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High-Throughput Analysis of Materials for Chemical Looping Processes
Chemical looping is a promising approach for improving the energy efficiency of many industrial chemical processes. However, a major limitation of modern chemical looping technologies is the lack of suitable active materials to mediate the involved subreactions. Identification of suitable materials has been historically limited by the scarcity of high-temperature (>600 °C) thermochemical data to evaluate candidate materials. An accuratethermodynamic approach is demonstrated here to rapidly identify active materials which is applicable to a wide variety of chemical looping chemistries. Application of this analysis to chemical looping combustion correctly classifies 17/17 experimentally studied redox materials by their viability and identifies over 1300 promising yet previously unstudied active materials. This approach is further demonstrated by analyzing redox pairs for mediating a novel chemical looping process for producing pure SO2 from raw sulfur and air which could provide a more efficient and lower emission route to sulfuric acid. 12 promising redox materials for this process are identified, two of which are supported by previous experimental studies of their individual oxidation and reduction reactions. This approach provides the necessary foundation for connecting process design with high-throughput material discovery to accelerate the innovation and development of a wide range of chemical looping technologies.
Observation of two cascading screening processes in an iron-based superconductor
Understanding how renormalized quasiparticles emerge in strongly correlated electron materials provides a challenge for both experiment and theory. It has been predicted that distinctive spin and orbital screening mechanisms drive this process in multiorbital materials with strong Coulomb and Hund’s interactions. Here, we provide the experimental evidence of both mechanisms from angle- resolved photoemission spectroscopy on RbFe 2 As 2 . We observe that the emergence of low-energy Fe 3d xy quasiparticles below 90K coincides with spin screening. A second process changes the spectral weight at high energies up to room temperature. Supported by theoretical calculations we attribute it to orbital screening of Fe 3d atomic excitations. These two cascading screening processes drive the temperature evolution from a bad metal to a correlated Fermi liquid.
Multiple monoenergetic gamma radiography (MMGR) with a compact superconducting cyclotron
Smuggling of special nuclear materials and nuclear devices through borders and ports of entry constitutes a major risk to global security. Technologies are needed to reliably screen the flow of commerce for the presence of high-Z materials such as uranium and plutonium. Here, we present an experimental proof-of-concept of a technique that uses inelastic (p,p') nuclear reactions to generate monoenergetic photons, which provide means to measure the areal density and the effective-Z (Z eff ) of an object with an accuracy surpassing that achieved by current methods. We use an ION-12 SC superconducting 12 MeV proton cyclotron to produce 4.4, 6.1, 6.9, and 7.1 MeV photons from a variety of nuclear reactions. Using these photons in a transmission mode, we show that we are able to accurately reconstruct the areal densities and Zeff of a test object. This methodology could enable mobile applications to screen commercial cargoes with high material specificity, providing a means of distinguishing common cargo materials from high-Z materials that include uranium and plutonium.
Exploiting the fraternal twin nature of thermoelectrics and topological insulators in Zintl phases as a tool for engineering new efficient thermoelectric generators
This review article presents a radical overview of the rich chemistry and physics of Zintl phases as it relates to their interesting structure–property relationships. In particular, it unveils the evolution of topological insulator (TI) and thermoelectric (TE) properties in Zintl materials as having a common origin and as such are driven by the same materials properties ranging from a narrow band gap to a strong spin-orbit coupling effect. To this end, excellent TE properties are ubiquitous in many TIs and because of the ever-increasing interest in the studies of topological properties of matter, several robust theoretical frameworks now exist to provide us with additional intuitive nature and understanding of this exotic phase of matter. Here, this invariably has also led to the screening of tens of thousands of materials for the presence of nontrivial topology using the combined predictive power of machine learning and ab-initio first-principles calculations. On the other hand, studies on TE materials are still largely based on some sort of hit-and-miss approach. Here we leveraged on the similar materials features and intersection between TE and TIs and review several Zintl materials that are already identified as TIs and present how exploiting their bulk and surface states properties can be harnessed for developing highly efficient TE materials for practical purposes.
Spontaneous Gap Opening and Potential Excitonic States in an Ideal Dirac Semimetal Ta 2 Pd 3 Te 5
The opening of an energy gap in the electronic structure generally indicates the presence of interactions. In materials with low carrier density and short screening length, long-range Coulomb interaction favors the spontaneous formation of electron-hole pairs, so called excitons, opening an excitonic gap at the Fermi level. Excitonic materials host unique phenomena associated with pair excitations. However, there is still no generally recognized single-crystal material with excitonic order, which is, therefore, awaited in condensed matter physics. Here, we show that excitonic states may exist in the quasi-one-dimensional material Ta 2 Pd 3 Te 5 , which has an almost ideal Dirac-like band structure, with the Dirac point located exactly at the Fermi level. We find that an energy gap appears at 350 K, and it grows with decreasing temperature. The spontaneous gap opening is absent in a similar material Ta 2 Ni 3 Te 5 . Intriguingly, the gap is destroyed by the potassium deposition on the crystal, likely due to extra-doped carriers. Furthermore, we observe a pair of in-gap flat bands, which is an analog of the impurity states in a superconducting gap. All these observations can be properly explained by an excitonic order, providing Ta 2 Pd 3 Te 5 as a new and promising candidate realizing excitonic states. Published by the American Physical Society 2024
A Data-Driven Framework for Predicting the Sorting and Screening Performance of an Integrated Biomass Feedstock Preprocessing System
The characteristics of mechanically sorted and screened lignocellulosic biomass, such as the mass contents of corn stover anatomical fractions (leaves, husks, stalks, cobs, etc.), can be used to calculate the intermediate feedstock quality attributes “yield” and “purity” that indicate the conversion efficiency of biocrude. No prior study has investigated the correlations from the characteristics of raw biomass and preprocessing unit operation parameters to those intermediate feedstock quality attributes. This work presents a data-driven framework for assessing and predicting the intermediate feedstock quality attributes in an integrated biomass feedstock preprocessing system. Our study used corn stover as a typical type of herbaceous biomass because of its abundance in the U.S. It began with data acquisition of moisture content, particle size distribution, and anatomical fractions of the materials after each unit operation in the system. The objective of this preprocessing system is to minimize husks and leaves and maximizing cobs and stalks by mechanically separating the materials into three streams via disc screen and air separator. Prototype neural network models were then developed to evaluate the feasibility of predicting process outcomes based on measurable parameters. It is found that incorporating physical constraints into these prediction models significantly enhances the accuracy of the predicted yield and purity against the ground truth data. The experimental data and model predictions indicate that decreasing throughput increases purity, while higher throughput results in lower purity. Finally, an optimization problem was introduced to search optimal combinations of feed material properties and preprocessing unit operation parameters, as the intermediate feedstock quality attributes – yield and purity, appeared to be competing factors. The study also suggests the continual need to improve the data-driven framework’s predictability by incorporating more accurate physical models to describe the dynamics in the preprocessing units such as the air separator.
Deep potential generation scheme and simulation protocol for the Li 10 GeP 2 S 12 -type superionic conductors
We report solid-state electrolyte materials with superior lithium ionic conductivities are vital to the next-generation Li-ion batteries. Molecular dynamics could provide atomic scale information to understand the diffusion process of Li-ion in these superionic conductor materials. Here, we implement the deep potential generator to set up an efficient protocol to automatically generate interatomic potentials for Li 10 GeP 2 S 12 -type solid-state electrolyte materials (Li 10 GeP 2 S 12 , Li 10 SiP 2 S 12 , and Li 10 SnP 2 S 12 ). The reliability and accuracy of the fast interatomic potentials are validated. With the potentials, we extend the simulation of the diffusion process to a wide temperature range (300 K–1000 K) and systems with large size (~1000 atoms). Important technical aspects such as the statistical error and size effect are carefully investigated, and benchmark tests including the effect of density functional, thermal expansion, and configurational disorder are performed. The computed data that consider these factors agree well with the experimental results, and we find that the three structures show different behaviors with respect to configurational disorder. Our work paves the way for further research on computation screening of solid-state electrolyte materials.
High-Intensity UV Exposure for the Rapid Screening of Silicon Photovoltaic Architectures
Advanced Si photovoltaic architectures incorporate different materials and processing pathways that influence degradation modes. Ultraviolet-induced degradation (UVID) is an understudied degradation mode for advanced cell architectures and is of increasing concern to industry due to growing adoption of UV-transparent encapsulation and bifacial technologies. In order to adopt new and evolving technologies confidently, novel component materials and processing techniques must be evaluated and designed for long-term stability, in addition to the conventional design focus on efficiency. In this work, a study protocol framework is presented for the rapid screening of unencapsulated devices against UVID. Unencapsulated passivated emitter rear contact (PERC) and tunnel oxide passivated contact (TOPCon) devices were aged under different UV irradiance intensities and measured via conventional nondestructive electrical characterization methods to assess performance degradation. Based on the results, protocol efficacy and recommendations for further study are discussed. As a result, this work is part of a broader effort to develop rapid screening processes that cut across architectures and exposure conditions to aid module manufacturers in vetting new materials choices for long-term stability.
Opening twisted polymer chains for simultaneously high printability and battery fast-charge
Fast-charging is key to the widespread adoption of battery-based electric vehicles. However, improving fast-charging through architecture optimization is expensive. To reduce costs and expand to commercialization, we applied roll-to-roll screen printing technology to create channels and decrease the tortuosity of electrodes. For the first time, this work successfully opened twisted polymer chains within high-solid-content inks to improve their screen printability and battery performance of as-printed electrodes. With LiNi 0.6 Mn 0.2 Co 0.2 O 2 as active materials, the 60% solid content ink presents superior screen printability after opening the twisted binder chains. As-printed electrode exhibits 33% higher charge capacity at 6 C than printed electrode with chains twisted ink at mass loading of 6.5 mg/cm 2 . Furthermore, coarse-grained molecular dynamics simulations are performed to study the underlying mechanism systematically. In conclusion, the new ink preparation procedure provides a scalable, effective strategy for manufacturing screen-printable battery ink and promotes screen-printed electrode technology.
Development of Porous Crystalline Materials for Selective Binding of O 2 from Air
Porous materials that take advantage of different chemisorptive behaviors of O 2 and N 2 could be an effective alternative to approaches based on physisorption for this important separation. Recently, the tetra-nuclear cobalt complex [(Co(III) 2 (bpbp)O 2 ) 2 bdc](PF 6 ) 4 (CSD code: GAMVIB; bpbp – = 2,6-bis(N,N-bis(2-pyridylmethyl)aminomethyl)-4-tert-butylphenolato; bdc 2– = 1,4-benzenedicarboxylato) was shown to have potential for O 2 /N 2 separations based on this concept. This observation raises the question of what other known materials have similar properties. Here, we combine structure screening with a high-throughput periodic density functional theory (DFT) workflow to investigate O 2 and N 2 adsorption in materials from validated crystal structure databases (e.g., CoRE-MOF database and CSD database). These calculations identify multiple materials that have similar di-Co clusters to GAMVIB that are predicted to selectively bind O 2 over N 2 , and suggest design rules that can be used to tune the O 2 and N 2 affinities in materials of this kind.
Pareto Optimization of Oligomer Polarizability and Dipole Moment Using a Genetic Algorithm
High-performance electronic components are highly sought after in order to produce increasingly smaller and cheaper electronic devices. Drawing inspiration from inorganic dielectric materials, in which both polarizability and polarization contribute, organic materials can also maximize both. For a large set of small molecules drawn from PubChem, a Pareto-like front appears between the polarizability and dipole moment, indicating the presence of an apparent trade-off between these two properties. We tested this balance in π-conjugated materials by searching for novel conjugated hexamers with simultaneously large polar- izabilities and dipole moments with potential use for dielectric materials. Using a genetic algorithm (GA) screening technique in conjunction with an approximate density functional tight-binding method for property calculations, we were able to efficiently search chemical space for optimal hexamers. Given the scope of chemical space, using the GA technique saves considerable time and resources by speeding up molecular searches compared to a systematic search. Here, we also explored the underlying structure–function relationships, including sequence and monomer properties, that characterize large polarizability and dipole moment regimes.
New Directions for Thermoelectrics: A Roadmap from High‐Throughput Materials Discovery to Advanced Device Manufacturing
Thermoelectric materials, which can convert waste heat into electricity or act as solid‐state Peltier coolers, are emerging as key technologies to address global energy shortages and environmental sustainability. However, discovering materials with high thermoelectric conversion efficiency is a complex and slow process. The emerging field of high‐throughput material discovery demonstrates its potential to accelerate the development of new thermoelectric materials combining high efficiency and low cost. The synergistic integration of high‐throughput material processing and characterization techniques with machine learning algorithms can form an efficient closed‐loop process to generate and analyze broad datasets to discover new thermoelectric materials with unprecedented performances. Meanwhile, the recent development of advanced manufacturing methods provides exciting opportunities to realize scalable, low‐cost, and energy‐efficient fabrication of thermoelectric devices. This review provides an overview of recent advances in discovering thermoelectric materials using high‐throughput methods, including processing, characterization, and screening. Advanced manufacturing methods of thermoelectric devices are also introduced to realize the broad impacts of thermoelectric materials in power generation and solid‐state cooling. In the end, this article also discusses the future research prospects and directions.
Alkali‐Ion‐Assisted Activation of ε‐VOPO 4 as a Cathode Material for Mg‐Ion Batteries
Abstract Rechargeable multivalent‐ion batteries are attractive alternatives to Li‐ion batteries to mitigate their issues with metal resources and metal anodes. However, many challenges remain before they can be practically used due to the low solid‐state mobility of multivalent ions. In this study, a promising material identified by high‐throughput computational screening is investigated, ε‐VOPO 4 , as a Mg cathode. The experimental and computational evaluation of ε‐VOPO 4 suggests that it may provide an energy density of >200 Wh kg −1 based on the average voltage of a complete cycle, significantly more than that of well‐known Chevrel compounds. Furthermore, this study finds that Mg‐ion diffusion can be enhanced by co‐intercalation of Li or Na, pointing at interesting correlation dynamics of slow and fast ions.
Machine-Learning-Driven Discovery of Water Splitting BaFe 2 O 4 and Human-in-the-Loop Improvement via Al-Substitution for Increased Thermal Stability
Thermochemical hydrogen (TCH) production offers a promising method for converting thermal energy into hydrogen fuel through heat-driven redox cycles of metal oxides. Here, in this work a defect graph neural network (dGNN) was used to predict oxygen vacancy formation energies ΔH V O combined with Materials Project predictions of oxygen chemical potential stability to screen candidate oxides via high-throughput database analysis. BaFe 2 O 4 was identified as a promising material for experimental validation based on its predicted ΔH V O , oxygen chemical potential stability range, and potential for tunable substitutions to improve thermal properties. Experimental validation using thermogravimetric analysis (TGA), stagnation flow reactor (SFR), X-ray diffraction (XRD), and electron microscopy confirmed positive water-splitting behavior but also revealed limitations in thermal stability under aggressive reduction conditions. To address this, a human-in-the-loop modification strategy was employed introducing Al substitution in BaFe 2–x Al x O 4 ; this modification improves thermal stability, alters the crystal structure and enhances overall performance. These results demonstrate a combined computational and experimental workflow in which machine learning accelerates identification of promising candidates, while targeted experimental design enables optimization of functional performance. This approach advances the development of robust, cost-effective TCH materials and highlights the importance of integrating data-driven discovery with human-guided materials design in paving the way for scalable hydrogen production technologies.
Electronic Structure and Stacking Arrangement of Tungsten Disulfide at the Gold Contact
There is an intensive effort to control the nature of attractive interactions between ultrathin semiconductors and metals and to understand its impact on the electronic properties at the junction. In this work, we present a photoelectron spectroscopy study on the interface between WS 2 films and gold, with a focus on the occupied electronic states near the Brillouin zone center (i.e., the Γ point). To delineate the spectra of WS 2 supported on crystalline Au from the suspended WS 2 , we employ a microscopy approach and a tailored sample structure, in which the WS 2 /Au junction forms a semi-epitaxial relationship and is adjacent to suspended WS 2 regions. The photoelectron spectra, as a function of WS 2 thickness, display the expected splitting of the highest occupied states at the Γ point. In multilayer WS 2 , we discovered variations in the electronic states that spatially align with the crystalline grains of underlying Au. Corroborated by density functional theory calculations, we attribute the electronic structure variations to stacking variations within the WS 2 films. We propose that strong interactions exerted by Au grains cause slippage of the interfacing WS 2 layer with respect to the rest of the WS 2 film. Our findings illustrate that the electronic properties of transition metal dichalcogenides, and more generally 2D layered materials, are physically altered by the interactions with the interfacing materials, in addition to the electron screening and defects that have been widely considered.
A high-throughput and data-driven computational framework for novel quantum materials
Two-dimensional layered materials, such as transition metal dichalcogenides (TMDs), possess an intrinsic van der Waals gap at the layer interface, allowing for remarkable tunability of the optoelectronic features via external intercalation of foreign guests such as atoms, ions, or molecules. Herein, we introduce a high-throughput, data-driven computational framework for the design of novel quantum materials derived from intercalating planar conjugated organic molecules into bilayer transition metal dichalcogenides and dioxides. By combining first-principles methods, material informatics, and machine learning, we characterize the energetic and mechanical stability of this new class of materials and identify the fifty (50) most stable hybrid materials from a vast configurational space comprising ∼105 materials, employing intercalation energy as the screening criterion.