserted into LiScMo 3 O 8 , transforming it into Li 3 ScMo 3 O 8 . Li 2 ScMo 3 O 8 prepared by electrochemical lithiation is compared to the quantum spin liquid candidate compound Li 2 ScMo 3 O 8 prepared through high-temperature solid-state methods, which has a slightly different structural stacking sequence but a similar kagome-derived network. Magnetic measurements are supported by first-principles calculations, showing that electrons remain localized on the Mo clusters throughout the doping series. As x is varied in Li x ScMo 3 O 8 , the measurements and calculations reveal the evolution from a diamagnetic band insulator at x = 1 to a geometrically frustrated magnet at x = 2, back to a diamagnetic insulator at x = 3. These results indicate a likelihood of strong coupling between the degree of Li disorder and charge/magnetic ordering over the Mo 3 clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Inferring the Energetics of CO 2 –Aniline Adduct Formation from Vibrational Spectroscopy

Control of atmospheric CO 2 is an important contemporary scientific and engineering challenge. Towards this goal, the reaction of CO 2 with amines to form carbamate bonds is an established method for CO 2 capture. However, controllable reversal of this reaction remains difficult and requires tuning the energetics of the carbamate bond. Through IR spectroscopy, we show that a characteristic frequency observed upon carbamate formation varies as a function of the substituent’s Hammett parameter for a family of para- substituted anilines. We present computational evidence that the vibrational frequency of the adducted CO 2 serves as a predictor of the energy of formation of the carbamate. Electron donating groups typically enhance the driving force of carbamate formation by transferring more charge to the adducted CO 2 and thus increasing the occupancy of the anti-bonding orbital in the carbon-oxygen bonds. Increased occupancy of the anti-bonding orbital within adducted CO 2 indicates a weaker bond, leading to a red shift in the characteristic carbamate frequency. As a result, our work serves the large field of CO 2 capture research where spectroscopic observables, such as IR frequencies, are more easily obtainable and can stand in as a descriptor of driving forces.

Amines↗