Implementation of a Core–Shell Design Approach for Constructing MOFs for CO 2 Capture
Not Available
36 MATERIALS SCIENCE↗
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Effect of Diel Cycling Temperature, Relative Humidity, and Synthetic Route on the Surface Morphology and Hydrolysis of α -U 3 O 8
The speciation and morphological changes of α-U 3 O 8 following aging under diel cycling temperature and relative humidity (RH) have been examined. This work advances the knowledge of U-oxide hydration as a result of synthetic route and environmental conditions, ultimately giving novel insight into nuclear material provenance. α-U 3 O 8 was synthesized via the washed uranyl peroxide (UO 4 ) and ammonium uranyl carbonate (AUC) synthetic routes to produce unaged starting materials with different morphologies. α-U 3 O 8 from UO 4 is comprised of subrounded particles, while α-U 3 O 8 from AUC contains blocky, porous particles approximately an order of magnitude larger than particles from UO 4 . For aging, a humidity chamber was programmed for continuous daily cycles of 12 “high” hours of 45 °C and 90% RH, and 12 “low” hours of 25 °C and 20% RH. Samples were analyzed at varying intervals of 14, 24, 36, 43, and 54 days. At each aging interval, crystallographic changes were measured via powder X-ray diffraction coupled with whole pattern fitting for quantitative analysis. Morphologic effects were studied via scanning electron microscopy and 12-way classification via machine learning. While all samples were found to have distinguishing morphologic characteristics (93.2% classification accuracy), α-U 3 O 8 from UO 4 had more apparent change with increasing aging time. Nonetheless, α-U 3 O 8 from AUC was found to hydrate more quickly than α-U 3 O 8 from UO 4 , which can likely be attributed to its larger surface area and porous starting material morphology.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Time-resolved in situ visualization of the structural response of zeolites during catalysis
Zeolites form an important class of materials that are widely used in various fields. Their unique properties come primarily from their size, shape, and connectivity of their sub-nm crystalline voids, the Si/Al ratio of the anionic framework, and the number and the nature of charge-balancing cations.The inhomogeneous distribution of the Si/Al ratio within crystals, and hence the cation density, the presence of organic residues, and their inhomogeneous distribution within crystals sensitively affect their performances because these factors influencethe intra-crystalline diffusion rates of the reactants and products. However, the information regarding these inhomogeneities in zeolite crystals cannot be obtained by conventional analytical tools because they only provide information regardingthe average properties of zeolite crystals. Here we employin situX-ray free electron laser-based time-resolved coherent X-ray diffraction imaging to investigate the internal deformations originating from the inhomogeneous Cu ion distributions in Cu-exchanged ZSM-5 zeolite crystals during the deoxygenation of nitrogen oxides with propene. We show that the interactions between the reactants and the active sites lead to an unusual strain distribution,which is confirmed by density functional theory simulations. Moreover, this elucidates the factors responsible for distinct active regions,which are essential to maximizing some applications with enhanced performances. These observations provide insights into the role of structural inhomogeneity in zeolites during a catalytic processand will assist the future design of zeolites for their applications.
36 MATERIALS SCIENCE↗
Tailored polyMOFs for ion transport in lithium-based battery electrolyte
Owing to their low flammability, solid-state and quasi-solid-state electrolytes are safer alternatives to liquid organic electrolytes for energy storage applications. Metal–organic frameworks (MOFs), with facile functional tunability, long-range order, and rich host–guest interactions, have been implemented as electrolyte materials in a wide range of energy storage applications. In this work, we investigate a class of MOFs called polyMOFs as quasi-solid-state electrolyte materials. Unlike MOF–polymer composites, which are physical mixtures of MOF particles and polymers, polyMOFs are composed of polymeric linkers and metal ion nodes that self-assembled into crystalline and porous framework materials. PolyMOFs thus marry the ionic transport properties of liquid electrolyte and polymers with the synthetic versatility and host–guest interactions of MOFs. We demonstrate that the functionality of the polymer backbone of the polyMOF linker can improve room-temperature ion transport in the material. The polyMOF based on poly(ethylene glycol) (PEG) exhibits greater ionic conductivity, lithium transference number, and lower activation energy than its polyethylene (PE) analog. Supported by solid-state 7 Li nuclear magnetic resonance spectroscopy, we propose these improvements are due to stronger coordination of Li + to oxide sites in PEG, allowing for dissociation of Li and its associated anion. DFT studies further reveal that the confined solvent molecule mediates Li + transport in PEG-functionalized UiO-66 via a metastable adsorption and hopping mechanism. This work lies at the interface of inorganic and polymer electrolytes, unveiling fundamental insights into the design of next-generation ion conductive materials for energy technologies.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Ultradynamic Isoreticularly Expanded Porous Organic Crystals
Porous organic materials showcasing large framework dynamics present new paths for adsorption and separation with enhanced capacity and selectivity beyond the size-sieving limits, which is attributed to their guest-responsive sorption behaviors. Porous hydrogen-bonded crosslinked organic frameworks (H C OFs) are attractive for their remarkable ability to undergo guest-triggered expansion and contraction facilitated by their flexible covalent crosslinkages. However, the voids of H C OFs remain limited, which restrains the extent of the framework dynamics. Here in this work, we synthesized a series of H C OFs characterized by unprecedented size expansion capabilities induced by solvents. These H C OFs were constructed by isoreticularly co-crystallizing two complementary sets of hydrogen bonding building blocks to generate porous molecular crystals, which were crosslinked through thiol–ene/yne single-crystal-to-single-crystal transformations. The generated H C OFs exhibit enhanced chemical durability, high crystallinity, and extraordinary framework dynamics. For instance, H C OF-104 crystals featuring a pore diameter of 13.6 Å expanded in DMF to 300 ± 10% of their original lengths within just 1 min. This expansion allows the HCOFs to adsorb guest molecules that are significantly larger than the pore sizes of their crystalline states. Through methanol-induced contraction, these large guests were encapsulated in the fast-contracted H C OFs. These advancements in porous framework dynamics pave the way for new methods of encapsulating guests for targeted delivery.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Fine Tuning the Pore Surface in Zirconium Metal–Organic Frameworks for Selective Ethane/Ethylene Separation
Not Available
36 MATERIALS SCIENCE↗
Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks
Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an end-to-end machine learning model that automatically generates descriptors that capture a complex representation of a material’s structure and chemistry. This approach builds on computational topology techniques (namely, persistent homology) and word embeddings from natural language processing. It automatically encapsulates geometric and chemical information directly from the material system. We demonstrate our approach on multiple nanoporous metal–organic framework datasets by predicting methane and carbon dioxide adsorption across different conditions. Our results show considerable improvement in both accuracy and transferability across targets compared to models constructed from the commonly-used, manually-curated features, consistently achieving an average 25–30% decrease in root-mean-squared-deviation and an average increase of 40–50% in R 2 scores. A key advantage of our approach is interpretability: Our model identifies the pores that correlate best to adsorption at different pressures, which contributes to understanding atomic-level structure–property relationships for materials design.
97 MATHEMATICS AND COMPUTING↗
Hybrid Mesoporous Carbon/Copper Ferrite Electrode for Asymmetric Supercapacitors
Asymmetric supercapacitors (ASCs) with two dissimilar electrodes are known to exhibit relatively moderate energy and power densities. If electrodes derived from earth-abundant materials or renewable resources such as lignocellulosic biomass (LCB) are used for fabrication, energy storage systems are expected to become less expensive and more sustainable. Hybrid electrode materials have advantages such as higher surface area, better chemical stability, and superior energy density. This study reports on the synthesis of a novel hybrid electrode material containing porous carbon (POC) and copper ferrite, which is designated as POC@Cu-ferrite, and its electrochemical performance in ASC configuration. Corn stover derived hydrochar is utilized for the sol–gel synthesis of POC@Cu-ferrite hybrid material using earth-abundant Cu and Fe-based precursors. This material is characterized using X-ray diffraction (XRD), Raman spectroscopy, Brunauer–Emmett–Teller (BET) surface area analyzer, and scanning and transmission electron microscopy (SEM/TEM). As-synthesized Cu-ferrite is found to contain 89.2% CuFe 2 O 4 and 10.8% Fe 2 O 3 , whereas other phases such as Fe 3 O 4 , CuFeO 2 , and CuO are observed for the POC@Cu-ferrite. BET-specific surface area (SSA) and pore volume of POC@Cu-ferrite are observed as 1068 m 2 /g and 0.72 cm 3 /g, respectively. POC@Cu-ferrite hybrid electrode is used with POC opposite electrode to fabricate ASC, which is tested using Gamry G-300 potentiostat/galvanostat/ZRA to obtain cyclic voltammetry (CV) profiles and galvanostatic charge–discharge (GCD) plots. ASC is also prepared using Cu-ferrite and POC materials and its specific capacitance and stability are compared with ASCs prepared with POC@Cu-ferrite and POC or graphene nanoplatelets (GNPs) electrodes. POC@Cu-ferrite hybrid electrode is found to be superior with a 2-fold higher capacitance and significant electrochemical stability over 100 GCD cycles as compared to the Cu-ferrite electrode.
36 MATERIALS SCIENCE↗
Assembling Si 2 BN nanoribbons into a 3D porous structure as a universal anode material for both Li- and Na-ion batteries with high performance
The development of anode materials is critical to the success of sodium ion batteries (SIBs). Because of the size difference between Li and Na, the commercial anode material graphite in Li-ion batteries does not work for Na-ion batteries. Thus, it will be ideal if some universal anode materials could work for both Li- and Na-ion batteries with high performance. Inspired by a recent study on the high performance of a 2D-Si 2 BN sheet as an anode material for Li-ion batteries, we design a three dimensional (3D) porous structure by using the nanoribbons of a Si 2 BN sheet as building blocks. Based on the state-of-the-art ab initio calculations, we find that the resulting 3D porous Si 2 BN structure is stable chemically, dynamically and thermally, exhibiting a high specific capacity of 512.42 (341.61 mA h g -1 ), a low voltage of 0.27 V (0.15 V), a small volume expansion of 2.5% (2.7%), and a low migration energy barrier of 0.44 eV (0.19 eV) for Li- (Na-) ion batteries. Finally, these intriguing features, together with the light mass and rich abundance of Si, B and N, suggest that the 3D porous Si2BN structure is a promising candidate for the anode material of both Li- and Na-ion batteries.
36 MATERIALS SCIENCE↗
Harnessing nanoscale densification for controlling gas selectivity in flexible zeolitic imidazolate frameworks
Flexible metal-organic frameworks (MOFs) are promising for gas separation due to their molecular recognition capabilities. However, gate-opening behavior in certain flexible MOFs can reduce gas selectivity, enabling simultaneous adsorption of multiple gases. We introduce a binder-free, pressure-free densification process to enhance gas selectivity in flexible zeolitic imidazolate frameworks (ZIF-7 and ZIF-9) by optimizing nanoparticle packing. Unlike powders, the densified ZIF-7 and ZIF-9 retain rhombohedral crystal structures after solvent removal, confirmed via synchrotron powder X-ray diffraction. This process modifies adsorption behavior by introducing a diffusion barrier, enabling diffusivity-driven kinetic separation and enhanced CO2/hydrocarbon selectivity. At 0.5 bar, ZIF-7 mono shows 2×, 4×, and 9.5× higher CO 2 selectivity over C 2 H 2 , C 2 H 4 , and C 2 H 6 , respectively, versus ZIF-7 pwd . ZIF-9 mono similarly shows 6.5×, 3×, and 39× improvements over ZIF-9 pwd . Both monoliths outperform powders in ternary gas mixtures. This study provides a novel strategy to control gate opening and enhance gas selectivity in flexible MOFs for practical separation applications.
CO2/hydrocarbon separation↗
Computational design of isotropic and anisotropic ultralow thermal conductivity polymer foams
Current state-of-the-art commercial polymer thermal insulation foam exhibits a thermal conductivity of 24 mW·m -1 ·K -1 (equivalently thermal resistivity of R-6/in.), similar to that of static air. To further optimize building energy efficiency, achieving even lower thermal conductivity is needed, which is, however, highly challenging. This paper presents computational evidence that demonstrates the feasibility of achieving an ultra-low thermal conductivity of less than 14.4 mW·m -1 ·K -1 (equivalently R-10/in.) using isotropic and anisotropic foam cell designs. For the isotropic design, we have identified analytical effective medium approximation (EMA) models within the accuracy of ±5% as finite element analysis (FEA) in predicting the effective thermal conductivity of foams with various porosities and filler gases. For the anisotropic design, we have developed and validated new EMA models against FEA in predicting the effective thermal conductivity of general anisotropic cuboids and Voronoi foams. For both isotropic and anisotropic designs, the design spaces for 18, 16, and 14.4 mW·m -1 ·K -1 (equivalently R-8, R-9 and R-10/in.) using various filler gases are obtained. It is found that polymer foams can be improved to achieve ultralow thermal conductivity by reducing CO 2 concentration, reducing radiation, increasing porosity, and using anisotropic pore geometry. In conclusion, these findings contribute to the development of highly efficient thermal insulation materials, enhancing building energy efficiency and promoting sustainable construction practices.
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Application of GOTHIC to Groundwater Transport Analysis - 20152
Migration of pollutants and hazardous wastes, potentially containing radioactive isotopes, via groundwater transport is a concern at most waste cleanup sites. Predictive analysis can be used to evaluate mitigating actions intended to minimize impact on the environment and public exposure. GOTHIC is a multipurpose thermal hydraulics code that is used extensively in the nuclear industry for design, licensing and operation evaluations. It combines the capabilities of typical one-dimensional system codes and the essential features of Computational Fluid Dynamics (CFD) codes for three-dimensional analysis. There are other codes that are specifically developed for groundwater transport analysis and the results presented here are consistent with prior analyses. However, GOTHIC has some unique features that offer advantages for applications related to nuclear waste. Most importantly, it has been developed and maintained under a Quality Assurance program in compliance with the requirements of 10CFR50 Appendix B [2] and applicable portions of ASME NQA-1 [3] since 1995. Available GOTHIC capabilities that make the code especially useful for groundwater transport of nuclear materials include: - Tracking of any number of tracer elements for contaminants and other species of interest; - Radioactive decay and progeny of tracer elements; - Adsorption/desorption of tracer elements; - Tracking of any number of dissolved gases; - Release and absorption for dissolved gases; - Vapor phase tracking; - Non-Newtonian fluid modeling. The general porous body modeling approach makes GOTHIC well suited to groundwater transport analysis. The multi-region modeling approach used by GOTHIC simplifies model construction for regions of varying hydrologic characteristics and focuses the computational effort on regions of particular interest while simultaneously capturing the macroscopic response and any feedback effects across the larger domain. The applicability of GOTHIC to groundwater transport applications is demonstrated by comparing code results with available analytic or semi-analytic solutions for groundwater behavior. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Comparison Study of Conventional and Adaptive Mesh Refinement in Organic Material Decomposition Models
This study compares conventional mesh refinement techniques, specifically Uniform Mesh Refinement (UMR), with a new Adaptive Mesh Refinement (AMR) method, applied to Organic Material Decomposition (OMD) models. The proposed benefit of AMR is that only areas that require refinement, based on minimizing a specific field gradient, are refined thus decreasing model wall time compared to conventional UMR methods. This work specifically focuses on comparing UMR and AMR methods on decomposing (both No-Flow and Porous-Flow material models) Polymeric Methylene Diisocyanate (PMDI) polyurethane foam. Throughout the work, the geometry increased in complexity to assess the refinement methods performance at varying levels geometric intricacy. While AMR has been shown to work well in a variety of applications, the UMR approach proved to be computationally faster, for many of the geometries and foam decomposition models, than AMR. However, it was observed that at higher levels of refinement, greater than 3 UMR, AMR begins to be computationally better. Additionally, the settings used to perform AMR greatly impact its performance, and lessons learned, in terms of OMD models, are shared. Due to physics involved in material decomposition, specifically the evolution of state variables, these problems don’t fully benefit from the advantages of AMR.
36 MATERIALS SCIENCE↗
Functional metal–organic frameworks as effective sensors of gases and volatile compounds
Developing efficient sensor materials with superior performance for selective, fast and sensitive detection of gases and volatile organic compounds (VOCs) is essential for human health and environmental protection, through monitoring indoor and outdoor air pollutions, managing industrial processes, controlling food quality and assisting early diagnosis of diseases. Metal–organic frameworks (MOFs) are a unique type of crystalline and porous solid material constructed from metal nodes (metal ions or clusters) and functional organic ligands. They have been investigated extensively for possible use as high performance sensors for the detection of many different gases and VOCs in recent years, due to their large surface area, tunable pore size, functionalizable sites and intriguing properties, such as electrical conductivity, magnetism, ferroelectricity, luminescence and chromism. The high porosity of MOFs allows them to interact strongly with various analytes, including gases and VOCs, thus resulting in easily measurable responses to different physicochemical parameters. Although much of the recent work on MOF-based luminescent sensors have been summarized in several excellent reviews (up to 2018), a comprehensive overview of these materials for sensing gases and VOCs based on chemiresistive, magnetic, ferroelectric, and colorimertic mechanisms is missing. In this review, we highlight the most recent progress in developing MOF sensing and switching materials with an emphasis on sensing mechanisms based on electricity, magnetism, ferroelectricity and chromism. We provide a comprehensive analysis on the MOF–analyte interactions in these processes, which play a key role in the sensing performance of the MOF-based sensors and switches. We discuss in detail possible applications of MOF-based sensing and switching materials in detecting oxygen, water vapor, toxic industrial gases (such as hydrogen sulfide, ammonia, sulfur dioxide, nitrous oxide, carbon oxides and carbon disulfide) and VOCs (such as aromatic and aliphatic hydrocarbons, ketones, alcohols, aldehydes, chlorinated hydrocarbons and N,N'-dimethylformamide). Altogether, this review serves as a timely source of information and provides insight for the future development of advanced MOF materials as next-generation gas and VOC sensors.
36 MATERIALS SCIENCE↗
The Impact of Surficial Biochar Treatment on Acute H2S Emissions during Swine Manure Agitation before Pump-Out: Proof-of-the-Concept
Acute releases of hydrogen sulfide (H2S) are of serious concern in agriculture, especially when farmers agitate manure to empty storage pits before land application. Agitation can cause the release of dangerously high H2S concentrations, resulting in human and animal fatalities. To date, there is no proven technology to mitigate these short-term releases of toxic gas from manure. In our previous research, we have shown that biochar, a highly porous carbonaceous material, can float on manure and mitigate gaseous emissions over extended periods (days–weeks). In this research, we aim to test the hypothesis that biochar can mitigate H2S emissions over short periods (minutes–hours) during and shortly after manure agitation. The objective was to conduct proof-of-the-concept experiments simulating the treatment of agitated manure. Two biochars, highly alkaline and porous (HAP, pH 9.2) made from corn stover and red oak (RO, pH 7.5), were tested. Three scenarios (setups): Control (no biochar), 6 mm, and 12 mm thick layers of biochar were surficially-applied to the manure. Each setup experienced 3 min of manure agitation. Real-time concentrations of H2S were measured immediately before, during, and after agitation until the concentration returned to the initial state. The results were compared with those of the Control using the following three metrics: (1) the maximum (peak) flux, (2) total emission from the start of agitation until the concentration stabilized, and (3) the total emission during the 3 min of agitation. The Gompertz’s model for determination of the cumulative H2S emission kinetics was developed. Here, 12 mm HAP biochar treatment reduced the peak (1) by 42.5% (p = 0.125), reduced overall total emission (2) by 17.9% (p = 0.290), and significantly reduced the total emission during 3 min agitation (3) by 70.4%. Further, 6 mm HAP treatment reduced the peak (1) by 60.6%, and significantly reduced overall (2) and 3 min agitation’s (3) total emission by 64.4% and 66.6%, respectively. Moreover, 12 mm RO biochar treatment reduced the peak (1) by 23.6%, and significantly reduced overall (2) and 3 min total (3) emission by 39.3% and 62.4%, respectively. Finally, 6 mm RO treatment significantly reduced the peak (1) by 63%, overall total emission (2) by 84.7%, and total emission during 3 min agitation (3) by 67.4%. Biochar treatments have the potential to reduce the risk of inhalation exposure to H2S. Both 6 and 12 mm biochar treatments reduced the peak H2S concentrations below the General Industrial Peak Limit (OSHA PEL, 50 ppm). The 6 mm biochar treatments reduced the H2S concentrations below the General Industry Ceiling Limit (OSHA PEL, 20 ppm). Research scaling up to larger manure volumes and longer agitation is warranted.
Chen, Baitong (ORCID:0000000266071253)↗
The Influence of Aqueous Dispersivity on Transport of Radiological Material at LANL MDA G - 20450
Aqueous dispersivity is a phenomenon by which a solute moving in groundwater mixes with water that does not contain the solute and becomes diluted. Solutes take paths of varying lengths through pore networks or experience slower velocities due to interactions with pore walls. Aqueous dispersivity leads to breakthrough curves with earlier arrival than expected in purely advective systems and persistent 'tails,' or late-arriving, dilute concentrations of the solute. Dispersivity can be longitudinal (in the direction of flow) or transverse (orthogonal to flow). LANL has disposed of radioactive material at Material Disposal Area (MDA) G since the late 1950's. Most of the disposed materials at MDA G are low-level waste (LLW), but other types of radioactive wastes are disposed or stored at the site. For example, there is a collection of remote-handled transuranic waste (RH-TRU) waste in 33 shafts, which were intended to be stored retrievably. Aqueous-phase radionuclides included in models of contaminant transport at MDA G are subject to dispersive processes in porous media of the vadose zone and saturated zone. To model dispersivity at MDA G probabilistically, we created site-specific distributions of aqueous dispersivity. First, we performed a comprehensive review of peer-reviewed publications, reports from other performance assessments of MDA G, and documentation from sites that were considered similar based on expert opinion, such as Yucca Mountain. Data were included from a wide range of sources, so that distributions developed based on the data reflect the current state of knowledge in properties of the subsurface environment. Data were grouped based on value type (e.g., determined via experiment or used in a different model), rock type, zone type (saturated or unsaturated), and site, and were weighted in the distributions according to their relevance to the site and zone type. We combined Monte Carlo simulation and bootstrapping techniques to produce approximate distributions of mean aqueous dispersivity. Distributions of dispersivity for saturated and unsaturated zone transport are differentiated by data weight and the length scales over which transport occurs. We find that underestimating or disregarding transverse dispersivity may lead to overstating simulated well capture in the saturated zone at MDA G. Neglecting transverse dispersivity is a common assumption due in part to use of one-dimensional transport models that do not consider solute spreading orthogonal to flow. Also, we find that variability in longitudinal dispersivity is associated with substantial travel time alterations in the MDA G unsaturated zone and in simulated contaminant breakthrough times at a downstream observation plane in the MDA G saturated zone. Finally, at large scales (>1000 m), a linear trend between the dispersivity coefficient and length over which transport occurs may overestimate the dispersivity coefficient. Future modeling work with application to solute spreading could include interacting advective and diffusive zones in the highly fractured basalt below MDA G. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
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↗
Structured illumination with thermal imaging (SI-TI): A dynamically reconfigurable metrology for parallelized thermal transport characterization
The recent push for the “materials by design” paradigm requires synergistic integration of scalable computation, synthesis, and characterization. Among these, techniques for efficient measurement of thermal transport can be a bottleneck limiting the experimental database size, especially for diverse materials with a range of roughness, porosity, and anisotropy. Traditional contact thermal measurements have challenges with throughput and the lack of spatially resolvable property mapping, while non-contact pump-probe laser methods generally need mirror smooth sample surfaces and also require serial raster scanning to achieve property mapping. Here, we present structured illumination with thermal imaging (SI-TI), a new thermal characterization tool based on parallelized all-optical heating and thermometry. Experiments on representative dense and porous bulk materials as well as a 3D printed thermoelectric thick film (~50 μm) demonstrate that SI-TI (1) enables paralleled measurement of multiple regions and samples without raster scanning; (2) can dynamically adjust the heating pattern purely in software, to optimize the measurement sensitivity in different directions for anisotropic materials; and (3) can tolerate rough (~3 μm) and scratched sample surfaces. Here, this work highlights a new avenue in adaptivity and throughput for thermal characterization of diverse materials.
42 ENGINEERING↗