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2023 Project Peer Review Report

The Bioenergy Technologies Office (BETO) within the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy supports the research, development, and demonstration (RD&D) of technologies aimed at mobilizing domestic renewable carbon resources for the reduction of greenhouse gas emissions across the U.S. economy. BETO systematically prioritizes RD&D into technology opportunities across a range of emerging scientific breakthroughs and technology readiness levels in the subprogram areas illustrated in Figure 1. This approach supports a diverse portfolio while developing the most promising and widely applicable technologies, testing technologies as integrated processes, and demonstrating integrated processes to support scale-up. These technologies will use a broad variety of renewable carbon resources to produce increasing volumes of biofuels and bioproducts. More information on BETO’s mission, goals, and strategic approaches can be found in the Bioenergy Technologies Office Multi-Year Program Plan. The biennial Peer Review process enables external stakeholders to provide feedback on the responsible use of taxpayer funding and develop recommendations for the most efficient and effective ways to accelerate the development of a bioenergy industry. This report includes the results of the Project Peer Review meeting held on April 3–7, 2023, in Denver, Colorado.

09 BIOMASS FUELS↗

RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence (University of Delaware)

This report summarizes the activities, technical accomplishments, and outcomes of the RAPIDS2 Institute project at the University of Delaware (UD). The RAPIDS2 Institute was a large multi-institution project with the objective of assisting SciDAC and Office of Science application teams in the use of DOE supercomputing resources to achieve scientific breakthroughs. The UD team contributed to this effort through work on formal software verification. This thrust aims to reduce software developer time and effort, especially regarding debugging and testing, and to increase confidence in the correctness of the results computed by the software.

97 MATHEMATICS AND COMPUTING↗

Progress of Gas Injection EOR Surveillance in the Bakken Unconventional Play—Technical Review and Machine Learning Study

Although considerable laboratory and modeling activities were performed to investigate the enhanced oil recovery (EOR) mechanisms and potential in unconventional reservoirs, only limited research has been reported to investigate actual EOR implementations and their surveillance in fields. Eleven EOR pilot tests that used CO2, rich gas, surfactant, water, etc., have been conducted in the Bakken unconventional play since 2008. Gas injection was involved in eight of these pilots with huff ‘n’ puff, flooding, and injectivity operations. Surveillance data, including daily production/injection rates, bottomhole injection pressure, gas composition, well logs, and tracer testing, were collected from these tests to generate time-series plots or analytics that can inform operators of downhole conditions. A technical review showed that pressure buildup, conformance issues, and timely gas breakthrough detection were some of the main challenges because of the interconnected fractures between injection and offset wells. The latest operation of co-injecting gas, water, and surfactant through the same injection well showed that these challenges could be mitigated by careful EOR design and continuous reservoir monitoring. Reservoir simulation and machine learning were then conducted for operators to rapidly predict EOR performance and take control actions to improve EOR outcomes in unconventional reservoirs.

Energy & Fuels↗

Single–Well Injection–Drift Test to Estimate Groundwater Velocity

A simple algebraic equation is presented here to estimate the magnitude of groundwater velocity based on data from a single-well injection-drift test thereby eliminating the time-consuming and costly extraction phase. A volume of tracer-amended water was injected by forced-gradient into a single well followed by monitoring of the conservative solute tracers under natural-gradient conditions as their upgradient portions drifted back through the well. The breakthrough curve data from the single well during the drift phase was analyzed to determine the mean travel times of the tracers. The estimated mean upgradient travel distance back through the single well and the mean travel times of the tracers were used in a simple algebraic equation to estimate groundwater velocity. The groundwater velocity based on the single-well injection-drift test was estimated to be approximately 0.64 ft per day. Two transects of observation wells were used to monitor the natural-gradient tracer transport downgradient of the injection well. The one-dimensional, or dual-well, transport of the tracer from the injection well to the nearest downgradient observation well indicated that the groundwater velocity was 0.55 ft per day. The two-dimensional, or multi-well, transport of the center of mass of the tracers indicated that the groundwater velocity was 0.60 ft per day; the dual- and multi-well results were in excellent agreement with those from the single-well and validated the simple algebraic equation. In conclusion, the new single-well method presented here is relatively simple, rapid, and does not require an extraction phase.

54 ENVIRONMENTAL SCIENCES↗

Mechanistic definition and prediction of the mass exchange coefficient between rivers and hyporheic zones: The $α$ of two $Ω$s

Solute transport in interconnected rivers and hyporheic zones is typically modeled through dual-domain models where first-order solute mass transfer between the two domains, Ω R and Ω HZ , is represented by a coefficient α. The transient storage model (TSM) is an example of such an approach. In practice, α is determined by fitting the tails of solute tracer breakthrough curves using a TSM. This approach has led to ambiguity regarding α’s physical meaning and transferability. Here, in this work, we investigated the physical basis for α and tested it with virtual experiments through the fully coupled multiphysics model hyporheicFoam for the Ω R – Ω HZ system. hyporheicFoam explicitly simulated coupled flow and solute transport over a kilometer with centimeter-scale resolution. Model results were analyzed to calculate α following its theoretical definition directly. Using the determined α within a TSM enables accurate reproduction of solute transport, underscoring α’s physical relevance and precision.

54 ENVIRONMENTAL SCIENCES↗

First Ever Polymer Flood Field Pilot to Enhance the Recovery of Heavy Oils on Alaska North Slope – Producer Responses and Operational Lessons Learned

The US Department of Energy and Hilcorp Alaska, LLC are jointly cosponsoring a field pilot project entitled “First Ever Field Pilot on Alaska’s North Slope to Validate the Use of Polymer Floods for Heavy Oil Enhanced Oil Recovery (EOR).” The objective of this pilot is to perform a field experiment to validate the use of an advanced polymer flooding technology to unlock the vast heavy oil resources on Alaska North Slope (ANS). Two pairs of horizontal injection and production wells have been deployed in an isolated fault block of the Schrader Bluff heavy oil reservoir at the Milne Point Field to conduct a polymer flood pilot which was designed to acquire field performance data to optimize polymer flood design in the Schrader Bluff heavy oil reservoirs on ANS. Hydrolyzed polyacrylamide (HPAM) polymer injection started on August 28, 2018 using a custom made polymer mixing and pumping unit. Polymer solution properties such as concentration, viscosity, and filter ratio, have been closely monitored and adjusted as necessary. Operational procedures have been improved to ensure adequate injectivity and polymer propagation through the formation. Oil and water production is tested frequently to monitor water cut performance, and produced water is sampled and analyzed for polymer content. Tracers were pumped pre and post polymer injection startup to compare polymer flood breakthrough timing and sweep efficiency. Polymer injectivity of the horizontal wells drilled in the Schrader Bluff NB sand is found to be sufficient to replace the reservoir production voidage although there were some declines as high viscosity polymer swept the near wellbore region. Production data show significant reduction in water cut and the oil production rate has stabilized. No polymer production has been confirmed from the two horizontal producers after 22 months of polymer injection into the two supporting horizontal injectors. Tracer data show very low sweep efficiencies with waterflood alone, whereas significant improvement has been achieved with polymer flood. Many operational lessons have been learned and improvements have been made regarding polymer mixing, pumping, and onsite quality control, particularly in a challenging Arctic environment. Adequate polymer injection rate can be achieved with diligent monitoring and quality assurance of the properties of the injected polymer solution.

Ning, Samson↗

Experimental Investigation on Separation Behavior of Heavy-Oil Emulsion for Polymer Flooding on Alaska North Slope

The first-ever field pilot on Alaska North Slope (ANS) to validate using polymer floods for heavy-oil enhanced oil recovery is currently ongoing. One of the major concerns of the operator is the effect of polymer on oil/water-separation efficiency after polymer breakthrough. This work investigates the influence of polymer on the separation behavior of heavy-oil emulsions and evaluates the performance of emulsion breakers (EBs). In this study, two types of heavy-oil emulsions were prepared and tested at 20 and 50% water cut (WC), respectively. The bottle test method was used in the experiments, in which the separated water volume with time, the separated water quality, and the volume fraction of phases were recorded. Results showed that polymer accelerated the oil/water separation acting as an emulsion inhibitor at 20% WC but tended to impede the water separation at 50% WC. Regardless of WC, polymer resulted in poor water quality and the formation of a stable intermediate oil in water (o/w) emulsion, because of the increased viscosity of the water phase. The performance of EBs showed a complex dependency on the WC, the type of demulsifier and dosage, and the polymer concentration. Despite the varied conditions encountered in the heavy-oil/water/polymer/demulsifier system, a compound EB achieved satisfactory demulsification performance, showing the highest potential for deployment in the current ANS polymer flooding pilot. Here, we systematically studied the potential influence of polymer breakthrough on the separation behavior of heavy-oil emulsion on ANS for the first time. The findings of this study will provide practical guidance in advance for produced fluid treatment of the ongoing first-ever polymer flooding pilot on ANS.

54 ENVIRONMENTAL SCIENCES↗

Enhancing Heavy-Oil-Recovery Efficiency by Combining Low-Salinity-Water and Polymer Flooding

Summary Combining low-salinity-water (LSW) and polymer flooding was proposed to unlock the tremendous heavy-oil resources on the Alaska North Slope (ANS). The synergy of LSW and polymer flooding was demonstrated through coreflooding experiments at various conditions. The results indicate that the high-salinity polymer (HSP) (salinity = 27,500 ppm) requires nearly two-thirds more polymer than the low-salinity polymer (LSP) (salinity = 2,500 ppm) to achieve the target viscosity at the condition of this study. Additional oil was recovered from LSW flooding after extensive high-salinity-water (HSW) flooding [3 to 9% of original oil in place (OOIP)]. LSW flooding performed in secondary mode achieved higher recovery than that in tertiary mode. Also, the occurrence of water breakthrough can be delayed in the LSW flooding compared with the HSW flooding. Strikingly, after extensive LSW flooding and HSP flooding, incremental oil recovery (approximately 8% of OOIP) was still achieved by LSP flooding with the same viscosity as the HSP. The pH increase of the effluent during LSW/LSP flooding was significantly greater than that during HSW/HSP flooding, indicating the presence of the low-salinity effect (LSE). The residual-oil-saturation (Sor) reduction induced by the LSE in the area unswept during the LSW flooding (mainly smaller pores) would contribute to the increased oil recovery. LSP flooding performed directly after waterflooding recovered more incremental oil (approximately 10% of OOIP) compared with HSP flooding performed in the same scheme. Apart from the improved sweep efficiency by polymer, the low-salinity-induced Sor reduction also would contribute to the increased oil recovery by the LSP. A nearly 2-year pilot test in the Milne Point Field on the ANS has shown impressive success of the proposed hybrid enhanced-oil-recovery (EOR) process: water-cut reduction (70 to less than 15%), increasing oil rate, and no polymer breakthrough so far. This work has demonstrated the remarkable economical and technical benefits of combining LSW and polymer flooding in enhancing heavy-oil recovery.

Engineering↗

ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability

Earth system predictability is challenged by the complexity of environmental dynamics and the multitude of variables involved. Current AI foundation models, although advanced by leveraging large and heterogeneous data, are often constrained by their size and data integration, limiting their effectiveness in addressing the full range of Earth system prediction challenges. To overcome these limitations, we introduce the Oak Ridge Base Foundation Model for Earth System Predictability (ORBIT), an advanced vision transformer model that scales up to 113 billion parameters using a novel hybrid tensor-data orthogonal parallelism technique. As the largest model of its kind, ORBIT surpasses the current climate AI foundation model size by a thousandfold. Performance scaling tests conducted on the Frontier supercomputer have demonstrated that ORBIT achieves 684 petaFLOPS to 1.6 exaFLOPS sustained throughput, with scaling efficiency maintained at 41% to 85% across 49,152 AMD GPUs. These breakthroughs establish new advances in AI-driven climate modeling and demonstrate promise to significantly improve the Earth system predictability.

Wang, Xiao↗

Ultra-High Temperature Thermal Barrier Coating Development and Validation

The most effective method to improve industrial gas turbine power is to increase firing temperature. To maintain component durability at these higher temperatures, thermal barrier coatings (TBC’s) are playing an increasing role in protecting turbine hardware. TBC’s have been successfully used on Solar Turbines’ combustor liners and turbine airfoils, but there is a need for TBC’s that can operate at higher temperatures. Based on recent, favorable rig testing experience, Solar recognized that yttrium aluminum garnet (YAG) TBC’s made by the Solution Precursor Plasma Spray Process (SPPS) has great potential for higher turbine temperatures. This testing verified the thermal cycle durability of the SPPS YAG TBC’s, as well as demonstrated that the temperature drop through the SPPS YAG TBC was twice that measured across a companion APS YSZ TBC. The SPPS YAG TBC with the potential for a 200°C improvement in temperature capability represents a materials breakthrough. The SPPS process also produces a number of unique microstructural features that confer superior properties. SPPC TBC’s have ultra-fine splats that increase toughness and erosion resistance, and the process can be tailored to produce through-thickness cracks for strain-tolerance and control porosity for lower thermal conductivity and increase coating abradability. This proposal would include further development of SPPS YAG density-graded coatings, optimization of the application process, and validation of higher temperature capability and durability through rig and engine testing of coated combustion liners and turbine outer air seals. The technology would be advanced from a TRL 3 to a proposed TRL 6 by overcoming processing concerns on efficiency, application distance and optimization of a graded coating without impacting coating durability by demonstrating the coating performance on components in rig and development gas turbine engine testing.

36 MATERIALS SCIENCE↗

Discrete fracture network model benchmarks developed and applied in a DECOVALEX-2023 repository performance assessment study

This study presents newly developed benchmarks for modeling flow and transport within discrete fracture networks (DFNs) and useful methods for analyzing the results. The new benchmarks are designed to test modeling approaches for use in probabilistic performance assessment models of deep geologic repositories in fractured rock. The benchmarks simulate flow and transport through a 1 km 3 block of fractured rock. The first simulates migration of a short pulse of tracer through a simple network of four intersecting fractures. The second adds 1089 stochastically generated fractures. The third changes the pulse to a continuous point source. Evaluation of model performance relies on moment analysis and comparison of the results of different models. The expected nondimensional first moment of the conservative tracer for each benchmark is 1. The benchmarks were simulated by teams from Canada, Czechia, Germany, Korea, Sweden, Taiwan, and the United States as part of a DECOVALEX-2023 study (decovalex.org). The teams used various approaches, including explicit DFN modeling, DFN upscaling to an equivalent continuous porous medium (ECPM), and a combination of both methods. Transport mechanisms are modeled using either the advection-dispersion equation or particle tracking. Results demonstrate strong agreement among the models in breakthrough behavior up to the 75th percentile. Significant deviations in first moments and well-clustered outputs led to the identification of inaccuracies in several models. Such findings exemplify the benefit of exercising these benchmarks and using the presented methods to test DFN flow and transport models.

Benchmark↗

Revolutionizing thermal Management in Next-Generation AI data centers: Challenges and breakthrough innovations

Data centers (DCs) serve as critical infrastructure for powering the growth and evolution of AI. Next-generation AI DCs present unique challenges in thermal management driven by unprecedented computational demands. This paper provides a comprehensive summary of key stakeholder perspectives on technology gaps, infrastructure requirements, test bed needs, emerging opportunities, and preliminary solutions related to thermal management for AI DCs. It establishes six strategic pillars of thermal management for next generation AI DC: reliability, deployability, efficiency, resilience, measurability, and valorization. The discussion spans a range of critical topics, including advanced cooling technologies, thermal strategies for emerging modular and edge DCs, system-level optimization and control frameworks, infrastructure planning and grid integration designs, benchmarking approaches, and pathways for waste heat recovery and reuse. The proposed research, development, and demonstration efforts are aimed at accelerating the deployment of AI DCs while ensuring energy efficiency, reliability, safety, and regulatory compliance.

Wang, Pengtao [ORNL] (ORCID:0000000214713429)↗

DOE Energy Frontier Research Centers Center for Direct Catalytic Conversion of Biomass to Biofuels (C3Bio)

New capabilities to predict, design and control the chemistries of carbon could answer a global imperative to transition from fossil-based to sustainable transportation fuels. While the use of inexpensive hydrocarbons has been an unparalleled achievement and enabler of economic prosperity for many nations, singular dependence upon crude oil has given rise to systemic vulnerabilities in climate, energy, economic, and national security. Lignocellulosic biomass, a renewable and carbon-neutral resource, has the potential to displace an estimated annual equivalent of three billion barrels of oil in the U.S. alone (National Research Council 2009, U. S. Department of Energy, 2011). However, biomass has only one-third the energy density of crude oil (Agrawal and Singh 2009, Richard 2010) and lacks petroleum’s versatility as a feedstock for fuels and chemicals. These limitations keep biomass conversion below the efficiency level needed for strategic impact while the scientific challenge of routing carbon from one molecular context to another remains unmet. In 2009, the Center for Direct Catalytic Conversion of Biomass to Biofuels (C3Bio) recognized the potential of chemical catalysis and fast pyrolysis to overcome such limitations by transforming the main components of biomass (cellulose, xylan, and lignin) from grasses and trees directly to liquid hydrocarbons and aromatic co-products. Enabled by the EFRC high-risk, high-reward approach to grand challenge science, C3Bio researchers have been key national players in disrupting the conventional paradigm of the cellulosic biorefinery into a new future of “no carbon left behind”—the full utilization of carbon from plant cell walls in energy-dense fuels (Fig. 1). We identified catalytic and fast-pyrolytic pathways that utilize cellulose, xylan and, most significantly, lignin. We developed catalytic processes that deoxygenate and transform monomers and isolated polymers into useful products and tested their use with intact biomass. We gained control of lignin synthesis within plants and initiated tailoring biomass to its end-use through the tools of plant molecular biology and genetic engineering. C3Bio breakthroughs have increased the energy density of biomass-derived substrates via catalytic and pyrolytic conversions into products such as benzoquinones, furfural and hydroxymethylfurfural, levoglucosan and levulinic acid, methoxypropylphenols and propylbenzene. Such advances in biomass conversion would not have been possible without simultaneous advances in analytical instrumentation and methodologies, and imaging technologies and applications. The legacy science developed by C3Bio enables design and control strategies for achieving a targeted product portfolio of fuel and chemical feedstocks from a diverse range of native and tailored biomass. Our research provides the knowledge base required for a bio-economy with product streams as diverse in functionality as those of the petrochemical industry. Coupling targeted computational modeling with experimentation, we achieved: (1) fundamental understanding of biopolymers and cell wall architecture assembly, (2) discovery of new chemistries that allow the development of highly selective pathways to fuels and desirable chemicals, and (3) an integrated systems-level understanding to control catalytic and pyrolytic pathways.

09 BIOMASS FUELS↗

Adsorption-based direct air capture using hierarchical porous composites prepared via confined-space crystallization

Capturing CO₂ at trace concentration remains a critical challenge in sustainable carbon management via adsorption, as conventional adsorbents suffer from low CO₂ selectivity, poor moisture tolerance, and energy-intensive regeneration requirements. Here, we report a hierarchical Ba²⁺-exchanged silicoaluminophosphate (Ba²⁺-CSAPO-34) composite synthesized via confined-space crystallization within an activated carbon matrix. Comprehensive characterization revealed a confined nucleation mechanism and the successful incorporation of Ba²⁺ active sites within the SAPO-34 framework, achieved via a two-step liquid ion-exchange protocol. The core-shell architecture combines the selective CO₂ binding of Ba²⁺-functionalized SAPO-34 with the hydrophobic protection of the carbon shell. Fixed-bed adsorption tests demonstrated strong CO₂ binding (at 500-2500 ppm), no roll-up, and effective suppression of water affinity, while maintaining high selectivity even at 90% relative humidity. A phenomenological adsorption model, validated against dynamic breakthrough data, accurately predicted dynamic adsorption behavior under real-world operating conditions, enabling rational process design for direct air capture (DAC) and closed-loop life support systems. Furthermore, these results establish Ba²⁺-CSAPO-34 as a scalable, moisture-resistant adsorbent that addresses key limitations in trace CO₂ capture, advancing practical implementation of carbon removal technologies.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

STARFIRE – Science and Technology Accelerated Research for Fusion Innovation and Reactor Engineering progress report

The STARFIRE hub leverages foundational science and technology (S&T) research and integrated plant modeling tools to advance Inertial Fusion Energy (IFE). S&T breakthroughs achieved in each thrust are incorporated into an integrated modeling tool to assess and prioritize remaining gaps to bridge for IFE to become viable. Scientific highlights span high-gain target design, diode-pumped solid-state lasers, and innovative target manufacturing. Key highlights include the investigation of shock propagation through various foam structures among other limiting factors of compression of IFE target, exploration of novel 3D printing techniques such as light-sheet additive manufacturing for 2-photon polymerization foams, and diode-pumped solid-state laser architectures required for several IFE approaches. In addition, the STARFIRE team has established two public-private working groups to address laser diode supply chain issues and test advanced laser diode configurations. Finally, a lite version of the integrated modeling tool has been developed to facilitate outreach and engage with private companies. STARFIRE’s management structure has been designed to ensure agile resource allocation, robust performance assessment, and alignment with the broader fusion energy mission. STARFIRE’s breakthroughs are disseminated to the community via reports, presentations, and publications, while agreements with private companies are set in place to protect proprietary information.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding the high-temperature behavior and corrosion resistance of Cr-Nb coated cladding for BWRs

While Cr-coated Accident Tolerant Fuel has proven successful in Pressurized Water Reactors, its dissolution in high dissolved oxygen Boiling Water Reactor environments represents a major technological barrier. Here, this study presents a comprehensive evaluation of novel Cr-Nb alloys as a coating breakthrough solution for Accident Tolerant Fuel cladding in Boiling Water Reactors. We systematically investigated Physical Vapor Deposited Cr-Nb coatings with 13% and 24 at% Nb content on commercial Zr-based cladding through rigorous testing under both normal and accident conditions. Our results demonstrate Cr-Nb coatings remained completely intact during extended Boiling Water Reactor autoclave testing, while pure Cr coatings failed catastrophically due to oxide dissolution. Under Loss-of-Coolant Accident conditions at 1100°C, Cr-Nb coatings maintained protective capability for 45 min. At 800°C, the alloy coatings matched pure Cr's excellent corrosion resistance. Despite microstructural changes during prolonged high-temperature exposure, no coating delamination occurred, ensuring continued protection of the underlying Zr substrate. These findings establish Cr-Nb coatings as a viable Accident Tolerant Fuel solution for Boiling Water Reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Ultrasonic waveguide reflectometry for quench detection (CRADA Final Report)

Early detection of thermal runaway (quench) is critical for safely operating high-temperature superconductor (HTS) magnets. Voltage-based techniques provide late detection of quenching in HTS, which can lead to magnet burnout and system damage. Various non-voltage quench-detection approaches are therefore investigated nowadays that are based on magnetic, acoustic, and optical sensing. LBNL has been actively developing the quench detection principle based on diffuse ultrasonic wave propagation since 2017 and has demonstrated the approach's viability with several peer-reviewed publications and a patent application. Over the last decade, Etegent, LBNL partner for this proposal and effort, has been developing a sensing technology that utilizes the propagation of stress waves through the solid metallic and nonmetallic waveguides (WG). The method is based on the dependence of materials' elastic properties and the speed of sound on temperature. Compared with optical analog, acoustic WG operates at much lower frequencies, eliminating the need for expensive, complex, highly sensitive receivers and data processing. Etegent proved this technology in many harsh environments, mainly concentrated high-temperature measurements. The initial contact between LBNL and Etegent started in 2020, aiming at combining our knowledge and effort toward developing a viable ultrasound-based quench detection technique for use with HTS magnets. A preliminary study conducted jointly in 2022 found no principle restrictions for expanding the WG technology toward cryogenic temperature operation. The present CRADA work aimed at designing, building, and testing ultrasonic waveguide temperature sensors at relevant cryogenic conditions, and demonstrating this technology's applicability to detecting heating and quenching in High Temperature Superconductor (HTS)-based cables and magnets. The technical objectives of the project included: (1) Design and fabricate ultrasonic WG sensors suitable for cryogenic operation, (2) Test ultrasonic WGs under cryogenic conditions, (3) Determining a suitable way of insulating WGs to prevent ultrasonic leakage while maintaining good thermal contact with the surrounding medium, (4) WG integration and cryogenic test with HTS conductors and HTS magnets, and (5) Design and basic prototyping of a standalone WG-based quench detection system. This project adds value to the present LBNL magnet diagnostics portfolio and enables a breakthrough in addressing the HTS magnet quench detection challenge.

47 OTHER INSTRUMENTATION↗

Adaptive Pore Opening to Form Tailored Adsorption Sites in a Cooperatively Flexible Framework Enables Record Inverse Propane/Propylene Separation

A proposed low-energy alternative to the separation of alkanes from alkenes by energy-intensive cryogenic distillation is separation by porous adsorbents. Unfortunately, most adsorbents preferentially take up the desired, high-value major component alkene, requiring frequent regeneration. Adsorbents with inverse selectivity for the minor component alkane would enable the direct production of purified, reagent-grade alkene, greatly reducing global energy consumption. However, such materials are exceedingly rare, especially for propane/propylene separation. Here, we report that through adaptive and spontaneous pore size and shape adaptation to optimize an ensemble of weak noncovalent interactions, the structurally responsive metal-organic framework CdIF-13 (sod-Cd(benzimidazolate) 2 ) exhibits inverse selectivity for propane over propylene with record-setting separation performance under industrially relevant temperature, pressure, and mixture conditions. Powder synchrotron X-ray diffraction measurements combined with first-principles calculations yield atomic-scale insight and reveal the induced fit mechanism of adsorbate-specific pore adaptation and ensemble interactions between ligands and adsorbates. Dynamic column breakthrough measurements confirm that CdIF-13 displays selectivity under mixed-component conditions of varying ratios, with a record measured selectivity factor of α ≈ 3 at 95:5 propylene:propane at 298 K and 1 bar. When sequenced with a low-cost rigid adsorbent, we demonstrated the direct purification of propylene under ambient conditions. In conclusion, this combined atomic-level structural characterization and performance testing firmly establishes how cooperatively flexible materials can be capable of unprecedented separation factors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗