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At least 1,171 records · Page 65

A type-I van der Waals heterostructure formed by monolayer WS 2 and trilayer PdSe 2

Two-dimensional (2D) heterostructures, formed by stacking 2D semiconductors through the van der Waals force, have been extensively studied recently. However, the majority of the heterostructures discovered so far possess type-II interfaces that facilitate interlayer charge separation. Type-I interfaces, on the other hand, confine both electrons and holes in one layer, which is beneficial for optical applications that utilize electron–hole radiative recombination. So far, only a few type-I 2D heterostructures have been achieved, which has limited the construction of multilayer heterostructures with sophisticated band landscapes. Here, we report experimental evidence of a type-I interface between monolayer WS 2 and trilayer PdSe 2 . Two-dimensional PdSe 2 has emerged as a promising material for infrared optoelectronic and other applications. We fabricated the heterostructure by stacking an exfoliated monolayer WS 2 flake on top of a trilayer PdSe 2 film, synthesized by chemical vapor deposition. Photoluminescence spectroscopy measurements revealed that the WS 2 exciton peak is significantly quenched in the heterostructure, confirming efficient excitation transfer from WS 2 to PdSe 2 . Femtosecond transient absorption measurements with various pump/probe configurations showed that both electrons and holes photoexcited in the WS 2 layer of the heterostructure can efficiently transfer to PdSe 2 , while neither type of carriers excited in PdSe 2 can transfer to WS 2 . These experimental findings establish a type-I band alignment between monolayer WS 2 and trilayer PdSe 2 . Furthermore, our results further highlight PdSe 2 as an important 2D material for constructing van der Waals heterostructures with emergent electronic and optoelectronic properties.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Synergizing superwetting and architected electrodes for high-rate water splitting

Water splitting is one of the most promising technologies for generating green hydrogen. To meet industrial demand, it is essential to boost the operation current density to industrial levels, typically in the hundreds of mA cm -2 . However, operating at these high current densities presents significant challenges, with bubble formation being one of the most critical issues. Efficient bubble management is crucial as it directly impacts the performance and stability of the water splitting process. Superwetting electrodes, which can enhance aerophobicity, are particularly favorable for facilitating bubble detachment and transport. By reducing bubble contact time and minimizing the size of detached bubbles, these electrodes help prevent blockage and maintain high catalytic efficiency. Here, in this review, we aim to provide an overview of recent advancements in tackling bubble-related issues through the design and implementation of superwetting electrodes, including surface modification techniques and structural optimizations. We will also share our insights into the principles and mechanisms behind the design of superwetting electrodes, highlighting the key factors that influence their performance. Our review aims to guide future research directions and provides a solid foundation for developing more efficient and durable superwetting electrodes for high-rate water splitting.

36 MATERIALS SCIENCE↗

Highly efficient semi-hydrogenation in strained ultrathin PdCu shell and the atomic deciphering for the unlocking of activity-selectivity

Excellent ethylene selectivity in acetylene semi-hydrogenation is often obtained at the expense of activity. To break the activity-selectivity trade-off, precise control and in-depth understanding of the three-dimensional atomic structure of surfacial active sites are crucial. Here, we designed a novel Au@PdCu core–shell nanocatalyst featuring diluted and stretched Pd sites on the ultrathin shell (1.6 nm), which showed excellent reactivity and selectivity, with 100% acetylene conversion and 92.4% ethylene selectivity at 122 °C, and the corresponding activity was 3.3 times higher than that of the PdCu alloy. The atomic three-dimensional decoding for the activity-selectivity balance was revealed by combining pair distribution function (PDF) and reverse Monte Carlo simulation (RMC). The results demonstrate that a large number of active sites with a low coordination number of Pd–Pd pairs and an average 3.25% tensile strain are distributed on the surface of the nanocatalyst, which perform a pivotal function in the simultaneous improvement of hydrogenation activity and ethylene selectivity. Our work not only develops a novel strategy for unlocking the linear scaling relation in heterogeneous catalysis but also provides a paradigm for atomic 3D understanding of lattice strain in core–shell nanocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Na/TM-site Mg substituted P2-Na 2/3 [Fe 1/3 Mg 1/12 Mn 7/12 ]O 2 cathode with extremely high capacity for sodium-ion batteries

The anionic redox reaction (ARR) has become a hot topic in battery research due to its ability to provide high energy density. Nevertheless, there are still many issues in Na-based layered oxides with the ARR, such as large voltage hysteresis, lattice oxygen loss, irreversible structural changes, and cation migration in the TM layer, resulting in structural collapse and poor electrochemical performance. Herein, a series of Na 2/3 [Fe 1/3 Mg x Mn 2/3–x ]O 2 cathodes are synthesized using a traditional solid-state reaction method. The effectiveness of Mg substitution amounts and site occupancy in regulating the reversibility of the ARR has been explored using various experimental techniques. Surprisingly, the well-designed Na/TM-site Mg substituted P2-Na 2/3 [Fe 1/3 Mg 1/12 Mn 7/12 ]O 2 exhibits an extremely high initial reversible capacity of ~253.21 mA h g –1 , equivalent to ~0.94 e – transfer, which is contributed by both cationic and anionic redox reactions as confirmed by hard X-ray absorption spectroscopy (hXAS) and soft X-ray absorption spectroscopy (sXAS) analyses. In addition, the improved cycling and high-rate performance of the P2-Na 2/3 [Fe 1/3 Mg 1/12 Mn 7/12 ]O 2 are achieved by a well-maintained crystal structure and the highly reversible anionic redox reaction of O 2– /O n– . Finally, these in-depth studies provide crucial knowledge for the development and understanding of cathode materials with a highly reversible ARR for low-cost and high-energy sodium-ion batteries.

36 MATERIALS SCIENCE↗

Surfactant templated biogenic nanoporous silica thermal insulation composite

Carbon-sequestration biogenic insulation materials offer a promising solution for sustainable and energy-efficient buildings. However, minimizing energy-intensive manufacturing processes and ensuring a uniform microstructure are essential to achieve widespread application. In this work, we introduce cetyltrimethylammonium bromide (CTAB) surfactant as both synthesis and dispersion template for nanoporous silica to create biogenic straw-based thermal insulation composites. As the amount of nanoporous silica increases to 72 wt%, the elastic insulation composite dried using the solvent exchange method exhibits a density of 0.058 g cm –3 , a thermal conductivity of 30.3 mW m –1 K –1 and a flexural modulus of 3.96 MPa, while demonstrating materials circularity and fire retardance. The use of CTAB surfactant effectively captures nanoporous silica, preventing its loss during manufacturing and enhancing the homogeneity and dispersion of the silica within the composite. In addition, the results show that the ethanol solvent exchange drying at ambient conditions provides the optimum thermal insulation performance with less energy consumption compared to freeze-drying.

36 MATERIALS SCIENCE↗

Nitrogen doping–enabled low-temperature capacitance retention in carbon materials

Reliable energy storage at subzero temperatures is crucial for polar and space applications. Nitrogen-doped multiscale porous carbon aerogels deliver 96% capacitance retention at −40 °C and 1.43 Wh L −1 energy density. In conclusion, enhanced nitrogen content and enlarged ion-accessible surface synergistically enable exceptional low-temperature supercapacitor performance.

Materials science↗

Machine learning inversion from small-angle scattering for charged polymers

We develop Monte Carlo simulations for uniformly charged polymers and a machine learning algorithm to interpret the intra-polymer structure factor of the charged polymer system, which can be obtained from small-angle scattering experiments. The polymer is modeled as a chain of fixed-length bonds, where the connected bonds are subject to bending energy, and there is also a screened Coulomb potential for charge interaction between all joints. The bending energy is determined by the intrinsic bending stiffness, and the charge interaction depends on the interaction strength and screening length. All three contribute to the stiffness of the polymer chain and lead to longer and larger polymer conformations. The screening length also introduces a second length scale for the polymer besides the bending persistence length. To obtain the inverse mapping from the structure factor to these polymer conformation and energy-related parameters, we generate a large data set of structure factors by running simulations for a wide range of polymer energy parameters. We use principal component analysis to investigate the intra-polymer structure factors and determine the feasibility of the inversion using the nearest neighbor distance. We employ Gaussian process regression to achieve the inverse mapping and extract the characteristic parameters of polymers from the structure factor with low relative error.

36 MATERIALS SCIENCE↗

Machine learning-assisted profiling of a kinked ladder polymer structure using scattering

Ladder polymers consisting of fused rings in the backbone have very limited conformational freedom, which results in very different properties from traditional linear polymers. However, accurately determining their size and chain conformations from solution scattering remains a challenge. Their chain conformations of kinked ladder polymers are largely governed by the structures and relative orientations or configurations of the repeat units, unlike conventional polymer chains whose bending angles between repeat units follow a unimodal Gaussian distribution. Meanwhile, traditional scattering models for polymer chains do not account for these unique structural features. This work introduces a novel approach that integrates machine learning with Monte Carlo simulations to construct a model that can describe the geometry of a type of kinked CANAL ladder polymers. We first develop a Monte Carlo simulation model for sampling the configuration space of CANAL ladder polymers, where each repeat unit is modeled as a biaxial segment. Then, we establish a machine learning-assisted scattering analysis framework based on Gaussian Process Regression. Finally, we conduct small-angle neutron scattering experiments on a CANAL ladder polymer solution to apply our approach. Our method uncovers structural features of such ladder polymers that conventional methods fail to capture.

Ding, Lijie [Oak Ridge National Laboratory (ORNL),↗

Electrolytic gold plating, stripping, and ion transport dynamics through a solid-state iodide perovskite

The pronounced electrochemical reactivity between halide perovskites and metal electrodes can introduce mobile extrinsic metal ions which can cause device instability or enable novel functionalities. Here we systematically investigate the kinetics of gold cation (Au + ) migration in indium tin oxide (ITO)/methylammonium lead triiodide (MAPbI 3 )/Au model devices under long-term potentiostatic biasing. Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) analyses reveal that Au + ions, electrochemically generated at the Au anode, traverse the perovskite layer with diffusion coefficients on the order of 10 −11 to 10 −10 cm 2 s −1 and are subsequently reduced at the cathode as Au 0 clusters, resembling metal plating behavior in electrolytic cells and solid-state batteries during charging. Furthermore, reversing the applied bias strips the plated Au 0 , revealing reversibility suitable for bipolar resistive switching devices and providing direct evidence of the electrochemical and ionic nature of Au transport within the perovskite matrix. Quantitatively determining diffusion coefficients and ion concentrations provides foundational inputs for future drift-diffusion modelling opportunities and allows us to relate our findings to implications on long term operation of devices like photovoltaic modules. These results clearly demonstrate the solid-state electrochemical nature of perovskite devices, highlight methods to be more quantitative about ion transport properties, provide and emphasize the importance of disentangling electro-, photo-, photoelectrochemical processes for understanding device performance and unlocking new functionalities.

14 SOLAR ENERGY↗

Advances in vat photopolymerization: early-career researchers shine light on a path forward

Vat photopolymerization (VP) has emerged as a promising additive manufacturing technique to allow rapid light-based fabrication of 3D objects from a liquid resin. Research in the field of vat photopolymerization spans across multiple disciplines from engineering and materials science to applied chemistry and physics. This perspective brings together early-career researchers from various disciplines in academia and national laboratories around the world to summarize the most recent advancements with special emphasis on the research highlighted as part of the Gordon Research Conference (GRC) 2024 meeting on Additive Manufacturing of Soft Materials. We provide an outlook on next-generation polymer processing methods from synthesis of novel materials to multimodality manufacturing and performance engineering. Further, this article combines the ideas of many of these junior researchers to present a vision for the future of the field by highlighting the challenges and opportunities that lie ahead.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Beyond real: alternative unitary cluster Jastrow models for molecular electronic structure calculations on near-term quantum computers

Near-term quantum devices require wavefunction ansätze that are expressive while also of shallow circuit depth in order to both accurately and efficiently simulate molecular electronic structure. While the unitary coupled cluster ansatz (e.g., UCCSD) has become a standard, the high gate count associated with the implementation of this limits its feasibility on noisy intermediate-scale quantum (NISQ) hardware. k -Fold unitary cluster Jastrow (uCJ) ansätze mitigate this challenge by providing O( kN 2 ) circuit scaling and favorable linear depth circuit implementation. Previous work has focused on the real orbitalrotation (Re-uCJ) variant of uCJ, which allows an exact (Trotter-free) implementation. Here we extend and generalize the k -fold uCJ framework by introducing two new variants, Im-uCJ and g-uCJ, which incorporate imaginary and fully complex orbital rotation operators, respectively. Similar to Re-uCJ, both of the new variants achieve quadratic gate-count scaling. Our results focus on the simplest k = 1 model, and show that the uCJ models frequently maintain energy errors within chemical accuracy (∼1 kcal mol −1 ). Both g-uCJ and Im-uCJ are more expressive in terms of capturing electron correlation and are also more accurate than the earlier Re-uCJ ansatz. We further show that Im-uCJ and g-uCJ circuits can also be implemented exactly, without any Trotter decomposition. Numerical tests using k = 1 on H 2 , H 3 + , Be 2 , C 2 H 4 , C 2 H 6 and C 6 H 6 in various basis sets confirm the practical feasibility of these shallow Jastrow-based ansätze for applications on near-term quantum hardware.

Tkachenko, Nikolay V. [University of California, B↗

Effects of deposition and annealing conditions on the crystallisation of NiTi thin films by e-beam evaporation

This Letter demonstrates the effects of deposition and annealing conditions on the crystallisation of nickel–titanium (NiTi) thin films deposited by the e-beam evaporation. NiTi thin films of 0.5 μm thick are fabricated on P-type (110) silicon substrates using the e-beam evaporation technique. We find that with the characterisations using the X-ray diffraction method, the results indicate that low e-beam deposition rate and argon employed annealing procedures can be beneficial to the formation of NiTi crystalline structure. Additionally, the as-deposited NiTi thin films without annealing procedures are amorphous, when deposited on the substrates at low temperatures. The differential scanning calorimetry studies show NiTi thin films formed by the e-beam evaporation are Ni-rich. Furthermore, SEM images illustrate that high-precision patterned NiTi thin film microstructures can be fabricated by combining with the e-beam evaporation and lift-off resist methods, without any wet or dry etching procedures. The proposed fabrication process for NiTi thin film microstructures shows great potential for application in shape memory alloy medical devices, as well as the micro-robotics.

36 MATERIALS SCIENCE↗

Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures

Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon expected to reach exabytes. Consequently, there is a growing need for computation, including structured data processing from raw data to consumer-ready derived data, extensive Monte Carlo simulation campaigns, and a wide range of end-user analysis. To manage these computational and storage demands, centralized workflow and data management systems are implemented. However, decisions regarding data placement and payload allocation are often made disjointly and via heuristic means. A significant obstacle in adopting more effective heuristic or AI-driven solutions is the absence of a quick and reliable introspective dynamic model to evaluate and refine alternative approaches. In this study, we aim to develop such an interactive system using real-world data. By examining job execution records from the PanDA workflow management system, we have pinpointed key performance indicators such as queuing time, error rate, and the extent of remote data access. The dataset includes five months of activity. Additionally, we are creating a generative AI model to simulate time series of payloads, which incorporate visible features like category, event count, and submitting group, as well as hidden features like the total computational load—derived from existing PanDA records and computing site capabilities. These hidden features, which are not visible to job allocators, whether heuristic or AI-driven, influence factors such as queuing times and data movement.

kilic, Ozgur Ozan [Brookhaven National Laboratory ↗

Experimental study of hot electron generation in shock ignition relevant high-intensity regime with large scale hot plasmas

In the shock ignition (SI) laser fusion scheme, hot electrons generated by the laser spike pulse can either preheat the fuel or strengthen the ignition shock, depending on the hot electron characteristics. We conducted a planar target experiment on the OMEGA-EP laser facility and characterized the temperature and total energy of hot electrons generated from a kilojoule-class 100-ps infrared (IR) or a 1-ns ultraviolet (UV) laser interacting with a large (L n ~330-450 μm) and hot (T e ~1-2 keV) coronal plasma at the SI-relevant intensities (~10 16 W/cm 2 ). The IR laser converts ~2.5% energy into hot electrons with T hot ~ 60–90 keV, while the UV laser couples 0.8% ± 0.7% energy into T hot =27 ± 9 keV hot electrons. The IR-produced hot electrons yield five times higher Cu Kα emission than the UV case, confirming the higher electron conversion efficiency with the IR laser. The low energy conversion from the UV laser to hot electrons may be due to the refraction of the off-normal incident laser in the large coronal plasma. These findings are the first comparisons of hot electron generation between the IR and UV pulses at kilojoule scales in SI-relevant large-scale plasmas. The findings may expand the SI design space to include IR lasers as the possible spike lasers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

All-electron ab initio Bethe-Salpeter equation approach to neutral excitations in molecules with numeric atom-centered orbitals

The Bethe-Salpeter equation (BSE) based on GW quasiparticle levels is a successful approach for calculating the optical gaps and spectra of solids and also for predicting the neutral excitations of small molecules. We here present an all-electron implementation of the GW+BSE formalism for molecules, using numeric atom-centered orbital (NAO) basis sets. We present benchmarks for low-lying excitation energies for a set of small organic molecules, denoted in the literature as “Thiel’s set.” Literature reference data based on Gaussian-type orbitals are reproduced to about one millielectron-volt precision for the molecular benchmark set, when using the same GW quasiparticle energies and basis sets as the input to the BSE calculations. For valence correlation consistent NAO basis sets, as well as for standard NAO basis sets for ground state density-functional theory with extended augmentation functions, we demonstrate excellent convergence of the predicted low-lying excitations to the complete basis set limit. A simple and affordable augmented NAO basis set denoted “tier2+aug2” is recommended as a particularly efficient formulation for production calculations. We finally demonstrate that the same convergence properties also apply to linear-response time-dependent density functional theory within the NAO formalism.

Liu, Chi↗