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At least 181 records · Page 10

Structural design and optimization of a series of 13.2 MW downwind rotors

The quest for reduced LCOE has driven significant growth in wind turbine size. A key question to enable larger rotor designs is how to configure and optimize structural designs to constrain blade mass and cost while satisfying a growing set of challenging structural design requirements. In this paper, we investigate the performance of a series of three two-bladed downwind rotors with different blade lengths (104.3-m, 122.9-m, and 143.4-m) all rated at 13.2 MW. The primary goals are to achieve 25% rotor mass and 25% LCOE reduction. A comparative analysis of the structural performance and economics of this family rotors is presented. To further explore optimization opportunities for large rotors, we present new results in a root and spar cap design optimization. In summary, we present structural design solutions that achieve 25% rotor mass reduction in a SUMR13i design (104.3-m) and 25% LCOE reduction in a SUMR13C design (143.4-m).

Yao, Shulong↗

Transformational Challenge Reactor – On the Application of Design for Additive Manufacturing (DfAM) Techniques to the Conception of Nuclear Core

Additive manufacturing (AM) technologies are radically changing the way objects are designed and manufactured. They allow building by deposition and solidification of material layer by layer, enabling the possibility to create simple and complex features alike, almost seamlessly. Generally, the design optimization process requires to define objectives, design variables and constraints. Additive manufacturing does not challenge this process per se but does allow designers to completely redefine the constraints space as the ones originating from fabrication can be considerably relaxed compared to more “traditional” manufacturing. Thus, design optimization becomes naturally far more responsive to the actual physics being solved and considerably less influenced by fabrication limitations, leading to dramatically different designs. To take advantage of these new opportunities, so-called Designing for Additive Manufacturing (DfAM) techniques are emerging. Development of design techniques specifically tailored for additive manufacturing is warranted because, considering AM, the design space is typically considerably larger than with traditional manufacturing. The ability to explore the design space efficiently is of paramount importance for designers. This study proposes to investigate and apply some of these DfAM techniques to the conception of nuclear core. The goal being to assess if these new methods can be applied to core design and if core design could benefits from additive manufacturing technologies. After a brief investigation on the pertinence of some DfAM techniques for core design, algorithms are proposed and a workflow is established to carry neutronics and steady-state thermal-hydraulics analyses. To diminish the work load, the workflow has been automated using python modules. These modules allow the rapid creation of input files, post-treatment of output files and visualization. To test the pertinence of the proposed workflow, three test cases have been investigated: a research and test reactor, a micro-reactor and a space propulsion reactor. These test cases offered a variety of objectives, constraints and operating conditions. It is observed that the proposed workflow is capable of converging quickly and efficiently to valid design solutions. It is then concluded that DfAM techniques can be applied to core design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials

A major challenge in materials design is how to efficiently search the vast chemical design space to find the materials with desired properties. One effective strategy is to develop sampling algorithms that can exploit both explicit chemical knowledge and implicit composition rules embodied in the large materials database. Here, we propose a generative machine learning model (MatGAN) based on a generative adversarial network (GAN) for efficient generation of new hypothetical inorganic materials. Trained with materials from the ICSD database, our GAN model can generate hypothetical materials not existing in the training dataset, reaching a novelty of 92.53% when generating 2 million samples. The percentage of chemically valid (charge-neutral and electronegativity-balanced) samples out of all generated ones reaches 84.5% when generated by our GAN trained with such samples screened from ICSD, even though no such chemical rules are explicitly enforced in our GAN model, indicating its capability to learn implicit chemical composition rules to form compounds. Our algorithm is expected to be used to greatly expand the range of the design space for inverse design and large-scale computational screening of inorganic materials.

36 MATERIALS SCIENCE↗

Heterogeneous Integration Technologies for High-temperature, High-density, Low-profile Power Modules of Wide Bandgap Devices in Electric Drive Applications (Final Technical Report)

The goal of this project is to develop packaging technologies for making high-temperature, high-density, and low-profile wide-bandgap (WBG) power electronics modules for electric drives. These modules are aimed at enabling the DOE’s University Consortium to reach its 2025 inverter targets of ≥ 100 kW/L and ≤ 2.7 $/kW. The specific objectives are to: design and fabricate SiC half-bridge power modules with double-sided cooling and parasitic inductances < 5 nH, heat flux density > 400 W/cm 2 , and working junction temperature of 200 o C; design, fabricate, and deliver a gate driver with double-sided cooled modules for the construction of a 100 kW/L inverter at Oak Ridge National Lab; and design and prototype intelligent gate drivers with integrated current sensor and a low-profile DC-DC power supply with air-core transformer for testing power modules at 200 o C junction temperature. We followed an iterative technical approach of design, simulation, fabrication, and testing of various versions of modules, current sensors, and power supply. The state-of-the-art silicon carbide devices rated at 1.2 kV and 149 A were packaged by sintered-silver bonding on an aluminum nitride direct-bond-copper substrate for high thermal conductivity, high working temperature, and high joint reliability. Porous silver posts were used to interconnect the device’s source pads to the other direct-bond-copper substrate for low mechanical stresses, ease of manufacturing, and double-sided cooling. A current sensor based on package parasitic inductance was developed to measure switching current. A dynamic feedback scheme was developed to compensate the effect of parasitic resistance and temperature variation. A constant-current class-E dc-dc converter with air-core transformer was developed. Air-core transformer was used due to the unavailability of magnetic core at high temperatures. Gate driver and power supply were integrated with the double-side cooled, high temperature SiC power modules for testing the modules at 200 o C junction temperature. Double-pulse and continuous testing of the integrated technologies validated the design and fabrication of the three component technologies. Throughout the project, we overcame the challenge for design verification caused by low prototyping yield, which then helped train the graduate students, the future workforce, to learn the engineering know-how for low-cost manufacturing of reliable products. Below is a summary of the major accomplishments of this project: development of a prototyping process for fabricating double-side cooled (1200 V, 149 A) SiC phase-leg modules capable of working to 200 o C Tj; simulation and experimental verification of the improvement of thermo-mechanical reliability of the double-side cooled SiC phase-leg module by using rigid encapsulant; design and experimental validation of a current sensor based on package parasitic inductance and a compensation solution for eliminating the effect of parasitic resistance; design and experimental validation of a low-profile power supply with six-output air-core transformer for gate driver; functional demonstration of a SiC phase-leg module integrated with its gate driver, current sensor, and an air-core power supply at 200 o C Tj in a double-pulse switching test setup and Buck converter continuous test setup; successful completion of six PhD and two MS students who are or will work at Apple Inc., Tesla Inc., Wolfspeed Inc., Microchip Inc., Monolithic Power Systems Inc., and LG Magna Inc.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

High-resolution chemical patterns from negative tone resists for the integration of extreme ultraviolet patterns of metal-oxide resists with directed self-assembly of block copolymers

Extreme ultraviolet (EUV) lithography faces significant challenges in designing suitable resist materials that can provide adequate precision, while maintaining economically viable throughput. These challenges in resist materials have led to printing failures and high roughness in EUV patterns, compromising the performance of semiconductor devices. Integrating directed self-assembly (DSA) of block copolymers (BCPs) with EUV lithography offers a promising solution because, while the BCPs register to the EUV-defined chemical guiding pattern, the thermodynamically determined structures of the BCPs automatically rectify defects and roughness in the EUV pattern. Despite the superior resolution of metal-oxide EUV resists (MORs), their application to DSA is limited by the difficulty in converting them into chemical patterns that allow effective transfer of the rectified patterns of DSA films into inorganic materials. To address this challenge, this study introduces a novel strategy for fabricating chemical patterns using hydrogen silsesquioxane (HSQ), a high-resolution negative tone inorganic resist, as a model system for MORs. Initially, a sacrificial Cr pattern is generated from HSQ patterns via reactive ion etching. The sacrificial Cr pattern is converted into a chemical pattern by first grafting a water-soluble polyethylene oxide brush onto the substrate, then wet etching the Cr, and finally grafting nonpolar polystyrene brushes. Assembling polystyrene-block-poly(methyl methacrylate) on these patterns results in structures oriented and registered with the underlying pattern, achieving 24 nm full-pitch resolutions. In conclusion, this approach has the potential to integrate MOR patterns into the DSA process, thereby enabling the generation of high-quality sub-10 nm patterns with high-χ BCPs.

Atomic force microscopy↗

Three-Dimensional Patterning of Nanoparticles by Molecular Stamping

Directing the formation of nanoscale architectures from nanoparticles is one of the key challenges in designing nanomaterials with prescribed functions. Atomic systems, given their ability to form molecules and crystals via directional chemical bonds, provide an inspiration for establishing approaches where nanoparticles with designed anisotropic binding modalities can be assembled into nanoscale architectures. However, fabricating such nanoparticles has been challenging due to their small dimensions and limited ways for site-specific control of their surface. To this end, we present a Molecular Stamping (MOST) approach to pattern DNA-coated nanoparticles with molecules at the predefined positions on a nanoparticle surface. This patterning is realized by use of a rigid and coordinative DNA frame as a molecular stamping apparatus (MOST App). The MOST App transfers multiple types of molecular “inks”, DNA sequences, onto nanoparticle surface and fixes these molecular inks into place to form a designed pattern. After a nanoparticle release from MOST App, it possesses single-molecule patches that can provide anisotropic bonds with distinctive affinities. We further use these stamped nanoparticles to assemble prescribed clusters, whose structure is determined by the locations of patches. Using electron microscopy and tomographic methods, we investigate the efficiency of cluster formation and the resulting spatial arrangements of nanoparticles. The presented approach provides a single-molecule and spatiallydetermined control over nanoparticle functionalization for creating nanoparticles with designed placement of different molecules and for realizing a rational fabrication of nanomaterial architectures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

RDPM: An Extensible Tool for Resilience Design Patterns Modelling

Resilience to faults, errors, and failures in extreme-scale high-performance computing (HPC) systems is a critical challenge. Resilience design patterns offer a new, structured hardware and software design approach for improving resilience. While prior work focused on developing performance, reliability, and availability models for resilience design patterns, this paper extends it by providing a Resilience Design Patterns Modeling (RDPM) tool which allows (1) exploring performance, reliability, and availability of each resilience design pattern, (2) offering customization of parameters to optimize performance, reliability, and availability, and (3) allowing investigation of trade-off models for combining multiple patterns for practical resilience solutions.

Kumar, Mohit↗

Design of a bifunctional TEMPO-tertiary amine mesoporous silica catalyst for the three-step cascade synthesis of a chromene derivative

A key challenge is design of materials and processes whereby competing reagents or conditions do not harm the multi-step sequence, thus allowing for more efficient chemical synthesis with elimination of work-up and separation steps. In this work, a three-step reaction cascade is performed using a porous bifunctional dimethylpropylamine-TEMPO-MCM41 catalyst, converting the commodity chemicals benzyl alcohol, sodium hypochlorite, and malononitrile to a biologically active anti-cancer, and anti-malarial 2-amino-chromene derivative. The cascade first utilizes a TEMPO-catalyzed oxidation of benzyl alcohol to benzaldehyde with NaOCl as the terminal oxidant. This is followed by a two-step, dual base catalyzed Knoevenagel condensation with malononitrile followed by a Michael addition with lawsone. Optimal conditions converting benzyl alcohol to 2-amino-5,10-dioxo-4-phenyl-5,10-dihydro-4H-benzo[g]chromene-3-carbonitrile include the delayed addition of malononitrile and lawsone during the three-step reaction sequence, which results in a 2-amino-chromene yield of over 80%. The importance of stepwise reagent addition is rationalized due to the unfavorable adsorption of acidic lawsone on the surface-grafted base catalyst. Tertiary Brønsted base sites of dimethylpropylamine outperform the more Lewis basic primary propylamine functionalized catalyst. This work outlines a simple and effective method for generating mesoporous materials with two types of active sites via co-condensation and thiol-ene coupling procedures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The use of gas chromatography – high resolution mass spectrometry for suspect screening and non-targeted analysis of per- and polyfluoroalkyl substances

This study is a workflow development for the analysis, identification, and categorization of per- and polyfluoroalkyl substances (PFAS) using gas chromatography-high resolution mass spectrometry (GC-HRMS) with non-targeted analysis (NTA) and suspect screening techniques. The behavior of various PFAS in a GC-HRMS was studied with regards to retention indices, ionization susceptibility, fragmentation patterns, etc. A custom PFAS database was constructed from 141 diverse PFAS. The database contains mass spectra from electron ionization (EI) mode, as well as MS and MS/MS spectra from positive and negative chemical ionization (PCI and NCI, respectively) modes. Common fragments of PFAS were identified across a diverse set of 141 PFAS analyzed. A workflow for suspect screening of PFAS and partially fluorinated products of incomplete combustion/destruction (PICs/PIDs) was developed which utilized both the custom PFAS database and external databases. PFAS and other fluorinated compounds were identified in both a challenge sample (designed to test the identification workflow) and incineration samples suspected to contain PFAS and fluorinated PICs/PIDs. The challenge sample resulted in a 100% true positive rate (TPR) for PFAS which were present in the custom PFAS database. In conclusion, several fluorinated species were tentatively identified in the incineration samples using the developed workflow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational design of closely related proteins that adopt two well-defined but structurally divergent folds

The plasticity of naturally occurring protein structures, which can change shape considerably in response to changes in environmental conditions, is critical to biological function. While computational methods have been used for de novo design of proteins that fold to a single state with a deep free-energy minimum [P.-S. Huang, S. E. Boyken, D. Baker, Nature 537, 320–327 (2016)], and to reengineer natural proteins to alter their dynamics [J. A. Davey, A. M. Damry, N. K. Goto, R. A. Chica, Nat. Chem. Biol.13, 1280–1285 (2017)] or fold [P. A. Alexander, Y. He, Y. Chen, J. Orban, P. N. Bryan, Proc. Natl. Acad. Sci. U.S.A. 106, 21149–21154 (2009)], the de novo design of closely related sequences which adopt well-defined but structurally divergent structures remains an outstanding challenge. We designed closely related sequences (over 94% identity) that can adopt two very different homotrimeric helical bundle conformations—one short (~66 Å height) and the other long (~100 Å height)—reminiscent of the conformational transition of viral fusion proteins. Crystallographic and NMR spectroscopic characterization shows that both the short- and long-state sequences fold as designed. We sought to design bistable sequences for which both states are accessible, and obtained a single designed protein sequence that populates either the short state or the long state depending on the measurement conditions. The design of sequences which are poised to adopt two very different conformations sets the stage for creating large-scale conformational switches between structurally divergent forms.

59 BASIC BIOLOGICAL SCIENCES↗

Fundamental studies of thermal and electrical transport in microporous metal-organic frameworks

In this work, we established porous metal-organic frameworks (MOFs) as designer conductors of electrons and ions relevant to fundamental research and technological applications. MOFs are porous, crystalline materials composed of organic linkers and inorganic nodes. While most MOFs are insulating with respect to ionic and electronic charge carriers, a number of exceptions have been reported in recent years. Electrically conductive MOFs are highly attractive for applications including electrical energy storage, chemiresistive sensing, and optoelectronics because of their high surface areas and tunable chemical properties. Ion-conducting MOFs are desirable for the synthetically tunable size, shape, and polarity of their pore environments, allowing for the tailored development of solid state electrolytes for metal-ion batteries. We developed systematic strategies for the design of MOFs that conduct ions and electrons. For each objective, we leveraged the versatile chemistry of these materials to obtain frameworks with targeted properties towards electronic or ionic charge carriers. We studied the factors that govern electrical transport in MOFs in order to gain fundamental knowledge of this emerging class of materials. We took several approaches to tackle this problem from multiple angles. Namely, we synthesized and characterized new frameworks, investigated post-synthetic modifications to enhance conductivity, and correlated theory and experiment to uncover new mechanistic findings. These results, which put forth new design principles for conductive MOFs, move the field toward one of the DOE Basic Energy Sciences Grand Challenges: to “design and perfect atom- and energy-efficient synthesis of revolutionary new forms of matter with tailored properties.” In addition to investigating the movement of electrons in MOFs, we also studied the movement of other charged species in MOFs, such as protons, lithium, and magnesium. Proton-conducting frameworks could be appealing materials for solid state electrolytes in fuel cells. In addition, they contain crystallographically defined proton-conducting channels, in contrast with state-of-the-art polymer membranes such as Nafion, which are amorphous. Controlling pore size and polarity in MOFs can thus shed light on proton and other ion transport mechanisms, ultimately enabling the design of more advanced electrolyte materials and potentially novel electrical energy storage materials.

36 MATERIALS SCIENCE↗

The interaction of wholesale electricity market structures under futures with decarbonization policy goals: A complexity conundrum

Competitive wholesale electricity markets can help facilitate energy system decarbonization by incentivizing investments in clean energy technologies that meet evolving system needs. We explore market structure impacts on generator operations and deployment by risk-averse, heterogeneous investor firms using the Electricity Markets and Investment Suite - Agent-based Simulation (EMIS-AS) model. Here we apply clean energy targets of 45%-100% by 2035 considering energy, ancillary services, capacity, and clean energy credit products and pricing and eligibility rules. Results highlight a complexity conundrum, whereby finding the "right" market design to achieve decarbonization goals and avoid unintended consequences can be a highly-nuanced, non-incremental challenge. Carefully designed energy-only markets can achieve the same clean energy targets as capacity market structures but with different revenue and profitability outcomes. Operating reserve demand curve-based scarcity pricing can substitute capacity markets for similar deployment outcomes. Carbon pricing alone is most effective at achieving decarbonization levels at low clean energy targets, and clean energy credit markets and carbon pricing are substitutionary at high clean energy targets. Restricting technology participation in capacity and operating reserve markets can impact deployment and operations, even for nonrestricted technologies. Adding an inertia product with fast frequency response yields insufficient provision at high clean energy targets, but work is needed to understand frequency requirements and capabilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

De novo design of small beta barrel proteins

Small beta barrel proteins are attractive targets for computational design because of their considerable functional diversity despite their very small size (<70 amino acids). However, there are considerable challenges to designing such structures, and there has been little success thus far. Because of the small size, the hydrophobic core stabilizing the fold is necessarily very small, and the conformational strain of barrel closure can oppose folding; also intermolecular aggregation through free beta strand edges can compete with proper monomer folding. Here, we explore the de novo design of small beta barrel topologies using both Rosetta energy–based methods and deep learning approaches to design four small beta barrel folds: Src homology 3 (SH3) and oligonucleotide/oligosaccharide-binding (OB) topologies found in nature and five and six up-and-down-stranded barrels rarely if ever seen in nature. Both approaches yielded successful designs with high thermal stability and experimentally determined structures with less than 2.4 Å rmsd from the designed models. Using deep learning for backbone generation and Rosetta for sequence design yielded higher design success rates and increased structural diversity than Rosetta alone. The ability to design a large and structurally diverse set of small beta barrel proteins greatly increases the protein shape space available for designing binders to protein targets of interest.

59 BASIC BIOLOGICAL SCIENCES↗

Wavelength Scaling of Widely-Tunable Terahertz Quantum-Cascade Metasurface Lasers

Terahertz (THz) external-cavity lasers based on quantum-cascade (QC) metasurfaces are emerging as widely-tunable, single-mode sources with the potential to cover the 1--6 THz range in discrete bands with milliwatt-level output power. By operating on an ultra-short cavity with a length on the order of the wavelength, the QC vertical-external-cavity surface-emitting-laser (VECSEL) architecture enables continuous, broadband tuning while producing high quality beam patterns and scalable power output. The methods and challenges for designing the metasurface at different frequencies are discussed. As the QC-VECSEL is scaled below 2 THz, the primary challenges are reduced gain from the QC active region, increased metasurface quality factor and its effect on tunable bandwidth, and larger power consumption due to a correspondingly scaled metasurface area. At frequencies above 4.5 THz, challenges arise from a reduced metasurface quality factor and the excess absorption that occurs from proximity to the Reststrahlen band. The results of four different devices — with center frequencies 1.8 THz, 2.8 THz, 3.5 THz, and 4.5 THz — are reported. Each device demonstrated at least 200 GHz of continuous single-mode tuning, with the largest being 650 GHz around 3.5 THz. The limitations of the tuning range are well modeled by a Fabry-Pérot cavity which accounts for the reflection phase of the metasurface and the effect of the metasurface quality factor on laser threshold. Lastly, the effect of different output couplers on device performance is studied, demonstrating a significant trade-off between the slope efficiency and tuning bandwidth.

47 OTHER INSTRUMENTATION↗

Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operationson Spatial Accelerators

To meet the extreme compute demands for deep learning across commercial and scientific applications, dataflow accelerators are becoming increasingly popular. While these“domain-specific” accelerators are not fully programmable like CPUs and GPUs, they retain varying levels of flexibility with respect to data orchestration, i.e., dataflow and tiling optimizations to enhance efficiency. There are several challenges when designing new algorithms and mapping approaches to execute the algorithms for a target problem on new hardware. Previous works have addressed these challenges individually. To address this challenge as a whole, in this work, we present an HW-SW co-design ecosystem for spatial accelerators called Union within the popular MLIR compiler infrastructure. Our framework allows exploring different algorithms and their mappings on several accelerator cost models. Union also includes a plug-and-play library of accelerator cost models and mappers which can easily be extended. The algorithms and accelerator cost models are connected via a novel mapping abstraction that captures the map space of spatial accelerators which can be systematically pruned based on constraints from the hardware, workload, and mapper. We demonstrate the value of Union for the community with several case studies which examine offloading different tensor operations (CONV/GEMM/Tensor Contraction) on diverse accelerator architectures using different mapping schemes.

Jeong, Geonhwa↗

Thermal Fluid Modeling Approaches in SAM for High Temperature Gas-Cooled Reactor Applications

This paper provides an overview of the unique modeling and simulation challenges and needs in the system and safety analysis of two common types of High Temperature Gas-cooled Reactor (HTGR) designs. The challenges are associated with the complex core geometry configurations and the change of the dominant heat removal mechanisms between normal operating conditions and decay heat removal transients. This requires that simulation tools utilize models with reasonable length scales and capture both the localized heat transfer and the core-scale heat transfer at the same time. To meet such analysis needs, different methodologies were developed. In conclusion, this includes adopting existing methods and further developing/improving them, as well as proposing innovative methods that leverage advanced computational frameworks such as the Multiphysics Object Oriented Simulation Environment (MOOSE).

HTGR↗

Carbon Fiber Oxidation in 4D

The oxidation of carbon fibers at high temperatures is the primary degradation process in the thermal protection system of many hypersonic flight vehicles. Predicting the rate and the extent of oxidation is critical to ensure a safe and effective design. An oversized thermal protection system adds unnecessary mass, while an under-designed one risks system failure and mission loss. Resolving high-temperature material degradation due to oxidation has been a long-standing challenge in designing for re-entry flight environments. Using time-resolved in situ X-ray microtomography, the oxidation of carbon fibers at high temperatures is directly imaged, resolving the two limiting degradation regimes: diffusion- and reaction-limited. The ability to resolve material degradation in time at the sub-micron scale sheds light on the ablation phenomenon and enables predictions of material constitutive properties evolving in time, with profound implications on the ability to model the aerothermal response of heat shield materials in hostile environments.

ablation↗

Center for Gas Separations (CGS)

The total energy consumption in the U.S. has been rising steadily for decades, and it currently amounts to ~98,000 TBtu/yr, with approximately 30% of this total attributable to the industrial sector. Reasonable estimates indicate that 45–55% of total industry energy consumption derives from chemical separations, and for example, over 120 TBtu/yr alone is used in carrying out olefin/paraffin separations via energy-intensive cryogenic distillation. Therefore, the pursuit of new, even radically different approaches to some of the most energy-intensive industrial separations processes is an imperative scientific pursuit for reducing energy consumption toward a more sustainable future. Adsorbent and membrane-based separations can require a fraction of the energy needed for distillation methods, and as such are considered promising solutions for balancing increasing energy demand in the U.S. with the need for a massive reduction in energy consumption. Although considerable research effort has been devoted to the design of materials capable of carrying out various gas separations, usually operating through size-selective, chemisorptive, or physisorptive mechanisms, it remains a great challenge to design materials that function adequately for real-world applications. Indeed, the chemical and physical differences between molecules in gas mixtures of interest are often small, and therefore it is necessary, through the use of nanoscience and synthetic chemistry, to engineer unprecedented molecular-level control in adsorbate–adsorbent interactions. The overarching mission of the Center for Gas Separations (CGS) was to discover fundamental innovations that have the potential to dramatically reduce the energy associated with critical gas separations. In particular, the CGS developed novel synthetic routes, guided by molecular chemistry principles, as well as advanced characterization and computational methods, that have enabled the discovery of new materials and membranes tailor-made to exhibit exceptional performance for a range of gas separations processes, as required in the clean use of fossil fuels and in reducing CO 2 emissions from industry. A challenge of this magnitude required the collaboration and synergy of a large team of researchers with expertise in materials synthesis, characterization, and computations. During the 11-year project period, the CGS created a range of new materials within the family of highly-tunable, porous solids known as metal–organic frameworks (MOFs). These new frameworks demonstrate novel mechanisms for key industrial gas separations, including revolutionary new cooperative adsorption processes that enable low-energy CO 2 and CO capture, and are capable of efficiently separating olefins from paraffins, O 2 from air, and the shape-selective separation of alkane isomers. In addition, the CGS developed new strategies for incorporating these materials into composite membranes toward highly efficient and selective membrane-based separations. As a testament to the success of the CGS, two start-up companies, Mosaic Materials,4 Inc. and Flux Technology, Inc., grew out of these research efforts, and these companies are seeking to commercialize MOF and composite membranes materials for key separations in industry, including large-scale CO 2 capture and hydrocarbon separations, respectively. Another company, framergy, Inc., licensed IP resulting from CGS research toward the commercialization of adsorbents for various energy-relevant applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗