An efficient approximation of the supercell approach to the calculation of the full phonon spectrum
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Duong, Thien C. (ORCID:000000018694814X)↗
SEARCH · Engineering Papers
Results for “Materials Design”
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Insights from machine learning of carbon electrodes for electric double layer capacitors
Recent years have witnessed the broad use of carbon electrodes for electric double layer capacitors (EDLCs) because of large surface area, high porosity and low cost. Whereas experimental investigations are mostly focused on the device performance, computational studies have been rarely concerned with electrochemical properties at conditions remote from equilibrium, limiting their direct applications to materials design. Through a comprehensive analysis of extensive experimental data with various machine-learning methods, we report herein quantitative correlations between the structural features of carbon electrodes and the in-operando behavior of EDLCs including energy and power density. Machine learning allows us to identify important characteristics of activated carbons useful to optimize their efficiency in energy storage.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Engineering phonon transport through cation disorder in dimensionally constricted high entropy MXene
Designing materials with low thermal conductivity is a crucial objective for applications in thermal insulation and thermoelectrics. Traditional methods such as doping, mechanical strain and introducing defects in perfect crystals have been widely explored to impede the flow of heat. Here, this work introduces dimensional constriction and cationic disorder as novel avenues to manipulate lattice thermal conductivity (LTC). High entropy materials characterized by random distribution of multiple elements, creates a suitable environment for thermal insulation due to its configurational disorder and local lattice distortions. On the other hand, MXenes, derived from MAX-phase, have garnered considerable attention due to their unique structural attributes, leading to potential applications in catalysis and energy storage. Ti 2 AlC MAX-phase is examined to understand the impact of dimensional constriction on phonon transport of Ti 2 C with cationic disorder, i.e., (Ti 0.25 Nb 0.25 Cr 0.25 Ta 0.25 ) 2 C. The exponential reduction in LTC of HE-MXene is attributed to disorder scattering that significantly limits phonon mean free path (MFP) and relaxation time. The spread of mode-resolved LTC with MFP highlights the influence of disorder on phonon scattering. This work provides a systematic approach to engineer LTC through dimensional constriction and cationic disorder, laying the foundation for tailored materials with desired thermal properties.
2D materials↗
Machine learning elastic constants of multi-component alloys
The present manuscript explores application of machine learning methods for determining elastic constants and other derived mechanical properties of multi-component alloys. Here, a number of machine learning models, including linear regression, neural network and random forest based models, are trained and tested on a dataset of binary alloys generated using density functional theory (DFT) calculations and spanning over a large number of elemental species in the periodic table. Starting with a wide range of simple and easily accessible compositionally-averaged elemental features, a correlation-based feature selection strategy was used to systematically down-select a set of most relevant features towards the prediction of the elasticity tensor components. The true predictive performance and the associated uncertainties of the models were established by testing on unseen data and bootstrapping, respectively. A single and pair-wise feature partial dependence analysis was performed to visualize the average property trends in the multi-dimensional feature space in order to further understand the achieved predictive performance. The utility of the trained model is further demonstrated by obtaining sufficiently accurate yet highly efficient approximations for bulk modulus, Young’s modulus, shear modulus and Poisson’s ratio for alloys beyond the binary space (i.e., two-component alloys) on which the model was originally trained. More importantly, we test and validate the predictive performance of the developed model directly against the experimentally measured elastic constants of technologically relevant multi-component alloys (such as, Ni- and Ti-based alloys). Finally, utility of such a data-enabled route is demonstrated by predicting the possible range of various elastic properties for vast composition space available within the five component Ni-Cr-Fe-Mo-W alloy system in a high-throughput manner.
36 MATERIALS SCIENCE↗
Leaching Model of Radionuclides in Metal-Organic Framework Particles
Metal-organic frameworks (MOFs) have been used to sequester radionuclides and seal them inside of porous scaffolds using postsynthetic modification procedures. Experiments show that certain Zr-MOF with different capping linkers significantly affects the radionuclide release kinetics. In this work, we developed a leaching model of radionuclides in Zr-MOF particles. The model assumes that uranyl species occupy two energetically favored sites: the metal node and the MOF pores. For a given overall concentration of uranyl species, the partitions of uranyl species at the metal nodes and within the pores are determined by their chemical potentials. The model also considers the effect of particle surface and concentration on chemical potentials and diffusivity. The effects of spatial and structural dependent chemical potentials and diffusivity as well as particle sizes on leaching kinetics are investigated with the model. Predicted and measured uranyl leaching kinetics in Zr-MOF particles under batch experiments are compared. The results demonstrate the model’s capability for exploring the mechanisms of leaching and provide guidance for material design.
Metal-Organic Framework, Diffusion, uranyl, Leachi↗
Agentic framework for programmatic crystal structure generation using a fine-tuned worker–supervisor large language model
Platinum group metals (PGMs) underpin many catalytic technologies but face severe supply constraints, motivating the search for alternative materials and computational methods to accelerate discovery. While atomistic simulation tools such as Pymatgen and ASE have streamlined structure manipulation, they require detailed inputs, limiting accessibility for experimentalists and slowing early-stage exploration. Here, in this study, we present an AI-driven agentic framework that orchestrates worker–supervisor large language models (LLMs). The worker translates natural-language prompts of varying abstraction into valid crystallographic structures using a compact LLM fine-tuned with low-rank adaptation on a curated text–code–CIF dataset, emphasizing energy-efficient training. Benchmarking against the baseline CodeGen-350M-mono model shows that fine-tuning reduces hallucination rates from 100% to as low as 5% and improves structural match accuracy to up to 82% for fully specified inputs. Accuracy declines with decreasing prompt detail but remains nontrivial even when only stoichiometry and space group are provided, underscoring the LLM’s capacity for crystallographic inference. The supervisor Claude LLM evaluates the outputs and triggers iterative refinement through the worker’s built-in structure manipulation capabilities (e.g., supercell scaling, strain, vacancy, and substitution operations). We further demonstrate use cases for technologically relevant catalysts, including IrO 2 , pyrochlore Pb 2 Ir 2 O 7 , Ni 2 FeO 4 , and Ni 3 Mo, where the framework generates physically consistent structures that can be refined via geometry optimization. This work introduces a low-energy, language-driven pathway for integrating human and machine intelligence in materials design, paving the way for AI-assisted synthesis planning and high-throughput screening of complex oxides.
AI agent↗
Constructing O2/O3 homogeneous hybrid stabilizes Li-rich layered cathodes
With the advantages of high energy density and low manufacture cost, lithium-rich layered oxides (LLOs), typically with a layered O3-type structure, are regarded as promising cathodes for lithium-ion batteries (LIBs), but their broad usages are hindered by severe voltage decay over cycling. Although recent progress in O2-type LLOs has aroused interest for their less voltage decay, the critical barrier of unsatisfactory capacity retention has not been overcome yet. In this work, to tackle these handicaps, we design a new type of LLO (O2/O3-type LLO) with a homogeneous hybrid structure, where the O2 and O3 lattice stacking sequences are arranged alternatively. Benefitting from this novel O2/O3 hybrid structure, the designed material shows greatly improved voltage and capacity stability than that of pure O2- and O3-type LLOs. Revealed by in-situ synchrotron X-ray diffraction and operando differential electrochemical mass spectra, the O2/O3-hybrid LLO cathode shows a more reversible structural evolution, smaller volume change and suppressed oxygen loss during the electrochemical processes. Our approach has initiated a new way to reduce the capacity and voltage decay of LLOs, which endows great promise to the development of high-energy-density LIBs.
25 ENERGY STORAGE↗
A comprehensive review of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) techniques in protonic ceramic cells (PCCs): Current status and future perspective
Protonic ceramic cells (PCCs) have emerged as a promising technology for power generation, energy storage, and value-added chemical synthesis, offering benefits such as fuel flexibility, low emissions, and efficient operation at intermediate temperatures (300–600 °C). Recently, significant breakthroughs in materials and manufacturing methods have markedly enhanced the performance of PCCs. However, establishing a fundamental understanding of their electrocatalytic reactions has gained less attention. As a fast and cost-effective method for physicochemical fingerprinting, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) has proven to be a surface-sensitive analytical tool for structural and functional studies. This review critically examines the most up-to-date applications of DRIFTS for characterizing key components of PCCs, including oxygen electrodes, protonic electrolytes, and hydrogen electrodes for different applications, with a focus on revealing hydration properties and catalytic reactions, and guiding rational material design. The challenges for advancing DRIFTS, including quantitative capabilities and operando applications for PCC investigations, are highlighted and strategies to tackle these challenges are discussed. Ultimately, this review underscores the critical role of DRIFTS in accelerating the development of high-performance and durable PCCs for next-generation energy solutions, offering methodologies and insights broadly applicable to a wide range of electrochemical energy conversion and storage technologies.
Diffuse Reflectance Infrared Fourier Transform Spe↗
High-rate, high-capacity electrochemical energy storage in hydrogen-bonded fused aromatics
Designing materials for electrochemical energy storage with short charging times and high charge capacities is a longstanding challenge. The fundamental difficulty lies in incorporating a high density of redox couples into a stable material that can efficiently conduct both ions and electrons. We report all-organic, fused aromatic materials that store up to 310 mAh g –1 and charge in as little as 33 s. This performance stems from abundant quinone/imine functionalities that decorate an extended aromatic backbone, act as redox-active sites, engage in hydrogen bonding, and enable a delocalized high-rate energy storage with stability upon cycling. Here, the extended conjugation and hydrogen-bonding-assisted bulk charge storage contrast with the surface-confined or hydration-dependent behavior of traditional inorganic electrodes.
36 MATERIALS SCIENCE↗
Fine-tuned thermally cross-linkable 6FDA-based polyimide membranes for aggressive natural gas separation
Glassy 6FDA-based polyimides are attractive membrane materials for many industrially important gas separations; however, plasticization in aggressive natural gas often causes significant loss in CO 2 /CH 4 selectivity. In this study, a family of thermally cross-linkable 6FDA-based polyimides containing carboxyl groups were synthesized and cross-linked as dense films via decarboxylation-induced thermal crosslinking. As well as chemical structure, crosslinking temperatures above and below T g are shown to be synergistic tools. Our results demonstrate that structure evolution during the decarboxylation-induced crosslinking process is affected significantly by the 3,5-diaminobenzoic acid (DABA) content in the polymer backbone. Even for a 50/50 CO 2 /CH 4 binary mixture with feed pressure up to 800 psia, decarboxylation-induced crosslinking provides attractive gas separation performance and plasticization resistance. Combined facile structure tunability, crosslinkability and high asymmetric fiber spinnability make the cross-linkable 6FDA-based polyimides a versatile platform for diverse aggressive natural gas feeds encountered in practice. Finally, our study provides insights into material design of thermally cross-linkable polymer membranes for such a broad spectrum of aggressive gas separations.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Non-equilibrium simulations of hydraulic permeation: Role of mechanical boundary conditions in dense membranes
Understanding the mechanisms of water transport in reverse osmosis membranes is critical for improving membrane performance and guiding material design. While classical models describe transport as either solution-diffusion (SD)—involving concentration-driven diffusion through a homogeneous medium—or pore-flow (PF)—involving pressure-driven convection through percolated water channels—their applicability to crosslinked polyamide membranes remains debated. Here, using non-equilibrium molecular dynamics simulations, we investigate the impact of mechanical support conditions on pressure-driven water transport in polyamide membranes across varying crosslink densities and pressure differentials (1000–5000 bar). Two support conditions are considered: graphene-restrained, representing experimentally relevant supported membranes, and freeze-restrained, mimicking a self-supported structure. In graphene-restrained systems, water concentration gradients and constant pressure profiles emerge, consistent with SD theory and incompatible with PF assumptions due to the absence of percolated pores and sub-nanometer voids. In contrast, freeze-restrained systems display uniform water concentration and linearly decreasing pressure at 1000 bar, and exhibit compressibility-induced water gradients and partial percolation at 5000 bar, resembling PF-like behavior. However, the underlying assumptions of PF theory—continuous solvent pathways and pressure transmission through water-filled pores—are not met under most conditions. Our results demonstrate that accurate modeling of reverse osmosis membranes must incorporate realistic mechanical boundary conditions to distinguish between transport mechanisms. For dense polyamide membranes supported by porous substrates, graphene-restrained simulations best reflect experimental setups and support the SD model as the dominant mechanism of water permeation.
molecular dynamics↗
Enhanced hindrance from phenyl outer side chains on nonfullerene acceptor enables unprecedented simultaneous enhancement in organic solar cell performances with 16.7% efficiency
Inner side-chain engineering on Y6 has been a proven successful in improving short-circuit current density (JSC) through fine-tuning aggregated structures of acceptors. However, it fails in tuning the lowest unoccupied molecular orbital level (LUMO) and open-circuit voltage (V OC ). In this paper, we turn to focus on engineering the outer side chains on the flanking thienothiophene units with 4-hexylphenyl (PhC6) and 6-phenylhexyl (C6Ph) chains. Use of PhC6 enhances the steric effect between the attached phenyl and the ending group, which in combination with the additional conjugation effect provided by the linking phenyl leads to upshifted energy levels and increased V OC as a result. Again, substitution with the bulkier PhC6 unprecedentedly improves film-morphology with reduced paracrystalline disorder and long period and increased root-mean-square composition variations as well, leading to increased electron and hole mobilities and suppressed monomolecular recombination with J SC and fill-factor (FF) simultaneously enhanced. The PM6:BTP-PhC6-based devices yield a higher efficiency value of 16.7% than the PM6:BTP-C6Ph-based one (15.5%). Furthermore, this study shows a conceptual advance in materials design towards reducing the conflict between V OC and J SC in binary blended organic solar cells, which can be achieved by introducing bulkier chains to twist the backbone and simultaneously enhance the packing order.
14 SOLAR ENERGY↗
Polysulfide regulation by defect-modulated Ta 3 N 5- x electrocatalyst toward superior room-temperature sodium-sulfur batteries
Resolving low sulfur reaction activity and severe polysulfide dissolution remains challenging in metal-sulfur batteries. Motivated by a theoretical prediction, herein, we strategically propose nitrogen-vacancy tantalum nitride (Ta 3 N 5-x ) impregnated inside the interconnected nanopores of nitrogen-decorated carbon matrix as a new electrocatalyst for regulating sulfur redox reactions in room-temperature sodium-sulfur batteries. Through a pore-constriction mechanism, the nitrogen vacancies are controllably constructed during the nucleation of Ta 3 N 5-x . Further, the defect manipulation on the local environment enables well-regulated Ta 5d-orbital energy level, not only modulating band structure toward enhanced intrinsic conductivity of Ta-based materials, but also promoting polysulfide stabilization and achieving bifunctional catalytic capability toward completely reversible polysulfide conversion. Moreover, the interconnected continuous Ta 3 N 5-x -in-pore structure facilitates electron and sodium-ion transport and accommodates volume expansion of sulfur species while suppressing their shuttle behavior. Due to these attributes, the as-developed Ta 3 N 5-x -based electrode achieves superior rate capability of 730 mAh g -1 at 3.35 A g -1 , long-term cycling stability over 2000 cycles, and high areal capacity over 6 mAh cm -2 under high sulfur loading of 6.2mgcm -2 . This work not only presents a new sulfur electrocatalyst candidate for metal-sulfur batteries, but also sheds light on the controllable material design of defect structure in hopes of inspiring new ideas and directions for future research.
25 ENERGY STORAGE↗
Predicting short-range order evolution in WTaCrVHf refractory high-entropy alloys
Short-range order (SRO) in multicomponent concentrated alloys affects their mechanical response. Hence, is paramount to understand how composition modifies the chemical ordering in the system to design materials with optimal properties. Here, in this work, we present a methodology to predict the SRO and thermodynamic properties in chemically complex systems and apply it to the WTaCrVHf quinary alloy. We observe that the addition of Hf significantly modifies the SRO, mainly at intermediate to low temperatures, matching experimental observations.
36 MATERIALS SCIENCE↗
Radiative cooling and thermoregulation in the earth’s glow
Efficient passive radiative cooling of buildings requires an unimpeded view of the sky. However, vertical facades of buildings mostly see terrestrial features that become broadband-radiative heat sources in the summer and heat sinks in the winter. The resulting summertime terrestrial heat gain by buildings negates or overwhelms their narrowband longwave infrared (LWIR) radiative cooling to space, while the wintertime terrestrial heat loss causes overcooling. We show that selective LWIR emitters on vertical building facades can exploit the differential transmittance of the atmosphere toward the sky and between terrestrial objects to achieve higher summertime cooling and wintertime heating than conventionally used broadband emitters. The impact of this novel and passive thermoregulation is comparable to that of painting dark roofs white and is achievable with both novel and commonplace materials. Our findings represent new and remarkable opportunities for materials design and untapped thermoregulation of entities ranging from buildings to human bodies.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Tunable Atomic Layer Deposition into Ultra-High-Aspect-Ratio (>60000:1) Aerogel Monoliths Enabled by Transport Modeling
Atomic layer deposition (ALD) modification of ultra-high-aspect-ratio structures (>10,000:1) is a powerful platform with applications in catalysis, filtration, and energy conversion. However, the deposition of conformal and tunable ALD coatings at these aspect ratios remains challenging, resulting in empirical tradeoffs between precursor utilization and reaction time. Here, we demonstrate tunable control of the ALD infiltration depth into an aerogel monolith (AM) and develop a reaction-diffusion model to accurately describe the coating process. Specifically, we investigate the ALD exposure time and precursor dose needed to conformally coat a silica AM with pore sizes of ~20 nm, a monolith thickness of ~2.5 mm, and aspect ratios exceeding 60,000:1. We demonstrate complete infiltration into the AM, which is quantified by elemental mapping. A reaction-diffusion model is developed, which accounts for multiple doses and precursor depletion in the ALD chamber during an exposure step. The experimentally validated model enables the prediction and tuning of infiltration depth into a tortuous, high-aspect-ratio structure such as an AM, allowing for the synthesis of rationally designed material architectures. Additionally, the model allows for co-optimization of the total deposition time and percentage of unreacted precursor, which are important for the manufacturability and sustainability of ALD processing. Lastly, we demonstrate that ultra-thin ALD Al 2 O 3 coatings can be used to stabilize silica AMs against structural degradation under high-temperature annealing conditions (700-800 °C), by limiting changes in surface area and monolith volume. As a result, this improved high-temperature stability has implications for numerous aerogel applications, including catalysis and thermal insulation.
14 SOLAR ENERGY↗
Map of the Zintl AM 2 Pn 2 Compounds: Influence of Chemistry on Stability and Electronic Structure
The AM 2 Pn 2 (A= Ca, Sr, Ba, Yb, Mg; M = Zn, Cd, Mg; and Pn = N, P, As, Sb, Bi) family of Zintl phases has been known as thermoelectric materials and has recently gained much attention for highly promising materials for solar absorbers in single-junction and tandem solar cells. In this paper, we will, from first principles, explore the entire family of AM 2 Pn 2 compounds in terms of their ground-state structure, thermodynamic stability, and electronic structure. We also perform photoluminescence spectroscopy on bulk powder and thin film samples to verify our results, including the first measurements of the band gaps of SrCd 2 P 2 and CaCd 2 P 2 . The AM 2 Pn 2 compounds exhibit broad stability, are mostly isostructural to CaAl 2 Si 2 (P$\overline{3}$m1), and cover a wide range of band gaps from 0 to beyond 3 eV. This could make them useful for a variety of purposes, for which we propose several candidates, such as CaZn 2 N 2 for tandem top cell solar absorbers and SrCd 2 Sb 2 and CaZn 2 Sb 2 for infrared detectors. By examining the band structures of the AM 2 Pn 2 , we find that Mg 3 Sb 2 has the most promise as a thermoelectric material due to several off-Γ valence band pockets, which are unique to it among the compositions studied here.
14 SOLAR ENERGY↗
Electronic Structure and Safety Insights into Prussian Blue Analog Cathode Behavior at Elevated Temperatures in Sodium-Ion Batteries
Prussian blue analogs (PBAs) represent promising cathode materials for sodium-ion batteries (SIBs) due to their high theoretical capacity, open framework structure, and use of earth-abundant elements. However, the high-temperature structural evolution, water content effects, and thermal safety of PBAs, particularly in charged states, remain poorly understood, hindering their practical deployment. Here, we investigate Na 2 Fe[Fe(CN) 6 ]·2H 2 O using thermogravimetric analysis (TGA), ex situ and in situ temperature-dependent X-ray absorption spectroscopy (XAS), and accelerated rate calorimetry (ARC). TGA and ex situ XAS confirm water loss between 150 and 200 °C, resulting in Fe 2+ oxidation, enhanced local symmetry, and uniform redox behavior that improves electrochemical performance. In situ XAS reveals irreversible structural changes above 240 °C, including ligand loss, Fe site distortion, and increased disorder, while ARC on charged electrodes shows minimal self-heating rates (<0.1 °C/min) up to 300 °C, indicating exceptional thermal stability without lattice oxygen release. These insights elucidate PBA thermal dynamics, demonstrating improved electrochemical performance of water-deficient PBAs and informing future material design and safety assessment for SIB applications.
batteries↗