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At least 199 records · Page 11

Metastable multimeric G-quadruplex 2′FY-RNA aptamers that selectively bind pyoverdines

Two 2′FY-RNA aptamers with distinct sequences were selected for specific binding to pyoverdine-Pf5 (PVD-Pf5), increasing chromophore fluorescence upon binding. They also recognized the peptide portion of pyoverdines, as shown by their differential specificity for related variants. Computational analysis and experimental data (NMM binding, CD spectra) identified G-quadruplex structures that were thermally metastable but reformed in the presence of PVD-Pf5. Further structural studies mainly with one aptamer revealed imino proton peaks in 1D H-NMR and pressure stability up to 2 kbar. Electrophoretic evidence identified dimeric G-quadruplexes formed by the 2′FY-RNA aptamers and their RNA equivalents. While cations were necessary for PVD-Pf5 binding, they were not required for G-quadruplex formation. Given the established role of G-quadruplexes as protein interaction sites, multimeric G-quadruplexes offer a potential framework for structure-based regulatory mechanisms in cellular RNAs. In addition to previously characterized multimeric G-quadruplexes, these aptamers contribute novel sequences that expand the repertoire of known multimeric G-quadruplexes.

2′FY-RNA↗

Electrochemical reduction of ammonia-captured CO 2 to CO over a nickel single-atom catalyst

Carbon reactive capture and conversion offers a sustainable route to valuable chemicals and fuels while aiding Green House Gas (GHG) reduction. Direct electrochemical conversion of capture solutions like bicarbonate avoids the energy demands of conventional CO 2 regeneration. Ammonium bicarbonate (NH 4 HCO 3 ) is particularly attractive due to its low decomposition temperature and ability to supply in situ CO 2 from dilute sources without requiring purified CO 2 . Meanwhile, single-atom catalysts (SACs) with nitrogen-coordinated metal sites further enhance CO 2 reduction efficiency using Earth-abundant materials. In this study, we demonstrate a nickel single-atom catalyst (Ni-SAC)-based electrolyzer that utilizes NH 4 HCO 3 as the CO 2 source, achieving significantly improved CO production performance compared to the conventional silver cathodes used in the CO 2 reduction reaction (CO 2 RR) to produce CO. The Ni-SAC cathode exhibited a Faradaic efficiency of 60.1% for CO production at −200 mA cm −2 , while the silver cathode achieved a Faradaic efficiency of only 2%, likely due to ammonium-induced poisoning. Furthermore, the integration of a customized microporous layer onto the electrode significantly increased the Faradaic efficiency from 64% to 83% at −100 mA cm −2 , emphasizing the crucial role of electrode structure optimization in enhancing CO selectivity. These findings demonstrate a sustainable and economically viable strategy for green CO production directly from CO 2 capture solutions.

30 DIRECT ENERGY CONVERSION↗

Developing reliable machine learning interatomic potential for Fe–Cr–Ni austenitic alloys

Gaining atomistic understanding of mechanical behavior of heat-resistant structural materials such as Fe–Cr–Ni-based alloys requires an approach with an accuracy close to density functional theory (DFT) that considers the intrinsic properties of the bulk lattice and important defects such as stacking faults, grain boundaries, and surfaces. This work aims to develop reliable machine learning interatomic potential (MLIAP) at cross-scale for Fe–Cr–Ni ternary alloys with a focus on the face-centered-cubic (fcc) solid solution structure. Leveraging the advantages of moment tensor potentials, which typically necessitate a relatively small training dataset and enable rapid calculations using the large-scale atomic/molecular massively parallel simulator package, we ensure the stability and accuracy of the trained potentials. Important defects such as stacking faults, grain boundaries, and surfaces for wide-range compositions are investigated. Structural, thermal, elastic, and defect properties are determined from molecular dynamics simulations comprising several thousand atoms, generated via canonical Monte Carlo simulations guided by the trained potential. The trained potential allows efficient atomic simulations of structural, thermal, and mechanical properties of fcc Fe–Cr–Ni solid solution alloys as a function of composition and temperature. Therefore, the MLIAP approach represents a major advancement from DFT calculations that are limited to small simulation sizes and traditional molecular dynamics simulations using relatively low accuracy potentials. Furthermore, this work outlines a practical foundation for further investigating the structural evolution and mechanical behavior of austenitic stainless steel and nickel-based alloys in a wide array of applications in extreme environments.

Crystal structure↗

Correlation of coercivity, microstructure, and surface defects in HDDR-processed Nd-Fe-B powders for bonded magnet applications

Hydrogenation-Disproportionation-Desorption-Recombination (HDDR) is an effective method for producing high coercivity, anisotropic powder from either fresh Nd-Fe-B alloy or recycled Nd-Fe-B magnets for use in bonded magnets. We investigated the impact of surface defects on the coercivity of HDDR-processed Nd-Fe-B using scanning electron microscopy (SEM), magnetic measurements, and micromagnetic simulations. We observed that coercivity decreases as particle size reduces, with SEM revealing surface defects and the detachment of Nd 2 Fe 14 B grains and Nd-rich phases from the particle surface. Micromagnetic simulations indicate that demagnetization initiates at the particle surface, where these defects are most concentrated, leading to reduced coercivity. The reduction in squareness of demagnetization curve, knee point field and coercivity for smaller HDDR particles is attributed to an increased specific surface area, which exhibits reduced nucleation field and weak domain wall pinning field during magnetization reversal. By addressing the role of surface defects in coercivity degradation, this study provides insights for improving both new powder production and recycling strategies, ultimately leading to enhanced performance of bonded magnets and contributing to more sustainable practices in the rare earth supply chain. One potential strategy to enhance the performance of HDDR Nd-Fe-B materials involves reducing the fraction of fine particles ($<$35 µm) and promoting the formation of grain boundary phases on particle surfaces.

Liu, Xubo B. [Ames Laboratory (AMES), Ames, IA (Un↗

Adaptive variational quantum dynamics simulations with compressed circuits and fewer measurements

The adaptive variational quantum dynamics simulation (AVQDS) method performs real-time evolution of quantum states using automatically generated parametrized quantum circuits that often contain substantially fewer gates than Trotter circuits. Here we report an improved version of the method, which we call AVQDS(T), by porting the tiling efficient trial circuits with rotations implemented simultaneously technique. The algorithm adaptively adds layers of disjoint unitary gates to the ansatz circuit so as to keep the McLachlan distance, a measure of the accuracy of the variational dynamics, below a fixed threshold. Here we perform benchmark noiseless AVQDS(T) simulations of quench dynamics in local spin models and compare with an alternative adaptive variational approach on quantum resource requirement. Quantum dynamical simulations implementing realistic noise channels are also reported. Finally, we propose a way to substantially alleviate the measurement overhead of AVQDS(T) while maintaining high accuracy by synergistically integrating quantum circuit calculations on quantum processing units with classical calculations using, e.g., tensor networks to evaluate the quantum geometric tensor. We showcase that this approach enables AVQDS(T) to deliver more accurate results than simulations using a fixed ansatz of comparable final depth for a significant time duration with fewer quantum resources.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Superconducting dome and structural changes in LaRu 3 ⁢Si 2 under pressure

LaRu 3 ⁢Si 2 is of current research interest as a kagome metal with a superconducting transition temperature, 𝑇 𝑐 ∼7 K, and higher-temperature charge density wave orders. Here we report on electrical transport and x-ray diffraction measurements on LaRu 3 ⁢Si 2 under pressure up to 65 GPa and 35 GPa, respectively. The superconducting transition temperature 𝑇 𝑐 first gets slightly enhanced and reaches a maximum ∼8.7 K at ∼8.5 GPa. With further applied pressure, 𝑇 𝑐 is initially gradually suppressed, then more rapidly suppressed, followed by gradual suppression, revealing a superconducting dome. Two possible pressure-induced structural phase transitions are also observed at room temperature, from the original hexagonal phase to another hexagonal structure above ∼11.5 GPa, and further to a structure with lower symmetry above ∼23.5 GPa. These transition pressures roughly correlate with features found in our pressure-dependent transport data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Enhancing stability, magnetic anisotropy, and coercivity of manganese aluminum: Machine learning, ab initio , and micromagnetic modeling

The binary manganese aluminum (MnAl) alloy with L⁢1 0 crystal structure is a promising rare earth (RE) element-free permanent magnetic material because of its exceptional magnetic properties. However, experimentally synthesizing it in a stable bulk form is extremely challenging. Here, in this study, an alternative method of stabilizing the material, a pathway for experimental synthesis and validation, is proposed and theoretically verified. This is done by partially substituting Mn and Al sites with Fe and Ni and identifying its enhanced phase stability, saturation magnetization density, magnetic anisotropy, and coercivity from density functional theory (DFT), machine learning (ML) crystal graph convolution neural network (CGCNN), and micro-magnetic modeling. When considering a fixed 50% Ni, the magnetic anisotropy increases with the increasing Fe content but decreases the formation energy. The calculated formation energies, elastic constants, and phonon frequencies demonstrate that the binary and quaternary compositions are stable. Most importantly, in 50% Fe and Ni-substituted-equiatomic phase, magnetic anisotropy constants and saturation magnetization density increase by 56% and 23% as compared to the MnAl. Further, the coercivity of the equiatomic phase predicted with micro-magnetic modeling is higher by 17% than the parent compound.

Bhandari, Churna [Ames National Laboratory, and Io↗

Performance evaluations of signed and unsigned noisy approximate quantum Fourier arithmetic

The Quantum Fourier Transform (QFT) grants competitive advantages, especially in resource usage and circuit approximation, for performing arithmetic operations on quantum computers, and offers a potential route toward a numerical quantum-computational paradigm. In this paper, we utilize efficient techniques to implement QFT-based integer addition and multiplications. These operations are fundamental to various quantum applications including Shor’s algorithm, weighted-sum optimization problems in data processing and machine learning, and quantum algorithms requiring inner products. We carry out performance evaluations of these implementations based on IBM’s superconducting-qubit architecture using different compatible noise models. We isolate the sensitivity of the component quantum circuits on both one-/two-qubit gate error rates, and the number of the arithmetic operands’ superposed integer states. We analyze performance and identify the most effective approximation depths for unsigned quantum addition and quantum multiplication within the given context. We then perform a similar analysis of signed addition and compare to the unsigned results. We observe significant dependency of the optimal approximation depth on the degree of machine noise and the number of superposed states in certain performance regimes. Finally, we elaborate on the algorithmic challenges—relevant to signed, unsigned, modular and non-modular versions—that could also be applied to current implementations of QFT-based subtraction, division, exponentiation, and their potential tensor extensions. Here, we analyze the performance trends in our results and speculate on possible future developments within this computational paradigm.

Computational models↗

Fluorinated ionic liquids as gas chromatographic stationary phases for the separation of volatile per- and polyfluoroalkyl substances

Background Here, the production of fluorinated organic compounds in the manufacturing, semiconductor, and pharmaceutical industries has increased exponentially over the past decade. This rapid growth has created an urgent need for efficient chromatographic platforms capable of selectively separating these compounds from complex mixtures, not only to support industrial quality control and waste management practices, but also to enable reliable environmental monitoring of volatile fluorinated contaminants. Conventional GC stationary phases lack the fluorophilic interactions needed for highly fluorinated analytes. Consequently, there is a clear demand for specialized stationary phases designed to improve chromatographic retention and selectivity for these compounds. Results Three stationary phases composed of fluorinated ionic liquids (ILs) with varied extent of fluorination were prepared to study fluorophilic interactions with fluorinated/non-fluorinated probe molecules by gas chromatography (GC). IL stationary phases featuring linear and branched perfluoroalkyl moieties, as well as a branched alkyl moiety, were systematically investigated. Chromatographic performance was examined using fluorinated compounds and their hydrocarbon analogs, including CF 3 -substituted aromatics, aliphatic alcohols, fluorotelomer alcohols (FTOHs), and perfluoroalkenes. Measurements on 5 m and 20 m columns revealed that the IL possessing branched alkyl provided stronger dispersive and hydrogen bonding interactions toward non-fluorinated aromatic and long-chain alcohols, whereas the fluorinated ILs enhanced retention of highly fluorinated FTOHs and perfluorodecene. Comprehensive two-dimensional GC (GC × GC), using a nonpolar primary column coupled with secondary columns featuring cross-bonded poly(trifluoropropylmethyl siloxane) (Rtx-200 ms), the branched fluorinated IL, or the branched non-fluorinated IL, highlighted complementary selectivity with the branched fluorinated IL providing the strongest interactions with fluorinated analytes. Significance These results demonstrate that fluorinated IL stationary phases are promising alternatives to conventional polysiloxane stationary phases for improving the separation of per- and polyfluoroalkyl substances and related fluorinated compounds. By correlating IL structure with fluorophilic interactions, this work establishes design principles for GC stationary phases that enable enhanced selectivity for highly fluorinated analytes while maintaining complementary interactions with non-fluorinated compounds.

Comprehensive two-dimensional GC↗

DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys

Designing ductile materials for extreme environments such as fusion reactors requires a deep understanding of the complex interplay between electronic structure, mechanical stability, and wide compositional space. Here, in this work, we introduce DuctGPT, a physics-informed, GPT-powered machine learning platform that enables rapid and accurate prediction of ductility across a wide range of refractory multi-principal element alloys (MPEAs). Trained on both experimental and high-fidelity computational data, DuctGPT integrates descriptors such as density of states at the Fermi level, elastic constants, and valence electron concentration to capture the fundamental mechanisms governing ductile versus brittle behavior. Using this framework, we screen over 1000 compositions in of body-centered cubic (BCC) MPEAs, including two new alloy classes, i.e., NbTa-rich (NbTa $>$ 50 at.%) NbTa-Ti-V and W-rich ($>$ 50 at.%) W-Ti-V MPEAs, to rapidly identify promising alloy compositions with enhanced ductility. Validation against experimental data confirms the model's ability to predict ductility with high fidelity and low uncertainty. By leveraging conversational AI and robust physical modeling, DuctGPT provides a blueprint for the next generation of alloy design assistants, enabling human-AI collaboration in the accelerated discovery of ductile, high-performance materials for fusion, aerospace, and advanced manufacturing.

AI/ML↗

Hydrogenolysis Versus Hydrocracking for Polyolefin Upcycling

Global plastic production has reached 413.8 million metric tons in 2024 and is forecasted to surpass 1.2 billion metric tons by 2050. Polyolefins, mainly polyethylene (PE) and polypropylene (PP), dominate single-use packaging and account for approximately 55% of global plastic waste. The chemical inertness that makes these materials desirable for commercial applications also renders them persistent in the environment. Current recycling technologies have proven to be insufficient to divert plastic waste from landfills or environmental loss due to technical limitations and poor economic incentives. Conventional mechanical recycling is a form of downcycling, in which the polymer remelting process results in products with inferior material properties and reduced market value. Pyrolysis, a thermochemical route used for the chemical recycling of plastic wastes into refinery feedstock, requires severe conditions, typically 400–600 °C in an oxygen-free environment. The high temperature drives up energy costs and produces a wide range of poorly defined products, including undesirable light gases and heavy tars that pose challenges for downstream processing. As an alternative, catalytic chemical recycling offers a promising route for converting waste polyolefins back into value-added hydrocarbons—such as fuels, lubricant base oils, and other chemical feedstocks—at temperatures typically below 300 °C. This opinion article focuses on two dominant pathways in heterogeneous catalysis that are used to cleave the C–C bonds of polyolefins: hydrogenolysis and hydrocracking. Both catalytic pathways have the potential to selectively convert polyolefin waste into valuable fuels and chemical feedstocks under mild conditions. Notably, while hydrocracking primarily yields branched hydrocarbon products, hydrogenolysis predominantly produces linear hydrocarbons. Here, we compare the mechanisms and catalyst designs for hydrocracking and hydrogenolysis, analyze critical technical challenges from catalyst stability to process engineering, and provide an outlook on how these complementary pathways can be used to repurpose plastic waste into valuable products.

Zhang, Ruoxi [Iowa State Univ., Ames, IA (United S↗

Critical minerals lists for low-carbon transitions: Reviewing their structure, objectives, and limitations

Critical minerals lists have flourished in the past decade, in particular linked to the importance of critical minerals for low-carbon transitions. We identified 27 critical minerals or materials lists across 15 countries and the European Union (EU). These lists are designed to attract public and private attention and investments to secure both domestic and foreign supplies. This review article fills a gap in the existing literature by analyzing the ways in which these lists are defined and utilized by countries engaged in a mineral rush. We focus our attention on three categories of minerals – battery minerals, platinum-group metals (PGMs), and rare earth elements (REEs) that are particularly important to energy transitions. We situate this research in the broader legal and administrative developments that have driven critical minerals policies in the past decade. We provide an in-depth analysis of the commonalities and variations in the raw materials included in these lists, and identify six core limitations of critical minerals lists: (1) unclear links between criticality assessments and mineral prioritization (2) failure to account for the full mineral value-chain; (3) limited strategic alignment between allied nations; (4) limited flexibility in dynamic environments (5) limited consideration for recycling and by-product sourcing; and (6) reliance on incomplete reserve and resource data.

Battery minerals↗

Theory meets experiment: Insights into structure and magnetic properties of Fe 1-x Ni x B alloy

Here, we studied the structural and magnetic properties of the solid solution Fe 1-x Ni x B through theoretical and experimental approaches. Powder X-ray diffraction, X-ray Pair Distribution Function analysis, and energy dispersive X-ray spectroscopy reveal that the Fe 1-x Ni x B solid solution crystallizes in the β-FeB structure type up to x = 0.6–0.7 and exhibits anisotropic unit cell volume contraction with increasing Ni concentration. Magnetic measurements showed a transition from ferromagnetism to paramagnetism around x = 0.7. For x = 0.5, the low (< 0.3 μ B ) magnetic moments suggest itinerant magnetism despite the relatively high Curie temperature (up to 225 K). Theoretical calculations indicated different types of magnetic orderings depending on the Fe/Ni atomic order, with the antiferromagnetic state being stable for ordered FeNiB 2 , whereas the ground state is ferromagnetic for the disordered alloy. Calculations also predicted the coexistence of low- and high-spin states in Fe atoms around the composition with x = 0.5, in line with the experimental evidence from 57 Fe Mössbauer spectroscopy. The two magnetically distinct Fe sites for x = 0.3, 0.4, and 0.5 observed by 57 Fe Mössbauer spectroscopy can also be interpreted as two magnetically different regions or clusters. The formation of these clusters could affect the critical behavior near a quantum magnetic transition based on a potential ferromagnetic quantum critical point identified computationally and experimentally near x = 0.64. This work highlights the complex interplay between structure and magnetism in Fe 1-x Ni x B alloys, suggesting areas for future research on quantum critical behavior.

Bhaskar, Gourab [Iowa State Univ., Ames, IA (Unite↗

Silyl Hot-Injection Versus Thiocyanate Heat-Up Synthesis of Chalcohalides: Pushing the Size and Composition Envelope

Chalcohalide semiconductors are rapidly gaining traction as stable, biocompatible materials for energy conversion applications. While the solid-state synthesis of bulk chalcohalides is relatively well-developed, the colloidal chemistry of these materials is still in its early stages. Colloidal semiconductors are often advantageous in device fabrication due to the cost effectiveness of solution processing. Thus, we aim to increase the utility of chalcohalides in device fabrication by establishing solution phase chemistry of promising compositions. We show that silyl hot-injection is a versatile and effective method of making colloidal PnChI (Pn = Sb, Bi; Ch = S, Se) and Sn 2 PnS 2 I 3 (Pn = Sb, Bi) chalcohalides of tunable sizes and compositions. Furthermore, we demonstrate the preparation of mixed-pnictide chalcohalides through direct hot-injection and/or postsynthetic cation exchange, the latter being one of the few reported instances in chalcohalides. Additionally, we use the thiocyanate heat-up approach in combination with density functional theory to study halide mixing in quaternary tin chalcohalides. By pushing the limits of each synthetic technique, we have designed more soluble chalcohalides with tunable compositions while also gaining a better understanding of the efficacy of each procedure in respect to thin film and subsequent device fabrication. In addition to size and composition tuning, silyl hot-injection can help facilitate the future development and wide-scale application of chalcohalide-based devices by expanding the selection of solution-processable chalcohalides.

halogens↗

In Silico Design of Methyl-Driven Overhauser Dynamic Nuclear Polarization Agents

Overhauser effect (OE) dynamic nuclear polarization (DNP) has drawn attention owing to its enhanced performance at ultrahigh magnetic fields. The lack of design principles has, nevertheless, limited the development of OE polarizing agents when compared to those used for cross-effect DNP. Here, we measured the 19 F OE DNP performance of a series of CF 3 -functionalized Blatter-type radicals. Using density functional theory calculations, we accurately predict the methyl-driven OE performance, paving the way for computer-aided design of optimized OE DNP polarizing agents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photooxidation of Organic Sulfide Enhanced by Heavy Atom Effect in Porphyrin Metal–Organic Frameworks with a Sea Topology

The photoactivity of three porphyrin-based metal-organic frameworks (PMOFs) incorporating Al, Ga, and In nodes was systematically evaluated using the photooxidation of an organic sulfide (2-chloroethyl ethyl sulfide, or CEES; a mustard gas simulant). Faster photodegradation of CEES was observed for PMOFs with heavier metal nodes, placing In-PMOF as the most efficient photocatalyst in the series. Guided by this insight, we developed CSLA-10, a MOF integrating In nodes and Sn-doped porphyrin linker to synergistically amplify heavy-atom effects at both the nodes and ligand levels. CSLA-10 exhibited the fastest reported CEES photooxidation to date, achieving a half-life of 38 s in methanol under blue LED irradiation. When grafted onto textiles, CSLA-10 enabled solvent-free CEES degradation in air/O 2 with a half-life of 2.7 min and complete conversion within 7 min, representing the most rapid full degradation reported under solvent-free conditions. Furthermore, this work establishes a dual heavy-atom strategy for enhancing intersystem crossing and singlet oxygen generation in porphyrin MOFs, providing a rational design principle for next-generation photocatalysts for the degradation of toxic organic sulfides.

Metal-organic frameworks↗

Interconnected nanoconfining pore networks enhance catalyst CO 2 interaction in electrified reactive capture

Systems that sequentially capture and upgrade CO 2 from air to fuels/fuel-intermediates, such as syngas and ethylene, rely on an energy-intensive CO 2 release process. Electrified reactive capture systems transform CO 2 obtained directly from carbonate capture liquid into products. Previous reactive capture systems show a decline in Faradaic efficiencies (FE) at current densities above 200 mA/cm 2 . Here we show the chemical origins of this problem, finding that prior electrocatalyst designs failed to arrest, activate, and reduce in situ-generated CO 2 (i-CO 2 ) before it traversed the catalyst layer and entered the tailgas stream. We develop a templated synthesis to define pore structures and the sites of Ni single atoms, and find that carbon-nitrogen-based nanopores are effective in accumulating i-CO 2 via short-range, non-electrostatic interactions between CO 2 molecules and the nanochannel walls. These interactions confine and enrich i-CO 2 within the pores, enhancing its binding and activation. We report as a result carbonate electrolysis at 300 mA/cm 2 with FE to CO of 50% ± 3%, and with <1% CO 2 in the tailgas outlet stream. This corresponds to a projected energy efficiency (EE) to 2:1 syngas of 46% at 300 mA/cm 2 when H 2 is added using a water electrolyzer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗