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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 55 records · Page 3

Plasma assisted NH 3 /H 2 /air ignition in nanosecond discharges with non-equilibrium energy transfer

Ammonia (NH 3 ), with its high energy density and easiness to store and transport as a hydrogen carrier, has become a promising alternative green fuel. However, its adoption in power generation is hindered by challenges such as low burning velocity, slow low-temperature oxidation, high NO x emissions, and ignition difficulty. Here, this work computationally investigates the effects of non-equilibrium energy transfer by nanosecond discharges on NH 3 ignition and flame propagation in an NH 3 /H 2 /air flow at 700 K and 1 atm. The simulation results demonstrate that NH 3 /air mixtures require a large ignition energy due to their large critical ignition radius. It is shown that adding 30 % hydrogen significantly reduces the critical ignition radius and minimum ignition energy. Two-dimensional modeling further shows a non-monotonic dependence of ignition kernel volume on the applied voltage and reduced electric field. The optimum ignition enhancement occurs at 200 Td where the generation of electronically excited species and radicals including N 2 (B), O( 1 D) and OH becomes most efficient. Higher voltages divert electron energy toward ionization, which makes it less effective for NH 3 ignition. The study also identifies an optimal electrode gap size for a given pulse energy. Smaller gap sizes increase deposited energy density, raising temperature and radical concentrations. However, excessive reduction of the gap distance reduces flame propagation speed due to the flame stretch effect in rich mixtures with the effective Lewis number greater than unity. A nonlinear relationship between pulse repetition frequency and ignition kernel volume is observed in a nanosecond pulsed high frequency discharge (NPHFD). An optimal frequency range of 200 kHz to 2 MHz is found when two pulses are used. In addition, an optimal number of pulses exists for each pulse repetition frequency, with higher frequencies requiring more pulses to maximize the overlap region. These findings provide critical insights on developing controlled plasma discharge techniques for efficient NH 3 ignition in reactive flows within internal combustion engines and gas turbines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dark Matter Reconstruction in LBAI Experiments with Imperfect Data

Long-baseline atom interferometer (LBAI) experiments offer unprecedented sensitivity to ultralight scalar dark matter (DM) [1], however reconstruction of a putative DM signal with traditional frequency-domain analysis requires ``perfect data (i.e., regularly-sampled with no missing samples). In a real LBAI experiment, there will undoubtedly be imperfections in the data leading to downtime. This downtime can arise from operational considerations (e.g., maintenance), the operational environment (motion of people and animals [2] or elevators), and robustness of the experimental apparatus (e.g., bad atom launches). In this work, we investigate the impact of various downtime models on the overall DM sensitivity of such an experiment. We compare the sensitivity for each downtime model as determined by a ``compound FFT analysis to a baseline no-downtime case. We also show how much sensitivity can be regained by moving to a Lomb-Scargle frequency analysis, as in [2]. Furthermore, we demonstrate reconstruction of the DM wave s phase as well as its frequency. [1] D. Antypas, et al, ``New Horizons: Scalar and Vector Ultralight Dark Matter (2022). arXiv:2203.14915 [2] J. Carlton and C. McCabe, ``From RATs to riches: mitigating anthropogenic and synanthropic noise in atom interferometer searches for ultra-light dark matter (2023). arXiv:2308.101731

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Hidden orders and phase transitions for the fully packed quantum loop model on the triangular lattice

Abstract Quantum loop and dimer models are prototypical correlated systems with local constraints, which are not only intimately connected to lattice gauge theories and topological orders but are also widely applicable to the broad research areas of quantum materials and quantum simulation. Employing our sweeping cluster quantum Monte Carlo algorithm, we reveal the complete phase diagram of the triangular-lattice fully packed quantum loop model. Apart from the known lattice nematic (LN) solid and the even$${{\mathbb{Z}}}_{2}$$ Z 2 quantum spin liquid (QSL) phases, we discover a hidden vison plaquette (VP) phase, which had been overlooked and misinterpreted as a QSL for more than a decade. Moreover, the VP-to-QSL continuous transition belongs to the (2 + 1)D cubic * universality class, which offers a lattice realization of the (fractionalized) cubic fixed point that had long been considered as irrelevant towards the O(3) symmetry until corrected recently by conformal bootstrap calculations. Our results are therefore of relevance to recent developments in both experiments and theory, and facilitate further investigations of hidden phases and transitions.

Physics↗

Coupled machine learning–ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N 2 O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N 2 O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high-emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N 2 O fluxes from US cropland. Trained and validated on ~12,000 N 2 O chamber measurements at 17 US Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N 2 O at both training (R 2 = 0.84, RMSE = 16.4 g N ha −1 d −1 ) and held-out testing sites (R 2 = 0.84, RMSE = 6.2 g N ha −1 d −1 ). Analyses identified six dominant N 2 O drivers: soil organic carbon (SOC), NH 4 + , NO 3 - , water-filled pore space, temperature, and aboveground biomass production. Wet, warm soils produced large N 2 O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N 2 O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

AI↗

1D modeling of plasma streamers at ammonia-air flame conditions

Abstract Self-consistent 1D modeling of streamers in ammonia-oxygen-nitrogen-water mixtures has been performed in this work. A fluid model that includes species transport, electrostatic potential, and detailed chemistry was developed and verified. This model is then used to simulate the avalanche, streamer formation and propagation phases, driven by a nanosecond voltage pulse, at different thermochemical conditions derived from a 1D laminar premixed ammonia-air flame. The applicability of the Meek’s criterion in predicting the streamer inception location was successfully confirmed. Streamer formation and propagation duration were found to vary significantly with different thermochemical conditions, due to the difference in ionization rates. The thermochemical state also affected the breakdown characteristics which was tested by maintaining the background reduced electric field constant. Detailed kinetic analyses revealed the importance of O ( 1 D ) in the production of key radicals, such as O, OH, and NH 2 . Furthermore, the contributions of the dissociative electronic excitation of NH 3 towards the production of H and NH 2 radicals have also been reported. Spatial and temporal evolution of the electron energy loss fractions for various inelastic collision processes at different thermochemical states uncovered the input plasma energy spent of fuel dissociation and the large variability in the dominant processes during the avalanche and streamer propagation phases. The methodology and analyses reported in this work are key towards developing effective strategies for controlled nanosecond-pulsed non-equilibrium plasma sources used for ammonia ignition and flame stabilization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

ECLEIRS: Exact conservation law embedded identification of reduced states for parameterized nonlinear conservation laws from sparse and noisy data

Multi-query applications such as parameter estimation, uncertainty quantification and design optimization for parameterized partial differential equation (PDE) systems are expensive. While reduced/latent state dynamics approaches for parameterized PDEs offer a viable alternative, these approaches rely on high-quality data and struggle with highly sparse spatiotemporal noisy measurements typically obtained from experiments. Furthermore, there is no guarantee that these models satisfy governing physical conservation laws. In this article, we propose a reduced state dynamics approach, referred to as ECLEIRS, that embeds exact conservation in the solution and flux representation by utilizing a space-time divergence-free neural network formulation. We compare ECLEIRS with other reduced state dynamics approaches, those that do not enforce any physical constraints and those with physics-informed loss functions, for three shock-propagation problems: 1-D advection, 1-D Burgers and 2-D Euler equations. In conclusion, the numerical experiments conducted in this study demonstrate that ECLEIRS provides the most accurate prediction of dynamics for unseen parameters even in the presence of highly sparse and noisy data.

97 MATHEMATICS AND COMPUTING↗

Numerical Investigation of Fluid Flow and Space Charge in Liquid Argon Time Projection Chamber (LArTPC) Detectors

Overview This project focused on developing a high-fidelity numerical framework to simulate the multiphysics environment within Liquid Argon Time Projection Chamber (LArTPC) detectors. The primary objective was to characterize the complex interplay between ion transport, background fluid dynamics, and electric field distortions—a critical factor for the calibration and sensitivity of next-generation High Energy Physics experiments, such as DUNE. Technical Achievements The research successfully yielded a hybrid numerical space-charge solver utilizing a Cell-Centered Finite Volume Method (FVM) for ion transport coupled with a Finite Element Method (FEM) for electric potential. Key accomplishments include: • Verification & Validation: The 3-D solver was rigorously verified against 1-D analytical solutions, demonstrating high numerical accuracy in predicting space-charge-induced field deviations. • Field Distortion Analysis: 3D simulations revealed that space charge effects introduce significant non-uniformities in the electric field. Critically, the research identified that background LAr flow velocities, when comparable to ion drift velocities, markedly exacerbate these distortions. • Technology Transfer: The resulting source code and comprehensive user manuals were successfully transferred to collaborators at Fermilab, providing a portable computational tool for the broader scientific community. Challenges and Future Directions While the space-charge solver achieved all performance metrics, the integrated fluid dynamics modeling encountered convergence challenges stemming from the extreme 200-fold disparity in length scales between the detector's 37 mm inlet pipes and the 8-meter global domain. To address this, the project has identified a clear technical pivot toward Hierarchical Geometric Adaptive Mesh Refinement (HG-AMR). By implementing an h-type refinement strategy with hanging nodes, future iterations of this solver will be capable of resolving localized high-gradient inlet flows without the prohibitive computational costs of regular grids. This advancement, combined with data-driven uncertainty quantification based on MicroBooNE-style calibration, will enable the precise modeling of detector responses in large-scale cryogenic environments where direct measurement remains difficult. Impact The computational tools developed under this award provide a foundation for enhancing the energy resolution and spatial reconstruction of noble liquid detectors. By bridging the gap between theoretical fluid dynamics and experimental field calibration, this work supports the DOE’s mission to advance the frontiers of neutrino physics and dark matter detection.

42 ENGINEERING↗

Unveiling Baryon Charge Carriers through Charge Stopping in Isobar Collisions

Utilizing a comprehensive (3 + 1)⁢D relativistic hydrodynamic framework with multiple conserved charge currents and charge-dependent lattice-QCD-based equation of state, we study the baryon and electric charge number deposition at midrapidity in isobar Ru + Ru and Zr + Zr collisions at the center of mass energy $\sqrt{s}_{NN}$ = 200 GeV. Comparing our predictions with upcoming experimental data from the Relativistic Heavy Ion Collider will shed light on the existence of baryon junctions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Computationally designed coiled coil ‘bundlemers’ as model colloidal nanoparticles for solution assembly and materials design (Final Report)

As a collaborative team at the University of Delaware and the University of Pennsylvania, Kloxin, Pochan and Saven designed new biomimetic nanomaterials de novo, leveraging a variety of complementary areas of expertise: computational design of biopolymers (Saven at the University of Pennsylvania), and synthesis and characterization (Kloxin and Pochan at the University of Delaware). Overall activities included: sequence-specific peptide synthesis; covalent crosslinking; noncovalent assembly; site-specific functionalization; and nanostructural characterization using electron microscopy and solution-phase (x-ray and neutron) scattering. Using natural and non-natural amino acids, the team created modular, functional peptide building blocks for elaboration of new nanostructured materials. Ultimately, the development of robust peptide-based, building blocks provides tools for researchers to readily produce complex nanomaterial structures in a wide range of applications. The project had three, interconnecting goals in an effort to provide the broader scientific community with a new peptide-based paradigm for materials design and characterization. First, we further developed the coiled-coil bundle-based toolbox (otherwise known as the ‘bundlemer’ toolbox) via computational design with experimental bundle assembly verification. Second, we developed new uses of covalent interactions, in addition to desired physical (noncovalent) interactions, to assemble bundlemers into 1-D polymer chains with targeted chain rigidity, length, and dispersity. Thirds, we used the above designs to experimentally realize (physical or covalent) polymers to target the creation of liquid crystals or to realize interparticle assembly into nanoporous lattices. The close integration of the three groups was instrumental in success of the biomolecular materials design, formation, and understanding for future designs.

36 MATERIALS SCIENCE↗

Constraining the phase shift of relativistic species in DESI BAOs

In the early Universe, neutrinos decouple quickly from the primordial plasma and propagate without further interactions. The impact of free-streaming neutrinos is to create a temporal shift in the gravitational potential that impacts the acoustic waves known as baryon acoustic oscillations (BAOs), resulting in a non-linear spatial shift in the Fourier-space BAO signal. In this work, we make use of and extend upon an existing methodology to measure the phase shift amplitude $\beta _{\phi }$ and apply it to the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) BAOs with an anisotropic BAO fitting pipeline. We validate the fitting methodology by testing the pipeline with two publicly available fitting codes applied to highly precise cubic box simulations and realistic simulations representative of the DESI DR1 data. We find further study towards the methods used in fitting the BAO signal will be necessary to ensure accurate constraints on $\beta _{\phi }$ in future DESI data releases. Using DESI DR1, we present individual measurements of the anisotropic BAO distortion parameters and the $\beta _{\phi }$ for the different tracers, and additionally a combined fit to $\beta _{\phi }$ resulting in $\beta _{\phi } = 2.7 \pm 1.7$. After including a prior on the distortion parameters from constraints using Planck we find $\beta _{\phi } = 2.7^{+0.60}_{-0.67}$ suggesting $\beta _{\phi } > 0$ at 4.3$\sigma$ significance. This result may hint at a phase shift that is not purely sourced from the standard model expectation for $N_{\rm {eff}}$ or could be a upwards statistical fluctuation in the measured $\beta _{\phi }$; this result relaxes in models with additional freedom beyond Lambda-cold dark matter.

79 ASTRONOMY AND ASTROPHYSICS↗

Spatially varying seasonal modulation to tidal stream energy potential due to mixed tidal regimes in the Aleutian Islands, AK

We provide an assessment of the tidal stream energy resource of the Aleutian Islands, Alaska via a validated barotropic tidal numerical model of the region. Eight island passes are identified as energy “hotspots”. The annual mean kinetic energy fluxes, KEF , calculated at each pass vary from 1000 to 11,000 MW, while the annual available energy, AAE , varies from 5 to 42 MWh m −2 . Notable seasonal modulation to monthly power density averages and ranges are noted at some passes and not others. Seasonal adjustment is linked to the semi-annual solar declination cycle which enhances (dampens) diurnal (D 1 ) tidal amplitudes in summer/winter (spring/fall) as well as the time-varying phase lag between D 1 and semidiurnal (D 2 ) fortnightly tidal cycles. Annual variability in monthly mean power density scales with the tidal current form factor, F u , with the largest seasonal change occurring for F u > 1 (D 1 dominated tide). The spread in power density over a month is on average smaller for passes with mixed tides (F u = 1 ) than those with D 1 or D 2 dominance, as changes to fortnightly phase lag become influential to net power density ranges when tides are mixed. This study outlines overlooked, but relevant, long-term modulation to tidal streams in regions with mixed tides.

16 TIDAL AND WAVE POWER↗

The Dark Energy Survey Supernova Program: an updated measurement of the Hubble constant using the inverse distance ladder

We measure the current expansion rate of the Universe, Hubble’s constant $H_0$, by calibrating the absolute magnitudes of supernovae to distances measured by baryon acoustic oscillations (BAO). This ‘inverse distance ladder’ technique provides an alternative to calibrating supernovae using nearby absolute distance measurements, replacing the calibration with a high-redshift anchor. We use the recent release of 1829 supernovae from the Dark Energy Survey spanning $0.01\lt z\lt 1.13$ anchored to the recent baryon acoustic oscillation measurements from Dark Energy Spectroscopic Instrument (DESI) spanning $0.30 \lt z_{\mathrm{eff}}\lt 2.33$. To trace cosmology to $z=0$, we use the third-, fourth-, and fifth-order cosmographic models, which, by design, are agnostic about the energy content and expansion history of the universe. With the inclusion of the higher redshift DESI-BAO data, the third-order model is a poor fit to both data sets, with the fourth-order model being preferred by the Akaike Information Criterion. Using the fourth-order cosmographic model, we find $H_0=67.19^{+0.66}_{-0.64}\mathrm{~km} \mathrm{~s}^{-1} \mathrm{~Mpc}^{-1}$, in agreement with the value found by Planck without the need to assume Flat-$\Lambda$CDM. However, the best-fitting expansion history differs from that of Planck, providing continued motivation to investigate these tensions.

79 ASTRONOMY AND ASTROPHYSICS↗

Dark Energy Survey Year 6 results: cell-based coadds and METADETECTION weak lensing shape catalogue

We present the metadetection weak lensing galaxy shape catalogue from the 6-yr Dark Energy Survey (DES Y6) imaging data. This data set is the final release from DES, spanning 4422 deg 2 of the southern sky. We describe how the catalogue was constructed, including the two new major processing steps, cell-based image coaddition, and shear measurements with metadetection. The DES Y6 M etadetection weak lensing shape catalogue consists of 151 922 791 galaxies detected over riz bands, with an effective number density of n eff = 8.22 galaxies per arcmin 2 and shape noise of σ e = 0.29. We carry out a suite of validation tests on the catalogue, including testing for point spread function (PSF) leakage, testing for the impact of PSF modelling errors, and testing the correlation of the shear measurements with galaxy, PSF, and survey properties. In addition to demonstrating that our catalogue is robust for weak lensing science, we use the DES Y6 image simulation suite to estimate the overall multiplicative shear bias of our shear measurement pipeline. We find no detectable multiplicative bias at the roughly half-per cent level, with m = (3.4 ± 6.1) x 10 –3 , at 3σ uncertainty. This is the first time both cell-based coaddition and Metadetection algorithms are applied to observational data, paving the way to the Stage-IV weak lensing surveys.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Spectroscopic Characterization of redMaPPer Galaxy Clusters with DESI

Optical galaxy cluster identification algorithms such as redMaPPer promise to enable an array of astrophysical and cosmological studies, but suffer from biases whereby galaxies in front of and behind a galaxy cluster are mistakenly associated with the primary cluster halo. These projection effects caused by irreducible photometric redshift uncertainty must be quantified to facilitate the use of optical cluster catalogues. We present measurements of galaxy cluster projection effects and velocity dispersion using spectroscopy from the Dark Energy Spectroscopic Instrument. Our findings are as follows: we confirm that the fraction of redMaPPer putative member galaxies mistakenly associated with cluster haloes is richness dependent, being more than twice as large at low richness than high richness; we present the first spectroscopic evidence of an increase in projection effects with increasing redshift, by as much as 25 per cent from $z\sim 0.1$ to $z\sim 0.2$; moreover, we find qualitative evidence for luminosity dependence in projection effects, with fainter galaxies being more commonly far behind clusters than their bright counterparts; finally, we fit the scaling relation between measured mean spectroscopic richness and velocity dispersion, finding an implied linear scaling between spectroscopic richness and halo mass. We discuss further directions for the application of spectroscopic data sets to improve use of optically selected clusters to test cosmological models.

clusters↗

It is not σ 8 : constraining the non-linear matter power spectrum with the Dark Energy Survey Year-5 supernova sample

The weak gravitational lensing magnification of Type Ia supernovae (SNe Ia) is sensitive to the matter power spectrum on scales $k\gt 1 h$ Mpc$^{-1}$, making it unwise to interpret SNe Ia lensing in terms of power on linear scales. We compute the probability density function of SNe Ia magnification as a function of standard cosmological parameters, plus an empirical parameter $A_{\rm mod}$ which describes the suppression or enhancement of matter power on non-linear scales compared to a cold dark matter only model. While baryons are expected to enhance power on the scales relevant to SN Ia lensing, other physics such as neutrino masses or non-standard dark matter may suppress power. Using the Dark Energy Survey Year-5 sample, we find $A_{\rm mod} = 0.77^{+0.69}_{-0.40}$ (68 per cent credible interval around the median). Although the median is consistent with unity there are hints of power suppression, with $A_{\rm mod} \lt 1.09$ at 68 per cent credibility.

79 ASTRONOMY AND ASTROPHYSICS↗

Comparing the DES-SN5YR and Pantheon+ SN cosmology analyses: investigation based on ‘evolving dark energy or supernovae systematics’?

Recent cosmological analyses measuring distances of type Ia supernovae (SNe Ia) and baryon acoustic oscillations (BAO) have all given similar hints at time-evolving dark energy. To examine whether underestimated SN Ia systematics might be driving these results, Efstathiou (2025) compared overlapping SN events between Pantheon+ and DES-SN5YR (20 per cent SNe are in common), and reported evidence for an $\sim$0.04 mag offset between the low- and high-redshift distance measurements of this subsample of events. If this offset is arbitrarily subtracted from the entire DES-SN5YR sample, the preference for evolving dark energy is reduced. In this paper, we show that this offset is mostly due to different corrections for Malmquist bias between the two samples; therefore, an object-to-object comparison can be misleading. Malmquist bias corrections differ between the two analyses for several reasons. First, DES-SN5YR used an improved model of SN Ia luminosity scatter compared to Pantheon+ but the associated scatter-model uncertainties are included in the error budget. Secondly, improvements in host mass estimates in DES-SN5YR also affected SN standardized magnitudes and their bias corrections. Thirdly, and most importantly, the selection functions of the two compilations are significantly different, hence the inferred Malmquist bias corrections. Even if the original scatter model and host properties from Pantheon+ are used instead, the evidence for evolving dark energy from CMB, DESI BAO Year 1 and DES-SN5YR is only reduced from 3.9$\sigma$ to 3.3$\sigma$, consistent with the error budget. Finally, in this investigation, we identify an underestimated systematic uncertainty related to host galaxy property uncertainties, which could increase the final DES-SN5YR error budget by 3 per cent. In conclusion, we confirm the validity of the published DES-SN5YR results.

79 ASTRONOMY AND ASTROPHYSICS↗

The Dark Energy Survey supernova program: a reanalysis of cosmology results and evidence for evolving dark energy with an updated Type Ia supernova calibration

We present improved cosmological constraints from a re-analysis of the Dark Energy Survey (DES) 5-year sample of Type Ia supernovae (DES-SN5YR). This re-analysis includes an improved photometric cross-calibration, recent white dwarf observations to cross-calibrate between DES and low-redshift surveys, retraining the salt3 light-curve model and fixing a numerical approximation in the host-galaxy colour law. Our fully recalibrated sample, which we call DES-Dovekie, comprises ~1600 likely Type Ia SNe from DES and ~200 low-redshift SNe from other surveys. With DES-Dovekie, we obtain Ω m = 0.330 ± 0.015 in flat Lambda-cold dark matter (⁠ΛCDM) which changes Ω m by –0.022 compared to DES-SN5YR. Combining DES-Dovekie with cosmic microwave background data from Planck, Atacama Cosmology Telescope, and South Pole Telescope and the DESI DR2 measurements in a flat CDM cosmology, we find ω 0 = –0.803 ± 0.054 and ω a = –0.72 ± 0.21⁠. Our results hold a significance of 3.2σ, reduced from 4.2σ for DES-SN5YR, to reject the null hypothesis that the data are compatible with the cosmological constant. This significance is equivalent to a Bayesian model preference odds of approximately 5:1 in favour of the flat ω 0 ω a CDM model. Using generally accepted thresholds for model preference, our updated data exhibits only a weak preference for evolving dark energy.

dark energy↗

Insights on carbon dioxide adsorption in a flexible 1-D coordination polymer from in situ X-ray scattering and density functional theory

A combination of in situ small-angle X-ray scattering (SAXS) microstructure characterization over scales ranging from 1 nm to 10 µm and powder X-ray diffraction (XRD) structure characterization under various gas/pressure/temperature conditions with density functional theory (DFT) calculations provides new insights for the CO2 sorption behavior of a one-dimensional porous coordination polymer: catena-bis­(di­benzoyl­methanato)(4,4′-bi­pyridyl)­nickel(II), denoted NiDBM-Bpy. The NiDBM-Bpy chains are held together by van der Waals forces, but the structure of guest-free NiDBM-Bpy is unsolved due to a lack of suitable crystals and high-quality powder XRD patterns. Nevertheless, SAXS and powder XRD can follow microstructural and structural changes as a function of gas pressure, composition and temperature. Both mixed-gas flow and static supercritical CO2 regimes are explored experimentally. DFT calculations are used to model the structural variation associated with XRD changes and hysteresis in the sorption isotherms. XRD and DFT calculations suggest that an orthorhombic Fddd structure with two CO2 per Ni emerges following a transition from the structure with lower molar volume and symmetry that exists without CO2 present.

Allen, Andrew J.↗