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At least 127 records · Page 7

Selective Sorbent Design: CaS Aerogel for Rapid Remediation of Aqueous Pb (II)

Heavy metals are a persistent environmental problem due to their high toxicity, even at very low concentrations (parts per billion, ppb). The removal of such diluted heavy metals is challenging because of the competition the counterions (Ca 2+ , Na + , Mg 2+ , etc.) present in natural water bodies. The design of sorbents capable of removing ions below the action limit (15 ppb for Pb 2+ ) requires a strong driving force for selective uptake and rapid removal. In this work, we report the synthesis of porous CaS aerogels (surface area = 143.6 m 2 /g) by oxidative assembly of CaS nanoparticles and describe their use in selective Pb 2+ ion remediation from water. Despite the presence of amorphous CaCO 3 (up to 50 wt %) in the gel network, the gels demonstrated a capacity of 17.1 mmol Pb/g aerogel (3543 mg/g), and this could be augmented to 22.5 mmol Pb/g aerogel (4593 mg/g) by modifying the synthesis to reduce CaCO 3 content to ca. 15 wt %. Moreover, the selectivity of CaS aerogels toward Pb 2+ ions is high, as evidenced by little-to-no change in the distribution constant (K d ∼ 10 4 ) in the presence of competing ions (1 M) such as Na + , Mg 2+ , and Ca 2+ . During remediation with low concentrations (100 ppb) of Pb 2+ with CaS aerogels, the level of Pb 2+ dropped to 5.4 ppb (below the 15 ppb EPA limit) within 1 h with a 95.4% removal efficiency. In contrast to the CO 2 supercritically dried aerogels, lower surface area ambient dried gels (xerogels) only remove 40% of the lead ions from a 100 ppb solution, saturating within 1 h. The efficiency and rapidity of selective Pb 2+ uptake using CdS aerogels arise from a combination of a strong thermodynamic driving force for cation exchange (K eq = 2.5 × 10 27 ) and chemisorption along with favorable kinetics associated with the high surface area porous architecture. These results show that formation of high surface area metal chalcogenide aerogels by oxidative assembly to form nanocrystalline architectures, as previously demonstrated for II−VI and IV−VI semiconductors, can be extended to the more highly ionic alkaline earth sulfides.

Aerogels↗

High-Current Density Durability of Pt/C and PtCo/C Catalysts at Similar Particle Sizes in PEMFCs

The durability of carbon supported PtCo-alloy based nanoparticle catalysts play a key role in the longevity of proton-exchange membrane fuel cells (PEMFC) in electric vehicle applications. To improve its durability, it is important to understand and mitigate the various factors that cause PtCo-based cathode catalyst layers (CCL) to lose performance over time. These factors include i) electrochemical surface area (ECSA) loss, ii) specific activity loss, iii) H + /O 2 -transport changes and iv) Co 2+ contamination effects. We use a catalyst-specific accelerated stress test (AST) voltage cycling protocol to compare the durability of Pt and PtCo catalysts at similar average nanoparticle size and distribution. Our studies indicate that while Pt and PtCo nanoparticle catalysts suffer from similar magnitudes of electrochemical surface area (ECSA) losses, PtCo catalyst shows a significantly larger cell voltage loss at high current densities upon durability testing. The distinctive factor causing the large cell voltage loss of PtCo catalyst appears to be the secondary effects of the leached Co 2+ cations that contaminate the electrode ionomer. A 1D performance model has been used to quantify the cell voltage losses arising from various factors causing degradation of the membrane electrode assembly (MEA).

08 HYDROGEN↗

Corn stover‐derived porous carbon for asymmetric supercapacitors

In this investigation, hydrothermal liquefaction‐derived hydrochar from pulverized corn stover (avg. particle size 1.12 mm and ash content 6.75 wt%) is chemically activated with aqueous KOH in the presence of Pluronic F127 surfactant and thermally treated further up to 800°C to generate porous carbon (POC) with higher specific surface area and porosity. POC obtained under different processing conditions is thoroughly characterized by Brunauer‐Emmett‐Teller surface area analyzer, Fourier transform infrared spectroscopy, Raman spectroscopy, scanning electron microscopy, and transmission electron microscopy. Metallic impurity present in POC is characterized by inductively coupled plasma mass spectrometry. Higher specific surface area POC is observed with the use of the surfactant during the activation process. Fully characterized POC is used with (Mn, Ti)‐mixed oxide electrode to fabricate asymmetric supercapacitor (ASC). Specific capacitance of ASC is measured by cyclic voltammetry (CV) technique using Gamry G‐300 potentiostat/galvanostat/ZRA. CV plots are obtained with different voltage scan rates whereas galvanostatic charge‐discharge plots are studied by varying the current density. Renewable corn stover‐derived POC prepared using Pluronic F127/KOH activation method is found to be highly suitable as an electrode material because of higher capacitance and electrochemical stability over 100 charging‐discharging cycles.

25 ENERGY STORAGE↗

The effects of sequential hydrothermal-mechanical refining pretreatment on cellulose structure changes and sugar recoveries

The recalcitrance of lignocellulosic biomass necessitates an efficient pretreatment protocol for operating a successful cellulosic biorefinery. It is critical to improve cellulose accessibility for hydrolysis and fermentation by altering the plant cell wall’s physical structure and chemical composition. Sequential hydrothermal-mechanical refining pretreatment (HMR) allows efficient recovery of cellulosic sugars without utilizing any hazardous chemicals. HMR has been successfully applied to Liberty switchgrass, a bioenergy cultivar released by the USDA, and now it is being applied to oilcane, a recently developed transgenic sugarcane variety engineered to accumulate lipids in its vegetative tissues. Sugar yields of oilcane bagasse (OCB) and switchgrass (SG) treated with HMR are 96.4% and 75.4%, respectively. This study sought to correlate cellulosic sugar yields with structural changes within the cell wall caused by HMR on two distinct bioenergy crops. Simon’s staining technique for the specific surface area analysis showed that HMR increased the specific surface area of pretreated biomass residues by 80–112%. In addition, ATR-FTIR was performed to determine the effects of HMR on physical structures based on the total crystallinity index (TCI) and hydrogen bonding intensity (HBI). Irrespective of biomass type, HMR decreased the initial crystalline cellulose contents of untreated biomass residues by 3.5% and reduced TCI and HBI by 7–13%. Here, the study found that sugar yields were negatively correlated to reducing values of hydrogen bonding intensity, crystalline cellulose content, and total crystallinity index.

09 BIOMASS FUELS↗

Tailored mesoporous structures of lignin-derived nano-carbons for multiple applications

This work uses a one-step KOH activation for lignin precursors to produce ultra-high mesoporous activated carbons (ACs) with an unprecedented combination of the surface area of 3207 m 2 g -1 and mesopore ratio of 76%. The ACs are applied for supercapacitors (SCs) and methylene blue (MB) adsorption. The capacitance of the SCs in the three-electrode system reaches 812.3 F g -1 and demonstrates a remarkable maximum MB adsorption capacity of 1250 mg g -1 . By modifying the process conditions, the mesopore ratio of ACs could be controlled from 10% to 80%. Compared with one-step activation, a two-step method produced microporous carbons with a lower surface area of 1227 m 2 g -1 and a high micropore ratio of 73%. The capacitance of SCs with two-step ACs reached 228.1 F g -1 and the maximum adsorption capacity of 476.19 mg g -1 for MB adsorption. The two-step method limited the surface area but had a higher oxygen surface functionality, benefiting its electrochemical performance. A techno-economic analysis reveals that the one-step KOH activation-based process develops ACs with a minimum selling price of $7648/ton. In conclusion, this work demonstrates tuning the processing-structure-property-performance relationship of lignin-based ACs to make an economically viable domestic carbon source.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of Engineered Form MOFs CaSDB and HKUST-1

Idaho National Laboratory (INL) and Pacific Northwest National Laboratory (PNNL) have studied different sorbents for the purpose of separating krypton (Kr) and xenon (Xe). PNNL has researched various metal-organic frameworks (MOFs) that have characteristics theoretically suitable for the separation. Based on computational analysis, PNNL chose Calcium–4,4’–sulfonyl dibenzoate (CaSDB) and Hong Kong University of Science and Technology MOF1 (HKUST–1). The raw MOFs are supplied in a powder form and must be incorporated into a robust engineered form to be viable for gas separation. In 2016, PNNL produced an engineered form of CaSDB by compressing and grinding the raw MOF material. This form was sent to INL for adsorption testing. Gentle mechanical agitation of the compressed form produced a large amount of powder, resulting in the conclusion that the form was not viable for the application. In 2019, INL successfully produced two engineered forms, CaSDB–EF1 and HKUST–EF2, by incorporating the active MOF powders into a polyacrylonitrile (PAN) binder. PNNL also produced two engineered forms, CaSDB–10pmma and HKUST–10pmma, by using polymethyl methacrylate (PMMA) as a binder. Surface area analysis indicated that the forms could be viable for separations in which the CaSDB–EF1 retained 84% of the raw CaSDB surface area and CaSDB–10pmma retained 48%. HKUST–EF2 retained all the raw HKUST–1 surface area, whereas HKUST–10pmma retained only 28%. Mechanical stability testing demonstrated that the PMMA forms formed a fine powder whereas, the PAN forms did not. In general, adsorption testing showed that CaSDB–10pmma had a lower Xe breakthrough capacity than CaSDB–EF1, but a higher saturation capacity at both room temperature and at 253 K. The CaSDB MOF was intended to be used as a room temperature sorbent to capture Xe. However, both CaSDB engineered forms displayed relatively short initial break through times. Reduced temperature increased the Xe capacity of both engineered forms. HKUST–1 was expected to be effective only at sub-zero temperatures. At 195 K, HKUST–10pmma had an initial Xe breakthrough capacity of 119 mmol/ kg, compared to HKUST–EF2 at 339 mmol/ kg. The saturation capacities were 275 and 383 mmol/ kg, respectively. HKUST–10ppm also had a lower Kr capacity of 1.7 mmol/kg, whereas the HKUST–EF had a Kr capacity of 3 mmol/ kg. Test results indicate that the PAN engineered forms are a more suitable choice for the complete separation of Xe and Kr, due to the increase in initial breakthrough capacity. CaSDB allows rapid breakthrough of Kr and Xe regardless of the type of engineered form. At 253 K, it is more viable, but is still not the most effective sorbent. HKUST–EF2 demonstrated viability for Xe capture at 195 K, which may merit further study, however it may be cost prohibitive.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Parametric Study of the Influence of Support Type, Presence of Platinum on Support, and Ionomer Content on the Microstructure of Polymer Electrolyte Fuel Cell Catalyst Layers

We report Ultra-small angle X-ray scattering (USAXS) was employed to investigate the effects of carbon support type, the presence of platinum on carbon, and ionomer loading on the microstructure of polymer electrolyte fuel cell (PEFC) catalyst layers (CLs). Particle size distributions (PSDs), obtained from fitting the measured scattering data were used to interpret the size of carbon aggregates (40–300 nm) and agglomerates (>400 nm) from two-component carbon/ionomer and three-component platinum/carbon/ionomer CLs. Two types of carbon supports were investigated: high surface area carbon (HSC) and Vulcan XC-72. CLs with a range of perfluorosulfonic acid (PFSA) ionomer to carbon (I/C) ratios (0.2–1.2) and also with perfluoroimide acid (PFIA) ionomer were studied to evaluate the effect of ionomer on CL microstructure. The carbon type, the presence of platinum, and ionomer loading were all found to significantly impact carbon agglomeration. The extent of Pt/C agglomeration in the CL was found to increase with increasing ionomer and platinum concentration and to decrease with increasing carbon surface area. Platinum electrochemically-active surface area (ECSA) and local oxygen transport resistance (R nF ) were correlated to the CL microstructure to yield relationships affecting electrode performance.

25 ENERGY STORAGE↗

A Three–Dimensional Nanoscale View of Electrocatalyst Degradation in Hydrogen Fuel Cells

The loss of platinum (Pt) electrochemically active surface area (ECSA) is a critical degradation mode that often becomes a limiting factor for heavy-duty proton exchange membrane fuel cell vehicles. High surface area carbon supports have been shown to improve Pt dispersion and limit detrimental ionomer-electrocatalyst interactions due to their large interior pore volume. Here, in this work, using automated scanning transmission electron tomography, the degradation of nanoparticles located on the interior versus exterior surfaces of the carbon support is compared following a catalyst-specific accelerated stress test (AST) of 90,000 voltage cycles between 0.6 V to 0.95 V. The results reveal a notable increase in median particle size for both interior and exterior Pt catalyst particles, with a slightly higher increase in particle size distribution and loss of specific surface area for the particles located on the exterior carbon surface. The fraction of Pt nanoparticles that reside within the interior of the carbon support also increased following the AST test, accompanied by evidence of an increase in average carbon mesopore size. Here, the results shed light on the degradation mechanisms affecting electrochemical properties and the enhanced particle accessibility at lower relative humidity.

08 HYDROGEN↗

Indirect electrochemical method for high accuracy quantification of protein adsorption on gold surfaces

We demonstrate the use of copper underpotential deposition (UPD) for measurement of the electrochemically active surface area of a protein-modified gold electrode. The kinetics of adsorption and the subsequent structural rearrangement of β-casein, as a model protein, on the surface of a gold electrode have been followed over time. The protein-free surface area was determined by measuring the charge derived from UPD copper deposition on the non-blocked surface area at different stages of adsorption. The behaviour of β-casein adsorption as a function of surface roughness and the microstructure of the gold electrode, as well as the concentration of the protein solution, are studied using this method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Air Dehumidification using Ionic Liquid-Based Fiber Bundle Membrane Contactor

Air dehumidification is essential since excess moisture in the buildings causes discomfort to the occupants, encourages the production of air pathogens such as mold or mildew, and causes corrosion and rotting that degrade building materials. Existing moisture removal processes are mainly focused on condensation and desiccant (liquid or solid) techniques with direct contact between air and desiccant. However, these methods are energy-intensive, or desiccant might be lost or cause corrosion in the process. The main objective of this study is to investigate an ionic liquid-based liquid desiccant absorber based on a membrane fiber bundle. The novel system consists of membrane contactors containing bundles of 10,000 polypropylene fibers. The fiber bundles have 0.3 micron diameter, with ionic liquid flowing inside, and air flowing outside. The fibers provide a high contact area among phases: 1.4 m2 contact surface area in a 0.00015 m3 volume. The ionic liquid as a sorbent stipulates the selectivity for air, prevents the loss of solvent in the operation due to negligible volatility, provides fast diffusion due to low viscosity compared to common ionic liquids, and has high affinity and solubility in water. The dehumidification capacity of the membrane technology was experimentally investigated. The experimental results show that the ionic-liquid based membrane system can effectively remove excess moisture from the air. The novel fiber bundle dehumidification system has a system volume of 0.00798 m3 (7.98 L) and active heat and mass transfer surface area of 8.4 m2. It achieved an average dehumidification of 320 ± 25 W with a volumetric air flowrate of 3.1 m3/min (108 ft3/min).

Turnaoglu, Tugba↗

Atomic Layer Deposition Overcoating Improves Catalyst Selectivity and Longevity in Propane Dehydrogenation

Propylene, a precursor for commodity chemicals and plastics, is produced by propane dehydrogenation (PDH). An increase in PDH yield via added catalyst activity, lifetime, or selectivity represents significant energy and economic savings. Using Pt dispersed on Al2O3 extrudate supports as a commercially relevant model system, we demonstrate that atomic layer deposition (ALD) metal oxide overcoats, used to tailor metal-active sites, can increase PDH yield and selectivity. We investigate the interplay of Pt loading, ALD overcoat thickness, and Al 2 O 3 support surface area on PDH activity, selectivity, and catalyst stability to show that applying a 6-8 A thick layer of Al 2 O 3 on low-surface area Al 2 O 3 supports of similar to 90 m 2 /g surface area yields the optimal combination of stability and activity, while increasing propylene selectivity from 91 to 96%. Increased stability upon steaming deactivation occurs because the Al 2 O 3 overcoat prevents the Pt nanoparticles from sintering. We speculate that the ALD overcoat selectively binds to the undercoordinated sites on the Pt nanoparticles, while leaving the more selective terrace sites available for dehydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Production of Carbon Nanomaterials and Sorbents from Domestic U.S. Coal (Final Report)

The main goal of this project was to produce high-value carbon nanomaterials and carbon sorbents from domestic coal resources in a cost-effective manner. Four types of domestic coal samples were processed through a combination of deashing, devolatilization, oxidation, reduction, and activation treatments to produce graphene oxide (GO), reduced graphene oxide (RGO), and activated carbon (AC). The precursors and developed materials were extensively characterized by various methods to investigate the impact of the coal feedstock type on the yield and quality of each product. A commercial graphite-based GO sample was included in the experimental work as the baseline material for comparison with the coal-based materials developed in this work. The performed work also included a technoeconomic analysis and cost estimation for a plant processing 20 tons/day coal, a market evaluation for the graphene materials, and a technology gap analysis. A simple process by concentrated nitric acid oxidation is used to oxidize coal precursors for the production of GO. Fine oxidized coal particles that were separated from larger oxidized coal particles had significantly higher oxygen contents and were identified as coal-based GO samples. Coarse oxidized coal particles were used as precursors for production of AC. Based on the Raman spectroscopy results, coal-based GO samples exhibited G and D bands similar to those of graphite-based GO samples. X-ray photoelectron spectroscopy revealed that coal-based GO samples had surface oxygen contents of ~26-35% that were higher than the oxygen contents of graphite-based GO samples. Larger particles of oxidized coal samples were activated under different conditions to produce high surface area functionalized AC. Prepared materials had surface areas exceeding 1,500 m 2 /g and pore volumes more than 1 cm 3 /g with different pore size distributions. Reduced graphene oxide samples were prepared by thermal reduction of both coal-based and graphite-based GO samples at 170-2800 ºC. Coal-based and graphite-based RGO samples exhibited similar carbon contents, Raman spectra, and XRD profiles. Heat treatment above 1500 ºC shifted RGO to synthetic graphite. Among anthracite, bituminous, subbituminous, and lignite coals tested, anthracite was the best precursor to produce carbon nanomaterials exhibiting properties similar to those of graphite-based materials. Anthracite-based carbon nanomaterials also had the highest production yields. Technoeconomic analysis estimated the production cost of GO and RGO for anthracite-based samples at about 2,600 and 4,200 $/ton, respectively, which is about two orders of magnitude lower than the current estimated price of graphite-based materials. Several gaps to further develop the proposed technology were identified and discussed that include process and equipment optimization, process integration, need for additional bench- and pilot-scale experiments, and other items to reduce the scale up risk. Market analysis reports suggested a compound annual growth rate of 40% for graphene and related materials. Short-term applications include composites, inks, and coatings. However, energy storage applications appear to be the dominant potential long-term applications. Different applications of coal-based GO and RGO need to be explored and clear metrics and standards for each application need to be developed.

01 COAL, LIGNITE, AND PEAT↗

Compact heat exchanger with alternating fluid channels

A compact heat exchanger is provided, in which multiple streams can flow within the same layer or layers, and different fluids may flow in alternating channels within the same layer as well as flowing in alternating layers. Having fluids in alternating channels—as compared to only alternating layers within the same layer—increases the direct surface area between the fluids (the primary surface area) for heat transfer, thereby increasing the rate and efficiency of heat transfer. Methods of making and using the heat exchanger are also provided.

Gadalla, Hani Ahmed↗

Particle emissions from mobile sources: Discussion of ultrafine particle emissions and definition

There is no universally agreed upon definition for ultrafine particles (UFP). Commonly used definitions for UFP are either particle number below 100 nm or total particle number, but without an agreed upon lower cut point. For example, a lower cut point of 3 nm compared to 10 nm could result in a substantially higher count. Another definition for UFP is total particle mass but without a commonly agreed upon aerodynamic diameter upper cut point, e.g., below 100 nm, 200 nm, 300 nm, etc. Yet another definition is lung deposited surface area weighted by lung deposition fraction, found mainly in the particle mobility diameter range from 20 to 400 nm. It is clear from these definitions that there are inconsistencies in the way UFP is used and defined in the literature. Sometimes these metrics are well correlated, sometimes not. In this paper we suggest three exposure metrics: UFP-N, UFP-M, and UFP-S, that we believe will add clarity. These metrics represent total number, mass, and surface area below 500 nm, respectively. For surface area and mass, the 500 nm cut point can be either aerodynamic or mobility diameter depending upon measurement methodology. For all metrics, this cut point captures nearly all of the primary particle emissions from mobile sources. Furthermore, UFP-N would include a lower cut point of 3–6 nm and would not require an upper size cut point because there is very little particle number above 500 nm or even above 100 nm. Thus, our definition of UFP-N is consistent with the current definition of ultrafine number except for, importantly, the specification of a lower cut point. These exposure metrics can help facilitate consistency in the characterization of both short- and long-term UFP ambient exposures and associated health effects in epidemiological studies.

42 ENGINEERING↗

Reformulated Red mud: a robust catalyst for in situ catalytic pyrolysis of biomass

Biomass feedstocks contain inorganic compounds generally classified as ash. The ash consists of compounds of potassium, calcium, magnesium, silicon, phosphorous and other elements. These elements have been reported to influence both the pyrolysis reactions as well as destabilizing the pyrolysis oils during storage. The inorganic elements have also been reported to deposit on catalyst surfaces during in situ catalytic pyrolysis leading to the eventual deactivation of acidic catalysts such as zeolites. The deposition of inorganic elements and their effect on formulated red mud (FRM) catalyst during in situ catalytic pyrolysis of pinyon juniper wood was investigated. The inorganic elements were measured for the fresh, coked, and regenerated catalysts. The BET specific surface area of the FRM catalyst decreased from 76 m2/g for the fresh catalyst to 53 m2/g for the stable regenerated catalyst. After three regenerations, the BET specific surface area stabilized at 53 m2/g and remained constant after all other regenerations. Potassium, calcium, magnesium, and phosphorous were deposited on the catalyst. Potassium deposition was linear with the number of regenerations while magnesium and calcium depositions were initially rapid but leveled off after three regenerations of the catalyst. Phosphorous deposition was almost linear, but the data were more scattered compared to potassium. The potassium deposition was attributed to physical phenomenon whereas calcium and magnesium depositions were more akin to chemical reactions related to the loss of BET surface area of the catalyst. The deposition of these elements on the surface of the catalyst did not deactivate it. After each catalyst regeneration, the oil yield was not significantly affected and the oil oxygen content and viscosity decreased slightly. This clearly showed that formulated red mud is a robust catalyst suitable for in situ catalytic fast pyrolysis of biomass.

Agblevor, Foster↗

Are you using the right probe molecules for assessing the textural properties of metal–organic frameworks?

Textural properties—such as the surface area, pore size distribution, and pore volume—are at the forefront of characterization for porous materials. Therefore, it is essential to accurately and reproducibly report a material's textural properties as they could ultimately dictate its applicability. This work aims to provide insightful and comprehensive studies of textural properties for a set of metal–organic frameworks (MOFs), a class of porous materials, using various gases to equip researchers in the field with a helpful guide and reference. Here, we selected a series of nine MOFs with different surface areas, pore sizes, shapes, and chemical environments to represent a wide range of materials. We probed the textural properties of these MOFs using traditional and distinctive gases: N 2 , Kr and O 2 at 77 K, Ar at 87 K, and CO 2 at 195 and 273 K. With regard to surface area, we discuss the validity and challenges associated with the current BET method, the importance of utilizing the Rouquerol et al. consistency criteria to ensure accuracy and reproducibility, and the recommended gas probes for certain materials. For pore size distribution, we discuss the efficacy of each probe for determining the pore sizes within a porous material relative to the calculated distribution from its crystal structure, the limitations of current computational kernels used to calculate pore size distributions, and the need for advanced kernels to envelope the diversity of porous materials. Finally, for pore volume, we discuss the use of the Gurvich rule to obtain the total pore volume in comparison with calculated values from crystal structures and its consistency as a metric for porous materials. Ultimately, we hope that this article will aid researchers in characterizing the textural properties of porous materials and encourage the development of new kernels capable of encompassing the complexity of MOFs and other porous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

Abstract Nanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well‐established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal‐organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high‐throughput, non‐destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

Fricke, Sophia N.↗

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

Abstract Nanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well‐established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal‐organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high‐throughput, non‐destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗