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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

OR-AGENT framework – Architecting electrified heavy-duty drayage applications

The widespread adoption of zero-emission vehicles in heavy-duty (HD) commercial freight transportation faces considerable technoeconomic challenges. For heavy-duty trucks, ensuring high uptime, cost parity with diesel, and safety standards is especially critical as these vehicles operate over long distances with heavy loads, where any downtime or off-nominal behaviors significantly impacts logistics, productivity, and the total cost of ownership. Unlike traditional diesel refueling, BEV charging infrastructure must be co-optimized with vehicle deployment, operational demands, and grid capacity to ensure cost-effective and reliable freight operations. However, the lack of a standardized ownership and service model has led to a fragmented approach—where commercial vehicle operators may invest in, own, and maintain both vehicle/batteries and charging/energy infrastructure. This disconnect may exclude energy service providers from the equation, forcing fleet operators to explore ‘behind-the-fence’ energy solutions that increase capital investment, operational downtime, overhead costs, and, in some cases, net carbon emissions. To address these issues, this study introduces OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport), a comprehensive modeling framework that integrates powertrain architectures, charging infrastructures, and energy backbone systems into a cohesive strategy. In this paper, OR-AGENT is applied to develop an interconnected systems architecture for energy efficiency and resiliency enhancement of heavy-duty drayage vehicles at the Port of Savannah, GA. This framework showcases an interconnected systems approach to electrifying heavy-duty drayage vehicles at the Port of Savannah, GA. The study assessed BEVs with 400–1200 kWh battery capacities, accounting for seasonal variations in weather and freight routing. A diverse charging mix (150 kW–1250 kW) was evaluated alongside grid capacity constraints, cost, and carbon intensity analysis, leading to the development of a strategic microgrid/Distributed Energy Resources (DER) deployment architecture to ensure a reliable and sustainable transition. However, the findings also highlight the need for alternative zero-emission solutions for remaining trips, such as larger batteries, electrified roadways, hydrogen powertrains, or net-zero emission fuels. In conclusion, the findings are incorporated into a Total Cost of Ownership (TCO) model to identify optimal architectures for an interconnected electrified ecosystem.

Commercial vehicles↗
DOE OSTI2023

Synthesis of PHI-type zeolite harmotome using barium as an inorganic structure-directing agent inspired from natural mineral compositions

Zeolites are nanoporous aluminosilicates widely used as commercial adsorbents, heterogeneous catalysts, and ion-exchange materials due to their unique porosity, acidity, and thermal stability. The vast majority of synthetically-realized zeolite structures are prepared under hydrothermal conditions in alkaline media, and often in the presence of an organic structure-directing agent that facilitates the crystallization of diverse porous networks. Due to economic and environmental disadvantages of organic-based syntheses, it is often desirable to produce zeolites in organic-free media using alkali metal ions as the most commonly employed inorganic structure-directing agents (ISDAs). Here, in this study, we were inspired by the elemental compositions of natural zeolite minerals to examine the use of an alkaline earth metal ion as the ISDA to prepare zeolites with the PHI framework type. Two natural minerals exhibiting this crystal structure are phillipsite and harmotome. Both structures contain sodium and potassium as extra-framework cations, but only harmotome contains barium cations. Here we examined how the combination of alkali and alkaline earth ISDAs promote the formation of PHI-type zeolites. Our findings reveal that each isostructure is prepared under different synthesis conditions where simply adding barium to a growth mixture does not always lead to harmotome formation. Harmotome is formed in more dilute and alkaline growth media; however, time-resolved analyses of zeolite crystallization reveal that harmotome can be synthesized at low temperatures (ca. 65 °C) with rates that are 5-times faster than syntheses of phillipsite. This seemingly indicates that barium reduces the energetic barrier for PHI-type zeolite nucleation in ways that are not fully understood. Moreover, harmotome crystals exhibit an average particle size of ca. 60 nm, which is nearly 40-fold smaller than phillipsite crystals prepared under similar conditions. Collectively, these findings identify routes to control crystallization of PHI-type zeolites and may provide a broader strategy for using the composition of natural zeolite minerals to optimize the preparation of synthetic analogues.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evaluation of a high-throughput method for processing sponge-stick samples to detect viable, non-spore-forming biothreat agents

After a bioterrorism incident, surface sampling is often used to determine the extent of contamination and exposure, guiding decontamination efforts and decisions for re-occupancy of affected sites. The sponge-stick (SS) is a preferred and commonly used device for sample collection to detect both spore-forming and non-spore-forming biothreat agents from non-porous surfaces. Here, in this study, a recently developed high-throughput method (HTM) for processing SS samples to detect viable Bacillus anthracis spores was adapted for detection of non-spore-forming biothreat agents, Yersinia pestis and Francisella tularensis. The scalable HTM was used to process up to 20 SS samples simultaneously, compared to the current stomacher-based method which processes one SS at a time. Comparisons of the HTM and the stomacher-based method were statistically indistinguishable for most experiments (P > 0.05) with HTM recoveries of 37–60 % for Y. pestis inoculated at 102–103 cells/SS and held 48 h at 4 °C to mimic sample transport/storage. The HTM was integrated with Rapid Viability-Polymerase Chain Reaction (RV-PCR) analysis to detect viable Y. pestis in the presence of particulate contamination (Arizona Test Dust, ATD). This approach detected Y. pestis inoculated at 20 cells/SS and ATD did not impact detection (P > 0.05). F. tularensis showed significantly lower recoveries between no-hold time and 48-h hold time (4 °C, P < 0.05) using the HTM, which further testing showed could be due to toxicity of the neutralizing buffer used for SS pre-wetting. With modifications, this method could enhance throughput capacity while maintaining similar recovery efficiencies to current methods for other non-spore-forming bacterial pathogens.

Biological and medical sciences↗
DOE OSTI2025

Functional group activation and coupling agent migration induced by plasma treatment in adhesive for enhanced toughness of metal-composite joints

Commercial adhesive paste was additionally activated using low-power oxygen plasma with different plasma exposure durations to investigate its interfacial bonding contribution in adhesively-bonded Aural-5/CFRP-PA6 double cantilever beam (DCB) joints with plasma-treated adherends. The plasma-treated adhesive showed enhanced functional peak intensities in Fourier transfer infrared spectroscopy (FTIR) as plasma exposure time was increased, and some degree of oxidation was also detected via X-ray photoelectron spectroscopy (XPS). A small molecule, dicyandiamde (coupling agent) in adhesive was migrated to adhesive layer, where double concentration of coupling agent was detected after 10 minutes of plasma treatment. As a result, characterization of the adhesive/CFRP-PA6 interface after DCB fracture showed additional chemical bonds formed through amine-initiated epoxy ring opening polymerization, as well as amide bonds and ester bonds. In conclusion, these additional bonds at the adhesive/CFRP-PA6 interfaces led to significantly increased failure extensions and fracture energies of the joints as the plasma exposure time on the adhesive increased, compared to the joints with plasma-treated adherends but non-plasma-treated adhesive as commonly seen in the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mechanisms of Degradation of Toxic Nerve Agents: Quantum-chemical Insight into Interactions of Sarin and Soman with Molybdenum Dioxide

With the urgent need to provide an efficient and reliable protection for people from fatal chemical and biological weapons, our fundamental understanding of how toxins interact with filters is far from complete. The situation is further complicated by natural difficulties of performing experimental measurements with lethal toxins. Unlike experiments, computational modeling offers an attractive and safe yet reliable way of studying behavior of toxic agents on a variety of substrates at a great level of detail. Here, we report DFT-based quantum-chemical calculations of adsorption and decomposition of DMMP, sarin and soman on MoO 2 (011) surface. Our calculations show that MoO 2 strongly adsorbs toxic nerve agents and quickly decomposes them. Decomposition of DMMP on the MoO 2 (011) surface proceeds via the PO-CH 3 bond breaking and a formation of a surface methoxy group. The calculated activation barrier for this reaction is 131.5 kJ mol -1 . Unlike DMMP, decomposition of sarin and soman proceeds via the dealkylation reaction yielding propene and 3,3-dimethyl-1-butene, respectively. Decomposition of sarin requires a remarkably low energy (53.7 kJ mol- 1 ), whereas the similar reaction in soman requires 50 kJ mol -1 more energy. We also make specific predictions to guide Ambient-Pressure X-ray Photoelectron Spectroscopy (APXPS) experiments on sarin interaction with MoO 2 samples. We conclude that MoO 2 serves as an efficient substrate able of degrading toxins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Titrating Controlled Defects into Si-LTA Zeolite Crystals Using Multiple Organic Structure-Directing Agents

Controlling defects in zeolites is crucial for tuning their adsorption and catalytic properties. In this work, we have performed an integrated zeolite synthesis, spectroscopy, and density functional theory study to test the limit of F– as a charge-balancing agent that mitigates defects in siliceous zeolites. We focused on the synthesis of siliceous zeolite LTA at 150 °C with 1,2-dimethyl-3-(4-methylbenzyl) imidazolium as the primary organic structure-directing agent (OSDA) and tetramethyl ammonium (TMA) as the secondary OSDA. By varying the amount of TMA in the synthesis gel, positive charges were titrated into the resulting as-made Si-LTA. Surprisingly, we found that greater TMA concentration does not induce more F– to enter into the zeolite. 29Si solid-state MAS NMR, Raman spectroscopy, and density functional theory suggest that this system has surpassed its capacity for F– to balance OSDA charge, and additional positive charge is balanced by Si–O– framework defects. The number of defects in the as-made Si-LTA can be precisely titrated by the amount of TMA in the zeolite structures. For the Si-LTA synthesized without TMA, framework defects formed in the early stage of crystal growth were found to heal during later crystallization, leading to defect-free Si-LTA. However, for the Si-LTA synthesized with TMA, the defects formed in early stages do not heal. A DFT thermodynamic analysis explains that crowding of Si-LTA pores by TMA impedes defect healing; this prediction is corroborated by synthesis experiments at an elevated temperature (170 °C). These results indicate that F– can have a limited capacity to balance OSDA charge in zeolite synthesis, opening up a third route to zeolite synthesis intermediate between the fluoride and hydroxide routes.

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

Complexing Agent-Assisted Membraneless Zinc–Iodine Aqueous Batteries

A membrane is required for conventional zinc–iodine aqueous batteries, since soluble polyiodides cross over to the anode side and react with zinc metal spontaneously. Making the battery membraneless increases ion transport and reduces its cost and overall footprint. In this paper, a membraneless Zn–I 2 aqueous battery is demonstrated, employing a complexing agent, 1-butyl-1-methylpyrrolidinium iodide (MBPI), to promote the formation of I 5 – -containing, phase-separated polyiodides upon charging, to minimize self-discharge and suppress Zn dendrite growth. With an additional 0.3 M MBPI in 4 M ZnI 2 electrolyte, the membraneless battery achieved 65 cycles with >85% Coulombic efficiency, whereas the MBPI-free control failed immediately. Additionally, a volumetric capacity of 14.3 Ah L –1 was achieved, surpassing those of most membraneless batteries reported to date regardless of redox chemistry, and underscores the potential of complexing agents in simplifying the architecture of conventional Zn–I 2 flow batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Synthesis of End-Functionalized Poly(norbornenes) and Poly(ethylidene norbornenes) Using a Pd(II) Catalyst in Combination with Chain Transfer Agents

Synthesis of end-functionalized poly(norbornene)s (PNBs) and poly(ethylidenenorbornene)s (PENBs) were prepared using the palladium catalyst t Bu 3 PPdMeCl/NaBAr f in combination with chain transfer agents (CTAs) 4-penten-1-ol and 10-undecenal. These CTAs produce polymers end-capped with -OH and -CHO groups, respectively, in high yields with M n values in the range of 6K to 17K, depending on the molar ratio of the CTA: monomer. End-functionalized PNBs and PENBs with precisely controlled Mn values and very narrow molecular weight distributions were accessed by using 4-penten-1-ol and 10-undecenal as chain-terminating agents following living polymerizations in which monomer is completely consumed. The utility of the aldehyde-functionalized polymers is illustrated via coupling to a dye molecule and by synthesis of ambiphilic diblock copolymers, PNB-b-PEG and PENB-b-PEG.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Dispersing Agents Impact Performance of Protonated Phosphonic Acid High-Temperature Polymer Electrolyte Membrane Fuel Cells

The microstructure of ionomers plays a significant role in the performance of high-temperature polymer electrolyte membrane fuel cells (HT-PEMFCs). Here, we establish direct correlations between the properties of dispersing agents and the microstructure of a protonated phosphonic acid ionomer. Most importantly, the formation of the porous structure of a protonated phosphonic acid ionomer depends on the pK a of the liquid media. Namely, the acid–base interaction between the charged polymer and dispersing agents determines the porosity in the ionomer thin films. The HT-PEMFC performance increases with the level of porosity of the ionomer, as the pores enable fast reactant gas accessibility. Overall, this study concludes the importance of the pK a of ionomers’ dispersing media for the HT-PEMFC performance.

25 ENERGY STORAGE↗
DOE OSTI2024

CACTUS: Chemistry Agent Connecting Tool Usage to Science

Large language models (LLMs) have shown remarkable potential in various domains but often lack the ability to access and reason over domain-specific knowledge and tools. In this article, we introduce Chemistry Agent Connecting Tool-Usage to Science (CACTUS), an LLM-based agent that integrates existing cheminformatics tools to enable accurate and advanced reasoning and problem-solving in chemistry and molecular discovery. We evaluate the performance of CACTUS using a diverse set of open-source LLMs, including Gemma-7b, Falcon-7b, MPT-7b, Llama3-8b, and Mistral-7b, on a benchmark of thousands of chemistry questions. Our results demonstrate that CACTUS significantly outperforms baseline LLMs, with the Gemma-7b, Mistral-7b, and Llama3-8b models achieving the highest accuracy regardless of the prompting strategy used. Moreover, we explore the impact of domain-specific prompting and hardware configurations on model performance, highlighting the importance of prompt engineering and the potential for deploying smaller models on consumer-grade hardware without a significant loss in accuracy. By combining the cognitive capabilities of open-source LLMs with widely used domain-specific tools provided by RDKit, CACTUS can assist researchers in tasks such as molecular property prediction, similarity searching, and drug-likeness assessment.

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

Dual Inhibitors of SARS-CoV-2 3CL Protease and Human Cathepsin L Containing Glutamine Isosteres Are Anti-CoV-2 Agents

SARS-CoV-2 3CL protease (Main protease) and human cathepsin L are proteases that play unique roles in the infection of human cells by SARS-CoV-2, the causative agent of COVID-19. Both proteases recognize leucine and other hydrophobic amino acids at the P 2 position of a peptidomimetic inhibitor. At the P 1 position, cathepsin L accepts many amino acid side chains, with a partial preference for phenylalanine, while 3CL-PR protease has a stringent specificity for glutamine or glutamine analogues. We have designed, synthesized, and evaluated peptidomimetic aldehyde dual-target (dual-acting) inhibitors using two peptide scaffolds based on those of two Pfizer 3CL-PR inhibitors, Nirmatrelvir, and PF-835321. Our inhibitors contain glutamine isosteres at the P 1 position, including 2-pyridon-3-yl-alanine, 3-pyridinyl-alanine, and 1,3-oxazo-4-yl-alanine groups. Inhibition constants for these new inhibitors ranged from K i = 0.6–18 nM (cathepsin L) and K i = 2.6–124 nM (3CL-PR), for which inhibitors with the 2-pyridon-3-yl-alanal substituent were the most potent for 3CL-PR. The anti-CoV-2 activity of these inhibitors ranged from EC 50 = 0.47–15 μM. X-ray structures of the peptidomimetic aldehyde inhibitors of 3CL-PR with similar scaffolds all demonstrated the formation of thiohemiacetals with Cys 145 , and hydrogen-bonding interactions with the heteroatoms of the pyridon-3-yl-alanyl group, as well as the nitrogen of the N-terminal indole and its appended carbonyl group at the P 3 position. The absence of these hydrogen bonds for the inhibitors containing the 3-pyridinyl-alanyl and 1,3-oxazo-4-yl-alanyl groups was reflected in the less potent inhibition of the inhibitors with 3CL-PR. In summary, our studies demonstrate the value of a second generation of cysteine protease inhibitors that comprise a single agent that acts on both human cathepsin L and SARS-CoV-2 3CL protease. Such dual-target inhibitors will provide anti-COVID-19 drugs that remain active despite the development of resistance due to mutation of the viral protease. Such dual-target inhibitors are more likely to remain useful therapeutics despite the emergence of inactivating mutations in the viral protease because the human cathepsin L will not develop resistance. This particular dual-target approach is innovative since one of the targets is viral (3CL-PR) required for viral protein maturation and the other is human (hCatL) which enables viral infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Impact of structural biology and the protein data bank on us fda new drug approvals of low molecular weight antineoplastic agents 2019–2023

Abstract Open access to three-dimensional atomic-level biostructure information from the Protein Data Bank (PDB) facilitated discovery/development of 100% of the 34 new low molecular weight, protein-targeted, antineoplastic agents approved by the US FDA 2019–2023. Analyses of PDB holdings, the scientific literature, and related documents for each drug-target combination revealed that the impact of structural biologists and public-domain 3D biostructure data was broad and substantial, ranging from understanding target biology (100% of all drug targets), to identifying a given target as likely druggable (100% of all targets), to structure-guided drug discovery (>80% of all new small-molecule drugs, made up of 50% confirmed and >30% probable cases). In addition to aggregate impact assessments, illustrative case studies are presented for six first-in-class small-molecule anti-cancer drugs, including a selective inhibitor of nuclear export targeting Exportin 1 (selinexor, Xpovio), an ATP-competitive CSF-1R receptor tyrosine kinase inhibitor (pexidartinib,Turalia), a non-ATP-competitive inhibitor of the BCR-Abl fusion protein targeting the myristoyl binding pocket within the kinase catalytic domain of Abl (asciminib, Scemblix), a covalently-acting G12C KRAS inhibitor (sotorasib, Lumakras or Lumykras), an EZH2 methyltransferase inhibitor (tazemostat, Tazverik), and an agent targeting the basic-Helix-Loop-Helix transcription factor HIF-2α (belzutifan, Welireg).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Engineering and evaluation of FXa bypassing agents that restore hemostasis following Apixaban associated bleeding

Direct oral anticoagulants (DOACs) targeting activated factor Xa (FXa) are used to prevent or treat thromboembolic disorders. DOACs reversibly bind to FXa and inhibit its enzymatic activity. However, DOAC treatment carries the risk of anticoagulant-associated bleeding. Currently, only one specific agent, andexanet alfa, is approved to reverse the anticoagulant effects of FXa-targeting DOACs (FXaDOACs) and control life-threatening bleeding. However, because of its mechanism of action, andexanet alfa requires a cumbersome dosing schedule, and its use is associated with the risk of thrombosis. Here, we present the computational design, engineering, and evaluation of FXa-variants that exhibit anticoagulation reversal activity in the presence of FXaDOACs. Our designs demonstrate low DOAC binding affinity, retain FXa-enzymatic activity and reduce the DOAC-associated bleeding by restoring hemostasis in mice treated with apixaban. Importantly, the FXaDOACs reversal agents we designed, unlike andexanet alfa, do not inhibit TFPI, and consequently, may have a safer thrombogenic profile.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Autonomous reinforcement learning agent for stretchable kirigami design of 2D materials

Abstract Mechanical behavior of 2D materials such as MoS 2 can be tuned by the ancient art of kirigami. Experiments and atomistic simulations show that 2D materials can be stretched more than 50% by strategic insertion of cuts. However, designing kirigami structures with desired mechanical properties is highly sensitive to the pattern and location of kirigami cuts. We use reinforcement learning (RL) to generate a wide range of highly stretchable MoS 2 kirigami structures. The RL agent is trained by a small fraction (1.45%) of molecular dynamics simulation data, randomly sampled from a search space of over 4 million candidates for MoS 2 kirigami structures with 6 cuts. After training, the RL agent not only proposes 6-cut kirigami structures that have stretchability above 45%, but also gains mechanistic insight to propose highly stretchable (above 40%) kirigami structures consisting of 8 and 10 cuts from a search space of billion candidates as zero-shot predictions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Operating advanced scientific instruments with AI agents that learn on the job

Advanced scientific user facilities, such as next generation X-ray light sources and self-driving laboratories, are revolutionizing scientific discovery by automating routine tasks and enabling rapid experimentation and characterizations. However, these facilities must continuously evolve to support new experimental workflows, adapt to diverse user projects, and meet growing demands for more intricate instruments and experiments. This continuous development introduces significant operational complexity, necessitating a focus on usability, reproducibility, and intuitive human-instrument interaction. In this work, we explore the integration of agentic AI, powered by Large Language Models (LLMs), as a transformative tool to achieve this goal. We present our approach to developing a human-in-the-loop pipeline for operating advanced instruments including an X-ray nanoprobe beamline and an autonomous robotic station dedicated to the design and characterization of materials. Specifically, we evaluate the potential of various LLMs as trainable scientific assistants for orchestrating complex, multi-task workflows, which also include multimodal data, optimizing their performance through optional human input and iterative learning. We demonstrate the ability of AI agents to bridge the gap between advanced automation and user-friendly operation, paving the way for more adaptable and intelligent scientific facilities.

Large Language Models↗
DOE OSTI2026

An agentic artificially intelligent X-ray scientist

Executing experimental tasks in both normal research laboratories and large-scale scientific facilities often requires extensive human supervision and remains a key challenge on the path to fully autonomous, artificial intelligence (AI)-driven science. Here we demonstrate a large language model-driven agent that autonomously performs X-ray sample alignment on a synchrotron beamline by planning actions, executing instrumental commands, interpreting observations and iterating towards experimental goals. Based on existing large language models with structured tool-use via the model context protocol, our AI X-ray scientist was guided and tested using an in-house-built virtual experimental setup that mirrors a six-circle diffractometer at an operational synchrotron beamline. The agentic workflow developed in the virtual environment was directly deployed on a real beamline, where it correctly identified reference reflections and determined the orientation matrix, an essential first step in any type of single-crystal scattering experiment. Our AI X-ray scientist responded effectively to unexpected experimental conditions, demonstrating adaptive problem-solving and readiness for addressing practical experimental situations. Our study provides a step towards autonomous operation across diverse experimental environments at large-scale scattering facilities.

Chen, Zhantao (ORCID:0000000319543868)↗
DOE OSTI2026

Managing autonomous materials labs with multi-agent AI and its implications for the science of science

Self-driving lab systems (aka, autonomous experimentation) accelerate research - letting scientists learn faster, spend less resources, and fail smarter in well defined, narrow studies. The next-generation materials lab combines self-driving systems to tackle broader challenges - orchestrating complex research campaigns while optimizing lab resources. We propose that agent-based and agentic artificial intelligence will be an integral part of next-generation lab management and discuss potential implementation scenarios. Additionally, digital and physical sandboxes will allow scientists to evaluate diverse and dynamic research and lab management strategies. Beyond the immediate benefit to lab optimization, such sandboxes will enable realistic computational studies of the philosophy of science (i.e., science of science) to achieve higher level scientific efficiencies.

Computer science↗
DOE OSTI2023

Highly efficient synthesis of zeolite chabazite using cooperative hydration-mismatched inorganic structure-directing agents

Chabazite (CHA type) zeolite is notoriously difficult to synthesize in the absence of organic structure-directing agents owing to long synthesis times and/or impurity formation. The ability to tailor organic-free syntheses of zeolites is additionally challenging due to the lack of molecular level understanding of zeolite nucleation and growth pathways, particularly the role of inorganic cations. In this study, we reveal that zeolite CHA can be synthesized using six different combinations of inorganic cations, including the first reported seed- and organic-free synthesis without the presence of potassium. We show that lithium, when present in small quantities, is an effective accelerant of CHA crystallization; and that ion pairings can markedly reduce synthesis times and temperatures, while expanding the design space of zeolite CHA formation in comparison to conventional methods utilizing potassium as the sole structure-directing agent. Herein, we posit the effects of cation pairings on zeolite CHA crystallization are related to their hydrated ionic radii. We also emphasize the broader implications for considering the solvated structure and cooperative role of inorganic cations in zeolite synthesis within the context of the reported findings for chabazite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗