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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Model of Grain Boundary Complexion Transitions and Grain Growth in Yttria-Doped Alumina

In this work, we present a physically-parameterized microstructure evolution model for the Yttria-doped alumina system. Yttria-doped alumina is a well-known ceramic system which undergoes first-order phase-like transitions at grain boundaries, which can radically alter interface properties. The change in interfacial properties in turn can radically change microstructure outcomes during processing, including the induction of abnormal grain growth modes. In this work, we develop a simulation that evolves alumina microstructure as a function of yttria concentration and temperature. In the window studied, we achieve strong agreement with reviewed experimental results in identifying the windows for large grains, small grains, abnormal grain growth, and complexion transition kinetics. We then apply the model to study and demonstrate how the possible inclusion of second-phase particles or uneven solute distribution profiles will impact microstructure evolution. It is found that particles do not significantly affect abnormal grain growth in the window studied (but do lead to reduced grain size through pinning effects). It is found that even modest amounts of solute inhomogeneity will result in substantial changes in microstructure outcomes, frequently leading to clusters of abnormal grains. This model largely corroborates the expectations and hypotheses made from recent experimental studies in oxide-doped alumina systems. Further, it is found that there exists a peak transition fraction for the system at which abnormal grain size tends to be maximized.

Grain Growth, Grain Boundary Complexion, abnormal ↗
DOE OSTI2011

Delayed translocation of NGFI-B/RXR in glutamate stimulated neurons allows late protection by 9-cis retinoic acid

Highlights: {yields} NGFI-B and RXR translocate out of the nucleus after glutamate treatment. {yields} Arresting NGFI-B/RXR in the nucleus protects neurons from excitotoxicity. {yields} Late protection by 9-cis RA is possible due to a delayed translocation of NGFI-B/RXR. -- Abstract: Nuclear receptor and apoptosis inducer NGFI-B translocates out of the nucleus as a heterodimer with RXR in response to different apoptosis stimuli, and therefore represents a potential pharmacological target. We found that the cytosolic levels of NGFI-B and RXR{alpha} were increased in cultures of cerebellar granule neurons 2 h after treatment with glutamate (excitatory neurotransmitter in the brain, involved in stroke). To find a time-window for potential intervention the neurons were transfected with gfp-tagged expressor plasmids for NGFI-B and RXR. The default localization of NGFI-Bgfp and RXRgfp was nuclear, however, translocation out of the nucleus was observed 2-3 h after glutamate treatment. We therefore hypothesized that the time-window between treatment and translocation would allow late protection against neuronal death. The RXR ligand 9-cis retinoic acid was used to arrest NGFI-B and RXR in the nucleus. Addition of 9-cis retinoic acid 1 h after treatment with glutamate reduced the cytosolic translocation of NGFI-B and RXR{alpha}, the cytosolic translocation of NGFI-Bgfp observed in live neurons, as well as the neuronal death. However, the reduced translocation and the reduced cell death were not observed when 9-cis retinoic acid was added after 3 h. Thus, late protection from glutamate induced death by addition of 9-cis retinoic acid is possible in a time-window after apoptosis induction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

National energy savings potential of cellular shades: A measurement and simulation study

Windows are major contributors to energy demand in residential homes because of their inferior thermal resistance compared with the opaque envelope, and sometimes from unwanted solar heat gain. Window attachments can help mitigate the energy demand by controlling the solar heat gains and enhancing window thermal resistance. Cellular shades have the potential of superior thermal performance compared with generic shades because of its honeycomb structure. Here, in this study, the team analyzed the energy savings potential of cellular shades in residential homes via experimental testing for two heating seasons and energy simulations. Five shading devices—three single-cell and two double cellular/cell-in-cell shades—were used to compare the performance with generic horizontal venetian blinds using two nearly identical side-by-side rooms in a residential home. The experimental testing showed daily heating energy savings in the range of 17%–36% compared with the case without shades. The experimental testing data also exhibited improvements in thermal comfort when using cellular shades. Additionally, energy simulations were performed to evaluate the energy savings potential of the cellular shades using a residential prototype home, which demonstrated energy savings up to 9 kWh/m2/year in cold climates. The total site energy savings for heating and cooling from cellular shades was up to ~9% for the home with a heat pump and up to ~15% for a home with a gas furnace compared with cases without any shading devices. The energy savings at a national scale were up to 14.6 TWh assuming a 20% penetration rate in residential homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Divide and conquer: Learning chaotic dynamical systems with multistep penalty neural ordinary differential equations

Forecasting high-dimensional dynamical systems is a fundamental challenge in various fields, such as geosciences and engineering. Neural Ordinary Differential Equations (NODEs), which combine the power of neural networks and numerical solvers, have emerged as a promising algorithm for forecasting complex nonlinear dynamical systems. However, classical techniques used for NODE training are ineffective for learning chaotic dynamical systems. In this work, we propose a novel NODE-training approach that allows for robust learning of chaotic dynamical systems. Here, our method addresses the challenges of non-convexity and exploding gradients associated with underlying chaotic dynamics. Training data trajectories from such systems are split into multiple, non-overlapping time windows. In addition to the deviation from the training data, the optimization loss term further penalizes the discontinuities of the predicted trajectory between the time windows. The window size is selected based on the fastest Lyapunov time scale of the system. Multi-step penalty(MP) method is first demonstrated on Lorenz equation, to illustrate how it improves the loss landscape and thereby accelerates the optimization convergence. MP method can optimize chaotic systems in a manner similar to least-squares shadowing with significantly lower computational costs. Our proposed algorithm, denoted the Multistep Penalty NODE, is applied to chaotic systems such as the Kuramoto-Sivashinsky equation, the two-dimensional Kolmogorov flow, and ERA5 reanalysis data for the atmosphere. It is observed that MP-NODE provide viable performance for such chaotic systems, not only for short-term trajectory predictions but also for invariant statistics that are hallmarks of the chaotic nature of these dynamics.

Chaotic dynamical systems↗
DOE OSTI2014

RED-BL: Evaluating dynamic workload relocation for data center networks

In this study, we present RED-BL (Relocate Energy Demand to Better Locations), a framework to minimize the electricity cost for operating data center networks over consecutive intervals of fixed duration. Within each interval, RED-BL provides a mapping of workload to a set of geographically distributed data centers. To this end, RED-BL uses the geographical and temporal variations in electricity prices as exhibited by electrical energy markets. In addition, we incorporate the transition costs associated with a change in workload mapping from one interval to the next, over a planning window comprising multiple such intervals. This results in a sequence of workload mappings that is optimal over the entire planning window, even though the workload mapping in a given interval may not be locally optimal. Our evaluation of RED-BL uses electricity prices from the US markets and workload traces from live Internet applications with millions of users. We find that RED-BL can reduce the electric bill by as much as 45% compared to the case when the workload is uniformly distributed. When compared to existing workload relocation solutions, for a wide range of data center deployment sizes, RED-BL achieves electricity cost savings that are 8.28% higher, on average. This seemingly modest reduction can save millions of dollars for the operators. The cost of this saving is an inexpensive computation at the start of each planning window.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Local reduced-order modeling for electrostatic plasmas by physics-informed solution manifold decomposition

Despite advancements in high-performance computing and modern numerical algorithms, computational cost remains prohibitive for multi-query kinetic plasma simulations. Here, in this work, we develop data-driven reduced-order models (ROMs) for collisionless electrostatic plasma dynamics, based on the kinetic Vlasov-Poisson equation. Our ROM approach projects the equation onto a linear subspace defined by the proper orthogonal decomposition (POD) modes. We introduce an efficient tensorial method to update the nonlinear term using a precomputed third-order tensor. We capture multiscale behavior with a minimal number of POD modes by decomposing the solution manifold into multiple time windows and creating temporally local ROMs. We consider two strategies for decomposition: one based on the physical time and the other based on the electric field energy. Applied to the 1D1V Vlasov–Poisson simulations, that is, prescribed E-field, Landau damping, and two-stream instability, we demonstrate that our ROMs accurately capture the total energy of the system both for parametric and time extrapolation cases. The temporally local ROMs are more efficient and accurate than the single ROM. In addition, in the two-stream instability case, we show that the energy-windowing reduced-order model (EW-ROM) is more efficient and accurate than the time-windowing reduced-order model (TW-ROM). With the tensorial approach, EW-ROM solves the equation approximately 90 times faster than Eulerian simulations while maintaining a maximum relative error of 7.5% for the training data and 11% for the testing data.

Electrostatic plasmas↗
DOE OSTI2015

DNS and LES of turbulent flow in a closed channel featuring a pattern of hemispherical roughness elements

Three mesh adaptivity algorithms were developed to facilitate and expedite the use of the CADIS and FW-CADIS hybrid Monte Carlo/deterministic techniques in accurate full-scale neutronics simulations of fusion energy systems with immense sizes and complicated geometries. First, a macromaterial approach enhances the fidelity of the deterministic models without changing the mesh. Second, a deterministic mesh refinement algorithm generates meshes that capture as much geometric detail as possible without exceeding a specified maximum number of mesh elements. Finally, a weight window coarsening algorithm decouples the weight window mesh and energy bins from the mesh and energy group structure of the deterministic calculations in order to remove the memory constraint of the weight window map from the deterministic mesh resolution. The three algorithms were used to enhance an FW-CADIS calculation of the prompt dose rate throughout the ITER experimental facility and resulted in a 23.3% increase in the number of mesh tally elements in which the dose rates were calculated in a 10-day Monte Carlo calculation. Additionally, because of the significant increase in the efficiency of FW-CADIS simulations, the three algorithms enabled this difficult calculation to be accurately solved on a regular computer cluster, eliminating the need for a world-class super computer.

Nuclear Science & Technology↗
DOE OSTI2013

Accuracy and Consistency of Respiratory Gating in Abdominal Cancer Patients

Purpose: To evaluate respiratory gating accuracy and intrafractional consistency for abdominal cancer patients treated with respiratory gated treatment on a regular linear accelerator system. Methods and Materials: Twelve abdominal patients implanted with fiducials were treated with amplitude-based respiratory-gated radiation therapy. On the basis of daily orthogonal fluoroscopy, the operator readjusted the couch position and gating window such that the fiducial was within a setup margin (fiducial-planning target volume [f-PTV]) when RPM indicated “beam-ON.” Fifty-five pre- and post-treatment fluoroscopic movie pairs with synchronized respiratory gating signal were recorded. Fiducial motion traces were extracted from the fluoroscopic movies using a template matching algorithm and correlated with f-PTV by registering the digitally reconstructed radiographs with the fluoroscopic movies. Treatment was determined to be “accurate” if 50% of the fiducial area stayed within f-PTV while beam-ON. For movie pairs that lost gating accuracy, a MATLAB program was used to assess whether the gating window was optimized, the external-internal correlation (EIC) changed, or the patient moved between movies. A series of safety margins from 0.5 mm to 3 mm was added to f-PTV for reassessing gating accuracy. Results: A decrease in gating accuracy was observed in 44% of movie pairs from daily fluoroscopic movies of 12 abdominal patients. Three main causes for inaccurate gating were identified as change of global EIC over time (∼43%), suboptimal gating setup (∼37%), and imperfect EIC within movie (∼13%). Conclusions: Inconsistent respiratory gating accuracy may occur within 1 treatment session even with a daily adjusted gating window. To improve or maintain gating accuracy during treatment, we suggest using at least a 2.5-mm safety margin to account for gating and setup uncertainties.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Dynamic calibration of differential equations using machine learning, with application to turbulence models

We present a methodology for calibration of parametric ordinary and partial differential equation models, using off-the-shelf software for back-propagation in Neural Networks (NN). As a prototypical example, we consider calibration of a Reynolds-averaged Navier-Stokes (RANS) turbulence closure model, against ground truth data from direct numerical simulations (DNS) of two different turbulent flows. Numerical time integration is represented as a custom NN, where only the RANS model parameters are trainable. A loss function is defined to quantify the mismatch between the NN prediction and the ground truth over a predefined, finite time integration window. This loss function is then minimized using a gradient descent method utilizing the back-propagation algorithm. Furthermore, this dynamic approach to training is to be contrasted with a static approach, wherein a least square regression estimate for parameters is obtained in the limit of an infinitesimal time integration window. In a first test of static and dynamic approaches against ground truth data generated by the model, the former proves to be significantly faster and more accurate than the latter at recovering the parameters. When both calibration approaches are tested against DNS data, for which it is known that the model cannot achieve a perfect fit, the static approach yields a good prediction only for short times, while the dynamic approach results in physical and stable predictions over the entire integration window. After optimization of the dynamic approach for time step, spatial resolution, stability, and physics-based constraints, we obtain a 50% improvement of outcomes over those obtained from the existing, manually calibrated set of parameters, demonstrating the merits of this systematic and automated procedure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Insights into radiation resistance of titanium alloys from displacement cascade simulations

Radiation damage in beam window materials limits the use of high power proton beams in high energy physics research. The alloy Ti-6Al-4V is presently used as a beam window material but a prospective alternative, Ti-15V-3Cr-3Sn-3Al has been proposed. Since both these alloys contain dual phases at room temperature, we compare the radiation damage in the α and ß-phases of these two materials via primary knock-on atom (PKA) cascade simulations in the 10-40keV energy range. At PKA energies 30 and 40keV, the number of Frenkel pairs in the ballistic stage is higher in the ß-phase of Ti-6Al-4V than that in the ß-phase of Ti-15V-3Cr-3Sn-3Al almost by a factor of 2. The α-phase, of both these alloys, by far outperforms the ß-phases of the two alloys, both in terms of damage during the ballistic stage and in terms of the surviving defects. The average displacement threshold energy (E d ) in the α-phase of both alloys was found to be 66eV while that in the ß-phase of Ti-15-3 was 55 eV and in the ß-phase of Ti-6-4 was 46. Further, while the number of surviving defects is almost equal in both alloys, the vacancy and interstitial clustering mechanisms differ notably, which can impact the degree of radiation hardening and loss of ductility. Our simulations show larger vacancy and interstitial clusters form in Ti-6Al-4V as compared to that in Ti-15-3-3-3 alloy. These results indicate that Ti-15-3-3-3 alloys may be a promising candidate for next generation beam window material with a higher radiation tolerance than the existing Ti-6-4 alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Energy savings and life cycle cost analysis of advanced double skin facade system applied to old apartments in South Korea

South Korea is one of the most densely populated countries in the world, and the population density in urban areas is much higher among others. Apartments are the most common form of residential buildings due to their high population density. More than 60% of domestic residential buildings are apartments, with more than 10 million households. The high population density is a problem that has long plagued South Korea because more than 45% of apartments are old apartments that are more than 20 years old. Old apartment buildings have low thermal performance that results in lots of energy consumption. Balconies, which worked as a thermal buffer, are also being removed by residents to expand indoor space. According to the green remodeling project supported by the Korean government, the typical retrofitting method is replacing external windows with the high-efficiency window in old apartments in South Korea. Here, this paper proposes a retrofitting method using an extended double-skin façade (DSF) system that replaces exterior windows and acts as a thermal buffer. The simulation model is developed with the EnergyPlus simulation program to conduct energy performance analyses. The simulation model has been calibrated using actual experimental data collected between October 1, 2019, and January 15, 2020. Results show that the cooling, heating, and lighting energy can be reduced up to 44.1% by fully utilizing electric energy generated by solar PV panels integrated with the DSF system. The payback period is about 15 years based on the energy price provided by the utility company. Although the payback period is long, it has great potential of energy savings and CO 2 emission reductions. The DSF system should be considered as a way of renovation, considering other factors such as increased real estate values and energy cost increases in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Using dynamic mode decomposition to predict the dynamics of a two-time non-equilibrium Green’s function

Computing the numerical solution of the Kadanoff–Baym equations, a set of nonlinear integral differential equations satisfied by the two-time Green's functions derived from many-body perturbation theory for a quantum many-body system away from equilibrium, is a challenging task. Recently, we have successfully applied dynamic mode decomposition (DMD) to construct a data driven reduced order model that can be used to extrapolate the time-diagonal of a two-time Green's function from numerical solutions of the KBE within a small time window. In this paper, we extend the previous work and use DMD to predict off-diagonal elements of the two-time Green's function. We partition the two-time Green's function into a number of one-time functions along the diagonal and subdiagonals of the two-time window as well as in horizontal and vertical directions. We use DMD to construct separate reduced order models to predict the dynamics of these one-time functions in a two-step procedure. We extrapolate along diagonal and several subdiagonals within a subdiagonal band of a two-time window in the first step. In the second step, we use DMD to extrapolate the Green's function outside of the sub-diagonal band. In conclusion, we demonstrate the efficiency and accuracy of this approach by applying it to a two-band Hubbard model problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Capacitance of Ti 3 C 2 T x MXene in Ionic Liquid Electrolyte

Ti 3 C 2 T x MXene, a two-dimensional (2D) early transition metal carbide, has shown an extremely high volumetric capacitance in aqueous electrolytes, but in a narrow voltage window (less than 1.23 V). The utilization of MXene materials in ionic liquid electrolytes with a large voltage window has never been addressed. Here, we report the preparation of the Ti 3 C 2 T x MXene ionogel film by vacuum filtration for use as supercapacitor electrodes operating in 1-Ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (EMI-TFSI) neat ionic liquid electrolyte. Due to the disordered structure of the Ti 3 C 2 T x hydrogel film and a stable spacing after vacuum drying, achieved through ionic liquid electrolyte immersion of the Ti 3 C 2 T x hydrogel film, the Ti 3 C 2 T x surface became accessible to EMI + and TFSI - ions. A capacitance of 70 F g -1 together with a large voltage window of 3 V was obtained at a scan rate of 20 mV s -1 in neat EMI-TFSI electrolyte. The electrochemical signature indicates a capacitive behavior even at a high scan rate (500 mV s -1 ) and a high power performance. This work opens up the possibilities of using MXene materials with various ionic liquid electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2018

Process development of 99.95% pure copper processed via selective electron beam melting and its mechanical and physical properties

Highlights: • Additively manufactured dense copper samples (>99.5%) • Measured electrical conductivity >58 MS/m (>100% IACS) • Equiaxed grain structure • 177 N/mm{sup 2} tensile strength, 87 N/mm{sup 2} yield strength, 59% elongation at fracture - Abstract: Additive manufacturing by selective electron beam melting (SEBM) was used to fabricate pure copper specimens. A process window at process temperature of 530 °C, gives the required beam powers and deflection speeds for manufacturing dense specimens (>99.5%). The microstructure of SEBM specimens was analyzed by using optical and scanning electron microscopy (SEM). Electrical conductivity, thermal conductivity, hardness, and mechanical performance were investigated by using eddy current, laser flash analysis, Vickers hardness and tensile tests, respectively. It was found that the variation of beam power and scan speed results in different microstructures from columnar to nearly equiaxed grain. The electrical conductivity of SEBM-processed specimens was above 58 MS/m (>100 IACS) while their hardness was around 55 HV0.05 and 46 HV5 without any dependency on processing parameters within the process window. The tensile tests revealed how vertical cracks affect the mechanical strength under tensile loading condition. The results of this study not only show a reliable process window but also introduce the links between processing parameters, defect formations, conductivity and mechanical strength of pure copper specimens manufactured by SEBM.

36 MATERIALS SCIENCE↗
DOE OSTI2014

A cost-effective process to prepare VO{sub 2} (M) powder and films with superior thermochromic properties

Graphical abstract: Combining codeposition and short time post annealing, VO{sub 2} (M) with high quality and excellent phase transition performance is obtained. After mixing the VO{sub 2} powder with acrylic resin, the composite films deposited on glass show superior visible transmission and solar modulation, which can be used as an excellent candidate of low cost smart window in energy saving field. - Highlights: • The VO{sub 2} powder obtained by short time thermolysis method is high purity and crystallinity with superior phase transition performance. • The maximum decreasing efficiency of phase transition temperature is about −30 K/at% with w = 0.4 at%. • After mixing VO{sub 2} powder with acrylic resin, the maximal visible transmission of the composite films is 48% and the transmission modulation at 2000 nm is 37.3% with phase transition temperature of 66.2 °C. • Though the phase transition performance is weakened by tungsten doping, the film prepared by 1.3 at% tungsten doped VO{sub 2} still show superior transmission modulation about 26.4%, which means that it is a potential candidate as smart windows. - Abstract: VO{sub 2} powder with superior phase transition performance was prepared by convenient thermolysis method. The results illustrated that VO{sub 2} powder show high purity and crystallinity. VO{sub 2} particles are transformed from cluster to quasi-sphere with the increase of annealing temperature. The DSC analysis proves that VO{sub 2} show superior phase transition performance around 68 °C. The phase transition temperature can be reduced to 33.5 °C by 1.8 at% tungsten doping. The maximum decreasing efficiency of phase transition temperature is about −30 K/at% with w = 0.4 at%. After mixing VO{sub 2} powder with acrylic resin, the maximal visible transmission of the composite thin films on glass is 48% and the transmission modulation at 2000 nm is 37.3% with phase transition temperature of 66.2 °C. Though the phase transition performance is weakened by tungsten doping, the film prepared by 1.3 at% tungsten doped VO{sub 2} still show superior transmission modulation about 26.4% at 2000 nm, which means that it is a potential candidate as smart windows.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Molecular dynamics simulation of framework flexibility effects on noble gas diffusion in HKUST-1 and ZIF-8

Molecular dynamics simulations were used to investigate trends in noble gas (Ar, Kr, Xe) diffusion in the metal-organic frameworks HKUST-1 and ZIF-8. Diffusion occurs primarily through inter-cage jump events, with much greater diffusion of guest atoms in HKUST-1 compared to ZIF-8 due to the larger cage and window sizes in the former. We compare diffusion coefficients calculated for both rigid and flexible frameworks. For rigid framework simulations, in which the framework atoms were held at their crystallographic or geometry optimized coordinates, sometimes dramatic differences in guest diffusion were seen depending on the initial framework structure or the choice of framework force field parameters. When framework flexibility effects were included, argon and krypton diffusion increased significantly compared to rigid-framework simulations using general force field parameters. Additionally, for argon and krypton in ZIF-8, guest diffusion increased with loading, demonstrating that guest-guest interactions between cages enhance inter-cage diffusion. No inter-cage jump events were seen for xenon atoms in ZIF-8 regardless of force field or initial structure, and the loading dependence of xenon diffusion in HKUST-1 is different for rigid and flexible frameworks. Diffusion of krypton and xenon in HKUST-1 depends on two competing effects: the steric effect that decreases diffusion as loading increases, and the “small cage effect” that increases diffusion as loading increases. Finally, a detailed analysis of the window size in ZIF-8 reveals that the window increases beyond its normal size to permit passage of a (nominally) larger krypton atom.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Design of enhanced porous organic cage solubility in Type 2 porous liquids

Decreasing cost of technologies for direct air capture of carbon can be achieved through the design of new materials with high CO 2 selectivity that can be incorporated into existing industrial processes. An emerging class of materials for these applications are porous liquids (PLs). PLs are mixtures of porous hosts and solvents with intrinsic porosity due to steric exclusion of solvent from inside the porous host. It is currently unknown how solvent -porous host interactions affect porous host solubility in the bulk solvent. Here, in this study, density functional theory simulations were used to investigate interactions between nine solvents and a CC13 porous organic cage (POC). Calculations identified that solvent molecules were the most stable when placed either inside the CC13 POC or in the pore window compared to interfacial binding sites. Structural changes to the CC13 POC correlated with reported experimental solubilities, including expansion of the CC13 POC with solvent molecule infiltration and expansion or contraction of the pore window. Based on these results, new PL design guidelines should include compositions with (1) high concentrations of POCs with flexible cage structures that can expand when solvated and (2) solvent molecule-POC combinations that contract the pore window during solvent molecule-host binding.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Critical role of solvation on CC13 porous organic cages for design of porous liquids

Efficient carbon capture requires the design of new materials with high CO 2 selectivity and gas adsorption capacity that can be incorporated into existing industrial processes. Porous liquids (PLs) are promising candidate materials that consist of a nanoporous host and a solvent forming a liquid with permanent porosity based on exclusion of the solvent from the interior of the nanoporous host. Stable PLs are based on solvent-nanoporous host interactions, which can be evaluated through molecular simulations. Here, time- and temperature-dependent density functional theory simulations were performed between four solvents, 2-bromophenol, 4-methylphenol, 2,4-dimethylphenol, and cyclohexanone and the CC13 porous organic cage (POC) as a prototypical PL composition. Overall, minimal reactions occurred in the PL including no changes in the POC structure. Additionally, POC-solvent coordination occurred through interactions of neighboring functional groups such as methyl/bromide and hydroxyl on the solvent molecules with the POC surface. Therefore, the location rather than the number of functional groups on the solvent molecule controls the POC-solvent interactions. Additionally, the POC pore window contracted or expanded up to 8% during solvation, which correlates with the experimental solubility and static solvent-POC binding, where solvents that caused less contraction of the POC pore window increased POC solubility. Finally, these results allow for the design of optimized POC-based PL compositions based on solvent-nanoporous host binding and variation in the pore window during solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗