Design Of Porous Materials Research Articles

Numerical study of transpiration cooling at different outlet angles and hole pattern

The effects of transpiration cooling depends on the distribution of micropores in porous materials. The work simplifies the porous medium to a micro-scale pore plate structure that is densely organized, based on the idea of the capillary bundle model. The effects of hole pattern and hole outlet angle on transpiration cooling are investigated using numerical simulation. It is discovered that the hole outlet angle mostly affects the homogeneity of temperature distribution and has minimal effect on the surface cooling efficiency. The temperature uniformity index dropped by 35.9% yet the surface cooling efficiency only declined by 1.1% when the outlet angle was lowered from 45° to −45°. Furthermore, the temperature uniformity and cooling efficiency are directly affected by the hole pattern. When the long axis of the elliptical hole is parallel to the mainstream, it can achieve the best temperature uniformity; however, when the long axis is perpendicular to the mainstream direction, it can achieve higher cooling efficiency. Third, the material’s permeability will be decreased to varying degrees depending on the hole pattern and hole outlet angle. The results have important reference significance for the design of porous materials used for transpiration cooling.

Efficient carbon dioxide capture from flue gas and natural gas by a robust metal–organic framework with record selectivity and excellent granulation performance

The design of porous materials for CO2 capture from flue gas and natural gas is highly demanded. However, it is challenging to target materials that combine high CO2 capacity and CO2 selectivity. In this work, we report a robust metal–organic framework (MOF) Zn-ox-mtz with one dimensional channels and narrow windows for excellent CO2 capture from CO2/N2 (simulated flue gas) and CO2/CH4 (simulated natural gas) with high selectivity. Zn-ox-mtz exhibits a high CO2 capacity (58.0 STP cm3 g−1 at 15 kPa), excellent CO2/N2 (15/85, S > 106) and CO2/CH4 (50/50, S > 105) selectivity and good chemical stability. In addition, the practical separation performance is demonstrated by breakthrough experiments under various process conditions. A efficient separation is achieved with the impressive CO2 capacity of 2.60 ± 0.12 mmol g−1 at 298 K. Importantly, the outstanding performance is sustained under high humidity. The molecular sieving mechanism investigated by theoretical calculations indicated that CO2 with small molecular size is tightly trapped by multiple C = O···H-C hydrogen bonding and O = C···O forces in the cavity while CH4 and N2 with larger molecular size display overlarge energy barrier to cross the contract pore windows. Moreover, the granulation of Zn-ox-mtz by hydroxypropyl cellulose is realized with high MOF loading (93.8 %) and the granulated Zn-ox-mtz beads retained the excellent CO2/N2 and CO2/CH4 separation performance.

Improvement of sound absorption of porous materials through periodic holes of sinusoidal decreasing profile

Porous materials used in several engineering applications for noise attenuation present poor acoustic performance at low frequencies. In this paper, a design of porous materials with various periodic decreasing hole profiles is presented and studied using the finite element method. The sound absorption coefficient and the normalized surface impedance are compared for different periodic decreasing hole profiles. A small drop in sound absorption is observed after the first peak with a decreasing linear profile. Using a sinusoidal decreasing hole profile, it is shown that the drop is attenuated. The impacts of the amplitude and the period of the sinusoidal profile on the sound absorption coefficient and the surface impedance are demonstrated. The proposed porous material design with periodic holes having a sinusoidal decreasing profile shows a significant improvement in sound absorption over a large frequency band compared to conventional porous materials.

Promising porous materials for uranium extraction from seawater

Uranium extraction from seawater is a promising approach for ensuring continued uranium fuel supply to the nuclear power industry. However, extracting uranium by this route is challenging due to the low concentration of uranium, high ionic strength, and marine micro-organisms in seawater. Recently, a range of novel porous adsorbent materials have been developed for uranium extraction from ocean water. These adsorbents rely on specific pore characteristics and functional groups (hydroxyl, carboxyl, amidoxime, phosphate, etc.) to achieve a high affinity and selectivity for uranyl ions (UO22+) relative to other ions. Relying strongly on coordination principles, specific binding sites for uranium are assembled in these porous materials, with cooperative actions of several functional groups often used to achieve strong uranium capture and adsorption selectivity. In addition to traditional adsorbents, adsorption-photocatalytic and adsorption-electrocatalytic materials are also being pursued, which include both specific adsorption sites and photocatalytic or electrocatalytic moieties in their frameworks. These innovative strategies allow the conversion of uranyl ions into harvestable solid products (such as UO2 or Na2O(UO3·H2O)x) and result in high extraction efficiencies together with good biofouling resistance. This perspective aims to capture some of the recent breakthroughs in the design of porous materials for selective uranium extraction from seawater.

Reaction-Initiated Single-Molecule Tracking of Mass Transfer in Core-Shell Mesoporous Silica Particles.

Understanding the host-guest interactions in porous materials is of great importance in the field of separation science. Probing it at the single-molecule level uncovers the inter- and intraparticle inhomogeneity and establishes structure-property relationships for guiding the design of porous materials for better separation performance. In this work, we investigated the dynamics of host-guest interactions in core-shell mesoporous silica particles under in situ conditions by using a fluorogenic reaction-initiated single-molecule tracking (riSMT) approach. Taking advantage of the low fluorescence background, three-dimensional (3D) tracking of the dynamics of the molecules inside the mesoporous silica pore was achieved with high spatial precision. Compared to the commonly used two-dimensional (2D) tracking method, the 3D tracking results show that the diffusion coefficients of the molecules are three times larger on average. Using riSMT, we quantitatively analyzed the mass transfer of probe molecules in the mesoporous silica pore, including the fraction of adsorption versus diffusion, diffusion coefficients, and residence time. Large interparticle inhomogeneity was revealed and is expected to contribute to the peak broadening for separation application at the ensemble level. We further investigated the impact of electrostatic interaction on the mass transfer of molecules in the mesoporous silica pore and discovered that the primary effect is on the fraction rather than their diffusion rates of resorufin molecules undergoing diffusion.

Inverse design of porous materials: a diffusion model approach

A diffusion model was employed to generate porous materials, marking one of the earliest endeavors in this domain. The model demonstrates high efficacy in designing structures with user-desired properties.

Porous Material for Gas Thermal Compression in Space Conditions: Thermal Design Aspects

Abstract It is almost impossible to name a field of human activity where porous materials are not used. Filters, membranes, thermal insulators, fuel cells, catalysts, wicks of heat transfer devices, sorbents, textiles, and other examples of porous materials explain such an increased interest in the study of their properties, design of new materials, and development of technologies for their manufacture. The recent need for in-orbit spacecraft refuelling has led to the development of gas thermal compression technology based on the use of porous material as both a fuel retention mechanism and thermal interface. The present paper reveals the thermal aspects of porous material design for a device intended for pumping xenon, fuel for ion thrusters, in zero-gravity conditions – Xenon Refuelling Compressor.

Enhancing Structure-Property Relationships in Porous Materials through Transfer Learning and Cross-Material Few-Shot Learning.

Porous materials have emerged as promising solutions for a wide range of energy and environmental applications. However, the asymmetric development in the field of metal-organic frameworks (MOFs) has led to a data imbalance when it comes to MOFs versus other porous materials such as covalent organic frameworks (COFs), porous polymer networks (PPNs), and zeolites. To address this issue, we introduce PMTransformer (Porous Material Transformer), a multimodal Transformer model pretrained on a vast data set of 1.9 million hypothetical porous materials, including metal-organic frameworks, covalent organic frameworks, porous polymer networks, and zeolites. PMTransformer showcases remarkable transfer learning capabilities, resulting in state-of-the-art performance in predicting various porous material properties. To address the challenge of asymmetric data aggregation, we propose cross-material few-shot learning, which leverages the synergistic effect among different porous material classes to enhance the fine-tuning performance with a limited number of examples. As a proof of concept, we demonstrate its effectiveness in predicting band gap values of COFs using the available MOF data in the training set. Moreover, we established cross-material relationships in porous materials by predicting the unseen properties of other classes of porous materials. Our approach presents a new pathway for understanding the underlying relationships among various classes of porous materials, paving the way toward a more comprehensive understanding and design of porous materials.

Porous Conductive Hybrid Composite with Superior Pressure Sensitivity and Dynamic Range

AbstractPorous conductive composites hold immense promise in flexible sensors and soft robotics due to their pressure‐responsive electrical conductivity. Unlike non‐porous composites whose pressure sensitivity is limited by relatively high elastic modulus, porous materials show improved pressure sensitivity owing to their lower stiffness. Despite this, existing porous composites still suffer from insufficient pressure sensitivity or narrow detection ranges, severely restricting their applications. This work presents a liquid metal hybrid filler porous composite to address these issues. Through experiment and simulation optimization, the composite exhibits a conductivity increase of five order‐of‐magnitude over 0–250 kPa, demonstrating a 900% higher pressure sensitivity than the best non‐porous counterpart in this work. The composite maintains a highly linear response (R2 of 0.999) over an exceptionally wide dynamic range up to 8.9 MPa, with a pressure sensitivity of 8.1 MPa–1, surpassing the state‐of‐the‐art in both pressure range and sensitivity. A proof‐of‐concept pressure sensor array further demonstrates the composite's excellent sensing performance, showing stable response under 100‐cycle loading with a measured pressure deviation of only 1.4%, outperforming existing commercial pressure sensors in terms of sensitivity, detection range and cyclic stability. The porous material design strategy opens doors for high sensitivity pressure sensors in wearable devices, flexible electronics, and soft robotics.

Synthetic control of correlated disorder in UiO-66 frameworks

Changing the perception of defects as imperfections in crystalline frameworks into correlated domains amenable to chemical control and targeted design might offer opportunities for the design of porous materials with superior performance or distinctive behavior in catalysis, separation, storage, or guest recognition. From a chemical standpoint, the establishment of synthetic protocols adapted to control the generation and growth of correlated disorder is crucial to consider defect engineering a practicable route towards adjusting framework function. By using UiO-66 as experimental platform, we systematically explored the framework chemical space of the corresponding defective materials. Periodic disorder arising from controlled generation and growth of missing cluster vacancies can be chemically controlled by the relative concentration of linker and modulator, which has been used to isolate a crystallographically pure “disordered” reo phase. Cs-corrected scanning transmission electron microscopy is used to proof the coexistence of correlated domains of missing linker and cluster vacancies, whose relative sizes are fixed by the linker concentration. The relative distribution of correlated disorder in the porosity and catalytic activity of the material reveals that, contrarily to the common belief, surpassing a certain defect concentration threshold can have a detrimental effect.

Strength design of porous materials using B-spline based level set method

The inverse homogenization method can tailor some mechanical and physical effective properties by laying out materials in a periodic representative volume element. However, studies on strength design are yet to be developed because of the difficulties in numerically retrieving its value. Unlike traditional asymptotic homogenization, the fast Fourier transform-based homogenization method based on the augmented Lagrangian approach uses a Green operator in the frequency domain to replace time-consuming finite element analysis and inherently meet the periodic boundary conditions. Thus, it is developed in this work to retrieve material strength in terms of the von Mises yield criterion. The zero-level contour of a linear combination of cubic B-spline basis functions with repeated knots is used to represent the microstructure profile in the design of material strength. The effective strength or its squared difference with a prescribed target is minimized within the framework of the reaction diffusion-based B-spline level set method. The filtered, non-consistent discrete Green operator is adopted to avoid slow convergence of porous material. Examples of porous material demonstrate that the proposed method guarantees surface smoothness, optimization flexibility, and structural periodicity in strength design.

Shrinkage Dynamics of Organic Template Substances with Long Alkyl Chains toward Porous Material Design

Shrinkage Dynamics of Organic Template Substances with Long Alkyl Chains toward Porous Material Design

Stabilized isogeometric formulation of the multi-network poroelasticity and transport model (MPET[formula omitted]) for subcutaneous injection of monoclonal antibodies

The MPET2 model couples the multi-network poroelastic theory (MPET) with solute transport equations and provides predictions of the material deformation, fluid dynamics, and solute transport in different compartments of a deformable multiple-porosity medium. MPET2 offers a comprehensive framework for understanding complex porous media across multiple disciplines. Examples of its applications include studying rock formations, soil mechanics and subsurface reservoirs, investigating biological tissues, modeling groundwater flow and contaminant transport, and optimizing the design of porous materials. Despite the wide range of applications of the model, its numerical discretization has received little attention. Here we propose a stabilized formulation of the MPET2 model. To address the unique challenges posed by the discretization of the MPET2 model, we use multiple techniques including the Fluid Pressure Laplacian stabilization, Streamline Upwind Petrov–Galerkin stabilization, and discontinuity capturing. Our spatial discretization is based on Isogeometric Analysis with higher-order continuity basis functions. The fully discretized governing equations are solved simultaneously with a monolithic algorithm. We perform a convergence study of the proposed formulation. Then, we conduct a series of simulations of subcutaneous injection of monoclonal antibodies under different injection conditions. Our simulations show that the stabilized MPET2 formulation can provide oscillation-free solutions for tissue deformation, fluid flow in the interstitial tissue, blood vessels, and lymphatic vessels, drug absorption in blood vessels and lymphatic vessels, as well as drug transport in each compartment. We also study the effects of different injection conditions on drug absorption, showing the potential of the proposed model and algorithm in the future optimization of injection strategy.

Investigation on the thermoelastic response of a porous microplate in a modified fractional-order heat conduction model incorporating the nonlocal effect

In recent years, the application of porous materials in practical engineering has become increasingly common. Under extreme thermal conditions, how to accurately describe the heat conduction and structural response of porous materials is a key issue in the structural safety and functional design of porous materials. Among them, it is particularly important to consider the size-dependent and memory-dependent effects for small-sized structures or microdevices of porous materials. To address these issues of porous structures and to guide their applications as well as optimization, this paper first investigates the thermoelastic transient response of porous microplates subjected to thermal and stress shocks at the left boundary based on the Atangana-Baleanu (AB) fractional-order generalized thermoelastic theory by considering nonlocal effects and fractional-order strain, which is combined with the thermoelasticity theory of porous materials and the dual-phase-lag (DPL) heat conduction model. The governing equations are then established and solved using the Laplace transform and its numerical inversion. Finally, the effects of newly defined fractional order parameters, nonlocal parameters and the initial magnitude of the mechanical shock on the dimensionless temperature, volume fraction field, displacement and stress distribution are discussed and displayed graphically.

Scalable and flexible biomass-based porous Juncus effusus fabric for high-efficient solar interfacial evaporation

Biomass porous materials have special structural properties that serve as solar interfacial evaporators. However, the integrated flexible design of porous materials for vapor generation is a problem. In this study, a novel textile weaving craft was proposed to fabricate a scalable, flexible, and stable solar vapor generator using a natural biomass porous plant (Juncus effusus, JE fibers). The high porosity, reflection, and refraction paths of light in the pore structure of JE fibers help improve water vapor escape and light absorption. Additionally, the designed bridge-like porous Juncus effusus-cotton yarn fabric (JECYF)-based solar vapor generator can achieve efficient thermal management, which can enhance the photothermal conversion efficiency of evaporation. After acquiring a light absorption modification treatment, the JECYF-based solar vapor generator obtained a significant photothermal performance of 2.42 kg m−2h−1 under 1 sun irradiation. Thus, textile weaving technology’s unique properties make large-scale preparation and practical application of porous materials in solar vapor evaporator devices possible.

New‐Generation Anion‐Pillared Metal–Organic Frameworks with Customized Cages for Highly Efficient CO2 Capture

AbstractThe rational design of porous materials for CO2 capture under realistic process conditions is highly desirable. However, trade‐offs exist among a nanopore's capacity, selectivity, adsorption heat, and stability. In this study, a new generation of anion‐pillared metal‐organic frameworks (MOFs) are reported with customizable cages for benchmark CO2 capture from flue gas. The optimally designed TIFSIX‐Cu‐TPA exhibits a high CO2 capacity, excellent CO2/N2 selectivity, high thermal stability, and chemical stability in acid solution and acidic atmosphere, as well as modest adsorption heat for facile regeneration. Additionally, the practical separation performance of the synthesized MOFs is demonstrated by breakthrough experiments under various process conditions. A highly selective separation is achieved at 298–348 K with the impressive CO2 capacity of 2.1–1.4 mmol g−1. Importantly, the outstanding performance is sustained under high humidity and over ten repeat process cycles. The molecular mechanism of MOF's CO2 adsorption is further investigated in situ by CO2 dosed single crystal structure and theoretical calculations, highlighting two separate binding sites for CO2 in small and large cages featured with high CO2 selectivity and loading, respectively. The simultaneous adsorption of CO2 inside these two types of interconnected cages accounts for the high performance of these newly designed anionic pillar‐caged MOFs.

Acoustic optimization design of porous materials on sandwich panel under flow-induced vibration

In this study, porous sound-absorbing materials used as a lining in double-panel structure applications (such as high-speed train body structures) to limit flow-induced vibration interior noise were studied, and acoustic optimization design was performed. First, in the wavenumber domain, the cross-spectrum Corcos model was used to characterize the dynamic hydrodynamic pressure of turbulence. Biot’s theory is used to model the porous materials. The transmission loss (TL) of the sandwich panel were also determined based on the model superposition method. Three types of sandwich panel structures were considered: air–air (A–A), bonded-bonded (B–B), and bonded-air (B–A). The TL of the three structure types under hydrodynamic pressure was used to evaluate the suppression of flow-induced vibration interior noise in porous materials. The effects of flow velocity, thickness and density of the porous material, and three types of polyimide foam on the TL characteristics of the sandwich panel were investigated. The results show that the flow velocity has a significant influence on the TL of the sandwich panel. The TL of the sandwich panel decreases by 3–4 dB when the flow velocity increases by 100 km/h The B–A configuration has satisfactory sound insulation performance at most frequencies. With an increase in material thickness, the TL of the sandwich panel structure first increases and then decreases, and the material density mainly affects the TL of the structure at intermediate and high frequencies. Based on the objectives of maximizing the average transmission loss (TLavg) and minimizing the structural weight, the acoustic optimization design of the B–A structure was performed, and the balance between the two objective functions was achieved by a nondominated sorting genetic algorithm (NSGA-Ⅱ). The TLavg s of the sandwich panel structure increased by 5.2 dB when the total mass of the structure was decreased by 0.2 kg.

Nanostructured supramolecular networks from self-assembled diamondoid molecules under ultracold conditions.

Diamondoid molecules and their derivatives have attracted attention as fascinating building blocks for advanced functional materials. Depending on the balance between hydrogen bonds and London dispersion interactions, they can self-organize in different cluster structures with functional groups tailored for various applications. Here, we present a new approach to supramolecular aggregation where self-assembly of diamondoid acids and alcohols in the ultracold environment of superfluid helium nanodroplets (HNDs) was analyzed by a combination of time-of-flight mass spectrometry and computational tools. Experimentally observed magic numbers of the assembled cluster sizes were successfully identified and computed cluster structures gave valuable insights into a different conglomeration mode when compared to previously explored less-polar diamondoid derivatives. We have confirmed that functional groups acting as good hydrogen bond donors completely take over the self-organization process, resulting in fascinating pair-wise or cyclic supramolecular assemblies. Particularly noteworthy is that mono- and bis-substituted diamondoid derivatives of both series engage in completely different modes of action, which is reflected in differing non-covalent cluster geometries. Additionally, formed cyclic clusters with a polar cavity in the center and a non-polar diamondoid outer layer can be of high interest in porous material design and provide insights into the structural requirements needed to produce bulk materials with desired properties.

Modeling method for variable and isotropic permeability design of porous material based on TPMS lattices

Porous materials are widely used in fluid and heat transport fields. The present graphite porous materials have random internal pore distribution, and it is difficult to precisely reconstruct their tiny pore structures and manage their permeability. In this work, a method of constructing porous structures based on triply periodic minimal surfaces (TPMS) is proposed, and the effect law of wall thickness and curvature parameter C on the permeability of TPMS porous structures is investigated. Permeability isotropic structures with permeability of approximately 5e-14 m2 to 2e-13 m2 are obtained by structural parameters adjustment and composite units. The study can provide a basis for the design of porous structures in the field of aerostatic bearings and heat transfer.

High-throughput Screening Computation for Discovery of Porous Zeolites for Hydrogen Storage

Hydrogen is considered an attractive energy resource because it is eco-friendly in contrast with fossil fuels. Hydrogen storage remains as essential technology for increasing the use of the hydrogen in applications such as hydrogen vehicles and fuel cells. Hydrogen storage requires retaining a high density of hydrogen molecules at ambient temperature in a suitable tank. Zeolites are one of the promising hydrogen storage materials, but experimentally investigating them for hydrogen storage is difficult since the number of the zeolites in the largescale material database has been increasing. In the present study I developed an efficient method of exploring potential zeolites in the database that had high volumetric hydrogen storage capacity. To do this I employed a high-throughput screening approach to automatically construct a zeolite database for hydrogen storage in the Inorganic Crystal Structural Database (ICSD). Also, I performed grand canonical Monte Carlo (GCMC) simulations to estimate hydrogen adsorption isotherms at operating ambient temperatures, to determine the volumetric hydrogen storage capacity of the zeolites. Finally, I found 10 top ranked materials in the zeolite database for H2 storage, and I calculated Pearson’s correlation coefficient to revealed the linear correlations between the hydrogen storage capacities and 3 structural characteristics (i.e., surface area, largest cavity diameter, pore limiting diameter). Furthermore, I investigated atom species in the 10 materials to show the relation between the hydrogen storage capacities and chemical elements. In future works, I expect the method can be easily applied to accelerate the discovery and design of porous materials for storing CO2 or toxic gases.