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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Origins of enhanced oxygen reduction activity of transition metal nitrides

Transition metal nitride (TMN-) based materials have recently emerged as promising non-precious-metal-containing electrocatalysts for the oxygen reduction reaction (ORR) in alkaline media. However, the lack of fundamental understanding of the oxide surface has limited insights into structure–(re)activity relationships and rational catalyst design. Here, in this work, we demonstrate how a well-defined TMN can dictate/control the as-formed oxide surface and the resulting ORR electrocatalytic activity. Structural characterization of MnN nanocuboids revealed that an electrocatalytically active Mn 3 O 4 shell grew epitaxially on the MnN core, with an expansive strain along the [010] direction to the surface Mn 3 O 4 . The strained Mn 3 O 4 shell on the MnN core exhibited an intrinsic activity that was over 300% higher than that of pure Mn 3 O 4 . A combined electrochemical and computational investigation indicated/suggested that the enhancement probably originates from a more hydroxylated oxide surface resulting from the expansive strain. This work establishes a clear and definitive atomistic picture of the nitride/oxide interface and provides a comprehensive mechanistic understanding of the structure–reactivity relationship in TMNs, critical for other catalytic interfaces for different electrochemical processes.

electrocatalysis↗
DOE OSTI2025

Origin of proton irradiation-induced deep acceptors in Al 0.70 Ga 0.30 N

Deep level defect introduction and carrier removal were characterized using steady-state photocapacitance (SSPC), deep level transient spectroscopy (DLTS) and lighted capacitance–voltage for proton irradiated n-type Al 0.70 Ga 0.30 N Schottky diodes grown by metal-organic vapor phase epitaxy on AlN-on-sapphire templates. SSPC observed deep levels in the as-grown diode with zero-phonon transition energies of 2.20, 2.65, 3.10, 3.40, and 4.65 eV relative to the conduction band minimum (E c ), and an additional deep level emerged at 1.20 eV with irradiation. Lighted capacitance–voltage measurements quantified the deep level concentration (N t ) of states detected by SSPC, and it was observed that N t increased with proton fluence only for the 1.2 and 4.65 eV levels. Carrier removal was much larger than the increase in N t of the 1.2 and 4.65 eV deep levels, suggesting that radiation-induced deep level compensators existed beyond what was detected with SSPC. DLTS detected additional, proton-induced deep acceptors at E c —0.55, 0.82, and 1.16 eV, the latter of which is likely the same 1.20 eV deep state observed by SSPC. The concentration of the E c —0.82 eV defect state was large enough to reconcile carrier removal with total deep level introduction. Comparing the E c —0.82 and 1.16 eV deep acceptor levels to previous experimental and theoretical reports suggests that their atomistic origins could be the nitrogen vacancy (V N ) and oxygen substituting on the nitrogen sub-lattice (O N ), respectively. This defect behavior contrasts starkly with GaN, where V N and O N are shallow donors, and demonstrates that the electronic properties of defects can evolve drastically within the AlGaN alloy system ranging from wide bandgap GaN to ultra-wide bandgap AlN.

Armstrong, Andrew Michael [Sandia National Laborat↗
DOE OSTI2021

Understanding copper diffusion in CuInSe 2 with first-principles based atomistic and continuum models

We investigate the diffusion of copper in CuInSe 2 using thermodynamic and kinetic models based on density functional theory calculations, attempting to reconcile large differences in reported experimental diffusivities. We find that observations of rapid chemical diffusion can be explained by large thermodynamic factors, which we calculate using a compositionally constrained model of intrinsic point defect formation. We further characterize how copper diffusion coefficients depend on material synthesis conditions and exhibit their variation across the CuInSe 2 secondary phase diagram. In doing so, we identify stable off-stoichiometries that are dominated by either vacancy- or interstitial-mediated diffusion mechanisms. These results are employed in the development of a continuum reaction–diffusion model, which we use to simulate experimental depth profiles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Multilevel Computational Studies Reveal the Importance of Axial Ligand for Oxygen Reduction Reaction on Fe–N–C Materials

The systematic improvement of Fe–N–C materials for fuel cell applications has proven challenging, due in part to an incomplete atomistic understanding of the oxygen reduction reaction (ORR) under electrochemical conditions. Herein, a multilevel computational approach, which combines ab initio molecular dynamics simulations and constant potential density functional theory calculations, is used to assess proton-coupled electron transfer (PCET) processes and adsorption thermodynamics of key ORR intermediates. These calculations indicate that the potential-limiting step for ORR on Fe–N–C materials is the formation of the Fe III –OOH intermediate. They also show that an active site model with a water molecule axially ligated to the iron center throughout the catalytic cycle produces results that are consistent with the experimental measurements. In particular, reliable prediction of the ORR onset potential and the Fe(III/II) redox potential associated with the conversion of Fe III –OH to Fe II and desorbed H 2 O requires an axial H 2 O co-adsorbed to the iron center. The observation of a five-coordinate rather than four-coordinate active site has significant implications for the thermodynamics and mechanism of ORR. Importantly, these findings highlight the importance of solvent–substrate interactions and surface charge effects for understanding the PCET reaction mechanisms and transition-metal redox couples under realistic electrochemical conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Directing reaction pathways via in situ control of active site geometries in PdAu single-atom alloy catalysts

Abstract The atomic scale structure of the active sites in heterogeneous catalysts is central to their reactivity and selectivity. Therefore, understanding active site stability and evolution under different reaction conditions is key to the design of efficient and robust catalysts. Herein we describe theoretical calculations which predict that carbon monoxide can be used to stabilize different active site geometries in bimetallic alloys and then demonstrate experimentally that the same PdAu bimetallic catalyst can be transitioned between a single-atom alloy and a Pd cluster phase. Each state of the catalyst exhibits distinct selectivity for the dehydrogenation of ethanol reaction with the single-atom alloy phase exhibiting high selectivity to acetaldehyde and hydrogen versus a range of products from Pd clusters. First-principles based Monte Carlo calculations explain the origin of this active site ensemble size tuning effect, and this work serves as a demonstration of what should be a general phenomenon that enables in situ control over catalyst selectivity.

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

Facet-dependent structure and dissociation of water at pristine IrO 2 /water interfaces

Understanding the microscopic structure of water at metal oxide interfaces is crucial for advancing electrocatalysis. IrO 2 , specifically, has shown exceptional activity for electrochemical water oxidation, but we currently lack a fundamental understanding of how the surface structure of IrO 2 impacts water reactivity. In this work, we developed a machine learning potential trained to first-principles accuracy for modeling IrO 2 /water interfaces across different facets: (110), (100), (101), and (001). Using extensive machine learning molecular dynamics simulations, we investigated the spontaneous dissociation of water molecules at these interfaces. Our results reveal a distinct dissociation probability trend: (110) > (100) ≈ (101) > (001), which we attribute primarily to the reaction thermodynamics of surface water dissociation. A strong correlation is observed between the surface Ir–O bond distances and the dissociation probabilities, highlighting the role of surface geometry in modulating reactivity. As a consequence, the interfacial solvation structures and hydrogen bonding environments are dynamically tuned by the varying water dissociation capabilities across facets. This work elucidates how water dissociation energetics depend on surface orientation and interfacial structure, offering atomistic insights into manipulating reaction chemistry at electrocatalytic interfaces.

organic↗
DOE OSTI2024

Molecular origin of viscoelasticity and influence of methylation in mesophase pitch

The viscoelastic and thermomechanical properties of pitches are responsible for their melt-spinning behavior, which is a critical step for manufacturing high-performance pitch-based carbon fibers. Here, we systematically explore the impact of methyl group modifications on the viscoelastic and thermal properties of mesophase pitches. We employ a range of atomistic modeling approaches, including Density Functional Theory (DFT), Density Functional Tight Binding (DFTB), and Classical Molecular Mechanics (MM), to provide detailed insights into the molecular interactions and structural changes. Further, our results revealed the molecular mechanisms that promote layered structures leading to the anisotropic nature of the viscoelastic behavior of mesophase pitch. Furthermore, we propose a modified molecular representation of naphthalene-based mesophase pitch based on the analysis of x-ray diffraction measurements. This study provides fundamental insights into the molecular structures of mesophase pitch and the role of methyl groups controlling its viscosity, which offer valuable insights into mesophase-based carbon fiber production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Metastable piezoelectric group-IV monochalcogenide monolayers with a buckled honeycomb structure

Multiple two-dimensional materials are being naïvely termed stable on the grounds of displaying phonon dispersions with no negative frequencies and of not collapsing on molecular dynamics calculations at fixed volume. But, if these phases do not possess the smallest possible structural energy, how does one understand and establish their actual meta stability? To answer this question, twelve two-dimensional group-IV monochalcogenide monolayers (SiS, SiSe, SiTe, GeS, GeSe, GeTe, SnS, SnSe, SnTe, PbS, PbSe, and PbTe) with a buckled honeycomb atomistic structure—belonging to symmetry group P3m1—displaying an out-of-plane intrinsic electric polarization are shown to be metastable by three independent methods. First, we uncover a coordination-preserving structural transformation from the low-buckled honeycomb structure onto the lower-energy Pnm2 1 (or Pmmn for PbS, PbSe, and PbTe) phase to estimate energy barriers E B that must be overcome during such structural transformation. Using the curvature of the local minima and E B as inputs to Kramers escape formula, large escape times are found, implying the structural metastability of the buckled honeycomb phase (with the exception of PbS and PbSe, these phases display escape times ranging from 700 years to multiple times the age of the universe and can be considered “stable” for practical purposes in that relative sense). The second demonstration is provided by phonon dispersion relations that include the effect of long-range Coulomb forces and display no negative vibrational modes. The third and final demonstration of structural metastability is furnished by room-temperature ab initio molecular dynamics for selected compounds. Here, the magnitude of the electronic band gap evolves with chemical composition. Different from other binary two-dimensional compounds such as transition metal dichalcogenide monolayers and hexagonal boron nitride monolayers which only develop an in-plane piezoelectric response, the twelve group-IV monochalcogenide monolayers with a buckled honeycomb structure also display out-of-plane piezoelectric properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Revealing Local Structures through Machine-Learning-Fused Multimodal Spectroscopy

Atomistic structures of materials offer valuable insights into their functionality. Determining these structures remains a fundamental challenge in materials science, especially for systems with defects. While both experimental and computational methods exist, each has limitations in resolving nanoscale structures. Core-level spectroscopies, such as X-ray absorption (XAS) or electron energy-loss spectroscopies (EELS), have been used to determine the local bonding environment and structure of materials. Recently, machine learning (ML) methods have been applied to extract structural and bonding information from XAS/EELS data. However, frameworks relying solely on a single data stream, defined as characterization data derived from a single element using one technique, are often insufficient because multiple local environments can yield similar spectral features, making it challenging to differentiate between competing structural hypotheses. Here, in this work, we address this challenge by integrating multimodal ab initio simulations, experimental data acquisition, and ML techniques for structure characterization. Our goal is to determine local structures and properties using EELS and XAS data from multiple elements and edges. To showcase our approach, we use various lithium nickel manganese cobalt (NMC) oxide compounds which are used for lithium ion batteries, including those with oxygen vacancies and antisite defects, as the sample material system. We successfully inferred local element content, ranging from lithium to transition metals, with quantitative agreement with experimental data. Beyond local element inference, we find that ML model based on multimodal spectroscopic data is able to determine whether local defects such as oxygen vacancy and antisites are present, a task which is impossible for single mode spectra or other experimental techniques. Furthermore, our framework is able to provide physical interpretability, bridging spectroscopy with the local atomic and electronic structures.

battery↗
DOE OSTI2023

An open database of computed bulk ternary transition metal dichalcogenides

Abstract We present a dataset of structural relaxations of bulk ternary transition metal dichalcogenides (TMDs) computed via plane-wave density functional theory (DFT). We examined combinations of up to two chalcogenides with seven transition metals from groups 4–6 in octahedral (1T) or trigonal prismatic (2H) coordination. The full dataset consists of 672 unique stoichiometries, with a total of 50,337 individual configurations generated during structural relaxation. Our motivations for building this dataset are (1) to develop a training set for the generation of machine and deep learning models and (2) to obtain structural minima over a range of stoichiometries to support future electronic analyses. We provide the dataset as individual VASP xml files as well as all configurations encountered during relaxations collated into an ASE database with the corresponding total energy and atomic forces. In this report, we discuss the dataset in more detail and highlight interesting structural and electronic features of the relaxed structures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Unveiling the Origin of Morphological Instability in Topologically Complex Electrocatalytic Nanostructures

Coarsening and degradation phenomena in metals have largely focused on thermally driven processes, such as bulk and surface diffusion. However, dramatic coarsening has been reported in high-surface-area, nanometer-sized Pt-based catalysts during potential cycling in an electrolyte at room temperature─a temperature too low for the process to be explained purely by surface mobility values measured in both vacuum and electrolytes (∼10 –22 and ∼10 –18 cm 2 /s, respectively). This morphological evolution must be due to a different mechanism for mass transport that is sensitive to electrochemical conditions (e.g., electrolyte composition, potential limits, and scan rate). However, there have been no notable studies of electrochemically induced coarsening in nanometer-sized electrocatalysts. Here, we unveil the origins of coarsening in an electrolyte through coupled in situ experiments and atomistic kinetic Monte Carlo (kMC) simulations. Our work demonstrates electrochemical coarsening is driven by two concurrent mechanisms that can be explained at the atomistic level: (i) dissolution/redeposition during the reduction of an oxidized species and (ii) rapid surface diffusion of undercoordinated atoms.

gold↗
DOE OSTI2024

Neural network interatomic potential-driven analysis of phase stability in Ti–V alloys at the atomistic scale

The evolution of the ω phase in titanium–vanadium (Ti–V) alloys is critical for their mechanical properties, particularly in aerospace and biomedical applications. Here, this study employs a Rapid Artificial Neural Network (RANN) potential to model the ω phase evolution at the atomistic level, demonstrating a high degree of consistency with experimental observations, unlike the Modified Embedded Atom Method (MEAM), which fails to capture this phase transformation accurately. RANN simulations replicate key phenomena such as the nucleation of α precipitates at ω/β interfaces and accurate lattice orientations, enhancing our understanding of phase stability and transformation kinetics. The findings affirm that RANN potentials can significantly improve the prediction accuracy of complex material behaviors, offering a powerful tool for designing advanced materials with tailored properties such as solute effect in various stacking fault energies. This approach not only bridges the gap between theoretical predictions and empirical data but also sets a new direction for future research in materials science, emphasizing the integration of machine learning techniques in the development and optimization of new alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tailoring composition and deformation modes at the microstructural level for next generation low-cost high-strength austenitic stainless steels

The objective of this project is to enable deliberate development of cost-effective, hydrogen resistant alloys by establishing detailed relationships specific to the effects of alloy composition, short-range order (SRO), and microsegregation in the presence of hydrogen on the transition between homogeneous deformation and localized plasticity in shear bands. In collaboration with the International Institute for Carbon-Neutral Energy Research, I2CNER, at Kyushu University in Japan, we conceptualized, designed, and manufactured four austenitic alloys that maintain corrosion resistance and ensure lower cost relative to baseline commercial alloys. The mechanical properties and deformation modes of the novel alloys (KU alloys) were assessed in the presence of hydrogen (H). Correlations between composition and performance revealed that two of the KU alloys are suitable replacements for 316 steel, while another is a viable replacement for 304 steel at room temperature. We found that, in the presence of other austenite stabilizing elements namely Mn and N, replacing Ni with Cu does not lead to martensite formation as has been previously reported.1–3 Furthermore, we found that the addition of Cu leads to an earlier onset of multiple slip resulting in an relative earlier onset of a higher work hardening rate (WHR). Greater understanding of the relationships between alloy composition and SRO required the development of a novel advanced electron diffraction methodology to characterize SRO in complex FCC alloys. This innovative approach, which combines fluctuation and correlation analyses of diffuse-scattering signals, successfully differentiated between SRO and long-range ordering (LRO). Further investigations into annealed austenitic stainless steels could provide insights into manipulating SRO and its effects on material properties. Atomistic simulations provided understanding of SRO behavior that was difficult to capture experimentally. This project created the first spin cluster expansion model that is able to capture and describe SRO effects in Fe-Ni-Cr FCC alloys, accounting for the non-negligible effects of magnetism. An automated computational workflow was established to provide reliable predictions of SRO in Fe-Ni-Cr austenitic alloys, both with and without the presence of H atoms. Analysis of the propensity for SRO in Fe-Ni-Cr alloys revealed that H tends to cluster with specific, well-defined SRO domains. The computational framework is general purpose and can be extended to realistic stainless steels across diverse composition ranges. With confidence that SRO is possible in austenitic stainless steels, we developed a discrete dislocation finite element code to understand the interaction of dislocations with SRO in the presence of H. By incorporating H effects on the dislocation emission and SRO stress field we show that the critical stress for the dislocation pileup to breakthrough the SRO domain decreases in the presence of H, which directly contributes localized deformation at the macroscale. Through the simulation of a uniaxial tension test, we demonstrated that H-induced weakening of SRO stress field and H-enhanced dislocation emission can lead to the onset of shear localization at lower macroscopic strains. As a whole, this project identified three novel alloys that show improvements in performance and cost efficiency for H-facing applications by studying correlations between alloy chemistry and deformation behavior. We also made significant advancements to experimental and computational methodologies necessary to study the chemistry and distribution of SRO across a range of alloys, which in turn allowed us to demonstrate how deformation mechanisms change due to the contributions of SRO in austenitic alloys in the presence of H. The combined advancements in fundamental understanding with novel alloy development in this project has increased the viability of next generation H-technologies for the broader public through accessible low-cost alloys and accelerated development towards future H-infrastructure.

08 HYDROGEN↗
DOE OSTI2022

Scale-invariant machine-learning model accelerates the discovery of quaternary chalcogenides with ultralow lattice thermal conductivity

We design an advanced machine-learning (ML) model based on crystal graph convolutional neural network that is insensitive to volumes (i.e., scale) of the input crystal structures to discover novel quaternary chalcogenides, AMM'Q 3 (A/M/M' = alkali, alkaline earth, post-transition metals, lanthanides, and Q = chalcogens). These compounds are shown to possess ultralow lattice thermal conductivity (κ l ), a desired requirement for thermal-barrier coatings and thermoelectrics. Upon screening the thermodynamic stability of ~1 million compounds using the ML model iteratively and performing density-functional theory (DFT) calculations for a small fraction of compounds, we discover 99 compounds that are validated to be stable in DFT. Taking several DFT-stable compounds, we calculate their κ l using Peierls–Boltzmann transport equation, which reveals ultralow κ l (<2 Wm -1 K -1 at room temperature) due to their soft elasticity and strong phonon anharmonicity. Our work demonstrates the high efficiency of scale-invariant ML model in predicting novel compounds and presents experimental-research opportunities with these new compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Local Electronic Structure of Supercritical CO 2 from X-ray Raman Spectroscopy and Atomistic-Scale Modeling

Supercritical CO 2 is encountered in several technical and natural systems related to biology, geophysics, and engineering. While the structure of gaseous CO 2 has been studied extensively, the properties of supercritical CO 2 , particularly close to the critical point, are not well-known. Here, in this work, we combine X-ray Raman spectroscopy, molecular dynamics simulations, and first-principles density functional theory (DFT) calculations to characterize the local electronic structure of supercritical CO 2 at conditions around the critical point. The X-ray Raman oxygen K-edge spectra manifest systematic trends associated with the phase change of CO 2 and the intermolecular distance. Extensive first-principles DFT calculations rationalize these observations on the basis of the 4sσ Rydberg state hybridization. X-ray Raman spectroscopy is found to be a sensitive tool for characterizing electronic properties of CO 2 under challenging experimental conditions and is demonstrated to be a unique probe for studying the electronic structure of supercritical fluids.

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

Combining Theory and Experiment to Map the Atomic-Level Structure–Energy Pathways of Adsorbate-Mediated Phase Changes in a Cooperatively Flexible Metal–Organic Framework

An important subclass of metal–organic frameworks (MOFs) exhibits cooperative flexibility, wherein individual crystallites undergo global structural phase changes in response to external stimuli. Where cooperative flexibility results in reversible changes between crystalline states of distinct accessible porosity, these frameworks can exhibit rare yet desirable behaviors that cannot be explained by local dynamics alone. Yet, the chemical and structural origins of cooperative flexibility and how frameworks undergo these reversible phase changes at the atomic level remain poorly understood. Deliberate design for specific applications is therefore exceedingly difficult, and there is great impetus to develop a fundamental understanding of this phenomenon. Here, an effective and widely accessible computational approach is developed, which is designed to provide microscopic resolution via direct comparison to experimental data along the desorption-guided pathway. The strategy is applied to explain the desorption-induced phase change in an experimentally well-characterized framework, CdIF-13 (sod-Cd(benzimidazolate)2), where experiment alone was unable to resolve the atomistically detailed phase change landscape. Our findings reveal that the cooperative phase change pathways are adsorbate dependent with thermodynamics of intermediate structural states dictated by a nuanced interplay of ligand orientation, skeletal symmetry, and modes of surface adsorption. The results reveal that this isotropically flexible framework is “chaperoned” through a complex energy landscape by specific adsorbates, revealed by the reported computational approach with atomic-level insight and validated by experimentally determined structures. Thus, this work facilitates both understanding and future design of flexible materials for applications in gas storage, transport, delivery, and separation technologies.

03 NATURAL GAS↗
DOE OSTI2023

Wafer-Scale Synthesis of 2D Materials by an Amorphous Phase-Mediated Crystallization Approach

The interest in the wafer-scale growth of two-dimensional (2D) materials, including transition metal dichalcogenides (TMDCs), has been rising for transitioning from lab-scale devices to commercial-scale systems. Among various synthesis techniques, physical vapor deposition, such as pulsed laser deposition (PLD), has shown promise for the wafer-scale growth of 2D materials. However, due to the high volatility of chalcogen atoms (e.g., S and Se), films deposited by PLD usually suffer from a lack of stoichiometry and chalcogen deficiency. To mitigate this issue, excess chalcogen is necessary during the deposition, which results in problems like uniformity or not being repeatable. This study demonstrates a condensed-phase or amorphous phase-mediated crystallization (APMC) approach for the wafer-scale synthesis of 2D materials. This method uses a room-temperature PLD process for the deposition and formation of amorphous precursors with controlled thicknesses, followed by a post-deposition crystallization process to convert the amorphous materials to crystalline structures. This approach maintains the stoichiometry of the deposited materials throughout the deposition and crystallization process and enables the large-scale synthesis of crystalline 2D materials (e.g., MoS 2 and WSe 2 ) on Si/SiO 2 substrates, which is critical for future wafer-scale electronics. We show that the thickness of the layers can be digitally controlled by the number of laser pulses during the PLD phase. Optical spectroscopy is used to monitor the crystallization dynamics of amorphous layers as a function of annealing temperature. The crystalline quality, domain sizes, and the number of layers were explored using nanoscale and atomistic characterization (e.g., AFM, STEM, and EDS) along with electrical characterization to explore process–structure–performance relationships. Finally, this growth technique is a promising method that could potentially be adopted in conventional semiconductor industries for wafer-scale manufacturing of next-generation electronic and optoelectronic devices.

2D electronics↗
DOE OSTI2022

Temperature Effects in Flexible Adsorption Processes for Amorphous Microporous Polymers

A collection of atomistic molecular simulations is reported that illustrate the impact of adsorption temperature on species uptake and adsorbate-induced structural rearrangement for amorphous polymers of intrinsic microporosity. Temperature-sensitive structural rearrangement is evaluated by contrasting two methods: standard grand canonical Monte Carlo simulations using a rigid framework approximation and a combined Monte Carlo/molecular dynamics approach that fully incorporates framework flexibility. We report single-component gas phase adsorption isotherms for CH 4 , C 2 H 4 , C 2 H 6 , C 3 H 6 , C 3 H 8 , and CO 2 across a temperature range of 250–400 K for models of an archetypal polymer of intrinsic microporosity, PIM-1. A quadratic model is presented that captures two main mechanisms of temperature-dependent adsorption-induced deformation of PIM-1 up to a relative swelling of 1.15: thermal expansion and an increased propensity to swell as a function of species uptake. Two case studies are reported that highlight the critical role of operating temperature in industrial storage and separation applications. The first study focuses on methane storage and delivery applications using a pressure–temperature swing adsorption application (PTSA). We demonstrate that larger working capacities are accompanied by increased volumetric strain between adsorption–desorption steps. The second case study considers PIM-1 as an adsorbent to separate an exemplar ternary syngas mixture at operating temperatures ranging 300–550 K. Here, a temperature threshold of ~400 K is identified, beyond which adsorption-induced PIM-1 swelling is negligible and the solubility selectivity-loading curve transitions to exhibiting a nearly linear relationship.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗