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At least 307 records · Page 17

FLAMES─Fast, Low-Storage, Accurate, and Memory-Efficient Adaptive Sampling─Approach to Resolve Spatially Dependent Dynamics of Molecular Liquids

Many critical phenomena in soft matter occur at large length scales, necessitating the resolution of their structure and dynamics at low wavenumbers. However, resolving wavenumber-dependent dynamics computationally via molecular dynamics simulations presents significant challenges, as these phenomena span several orders of magnitude in both time and length scales, resulting in high computational costs and memory demands. Here, this work highlights the computational and memory challenges associated with analyzing molecular trajectories in reciprocal space and demonstrates a method to address them. We introduce FLAMESFast, Low-storage, Accurate, and Memory-Efficient adaptive Sampling, which is a direct method for calculation of structure factors, allowing us to select only the required number of wavevectors for binning. We also use wavenumber-dependent time steps to extract dynamics. Our FLAMES approach effectively mitigates computational and memory/storage bottlenecks. We demonstrate the method using simulations of a model system, liquid octane, at various temperatures. Comparisons with experimental data and real space computation show that the FLAMES technique achieves high accuracy in resolving temperature- and spatially dependent dynamics while being significantly more computationally efficient and requiring less memory and storage than methods based on a uniform wavevector grid and fixed temporal spacing.

Chen, Guang [Argonne National Laboratory (ANL), Ar↗

Similarity Metric for Data Optimization and Efficient Training of Reactive Machine Learning Force Fields for Hydrocarbon Radiolysis

Radiolysis is a common approach to sterilize polymers, chemically modify them for upcycling, and accelerate their decomposition for recycling purposes. Reactive molecular dynamics (MD) simulations provide a powerful tool to generate atomic-level trajectories of the reactive processes and quantify radiolytic chemical degradation pathways. For this, machine learning (ML) surrogate models for reactive force fields with quantum mechanical accuracy are now widely used, which require ML training data sets that can provide information on atomic environments for target chemical systems. However, radiolysis chemistry can be highly complex and diverse, which poses significant challenges for generating training data to parametrize ML models. In this regard, we developed a method for optimizing the training data set using a cosine similarity metric to help guide training set selection for radiolysis of polyethylene, a model hydrocarbon polymer, as well as to enhance the transferability of our reactive ML force field (MLFF) to a variety of molecular and polymeric systems. Our approach performs atom-by-atom comparisons between local atomic environments to pinpoint important data points associated with rare and localized events, such as radiolysis damage within structures. We apply this approach to train the Chebyshev Interaction Model for Efficient Simulation (ChIMES) MLFF model, which expresses the atomic interaction potentials in terms of linear combinations of many-body Chebyshev polynomials. We first show that our method can reduce our training set size by ∼70% while improving overall accuracy compared to more standard MD model fitting approaches. We then validate our optimum model against diverse hydrocarbon simulation data, including simple alkanes and systems with unsaturated carbon bonds, over a wide range of thermodynamic conditions. Finally, we use our ChIMES model to perform MD simulations of radiolytic damage with large-scale systems that help avoid system size effects. Overall, our approach yields an MD force field that retains most of the accuracy of the underlying quantum method while yielding many orders of improvement in computational efficiency. In conclusion, our efforts will have impact on future hydrocarbon polymer radiolysis studies, where the chemical details of the polymer–radiation interactions can have a strong effect on the resulting products observed in experiments.

Hydrocarbons↗

Hierarchical Reinforcement Learning of a Short-Range Bond-Order Potential for Silica: Analytic Embedding of Coordination with Classical Efficiency

Reinforcement learning (RL) has recently emerged as a data-efficient strategy to parametrize short-range interatomic potentials. Building on our past RL optimization of pairwise silica models, we extend the framework to a bond-order (Tersoff-type) potential that provides an analytic embedding of local coordination through a three-body term. A hierarchical RL workflow combining continuous-action Monte Carlo Tree Search and property-based rewards efficiently explores the 26-dimensional parameter space, sequentially optimizing lattice parameters, densities, angles, and cohesive energies of 21 silica polymorphs. The resulting models, Q-Tersoff and ML-Tersoff, reproduce the energetic ordering of low-energy phases and capture the angular correlations and amorphous structure factors of silica with improved fidelity over pairwise force fields, while remaining orders of magnitude faster than high-dimensional machine-learned potentials. Both models underperform for elastic constants and high-energy frameworks, delineating the limits of the current analytic form. The approach establishes a general and interpretable route to angle-aware, short-range potentials that bridge physics-based and machine-learned descriptions of silicate materials.

36 MATERIALS SCIENCE↗

Leveraging Multiproton-Coupled Electron Transfer to Improve Ir(III) Photocatalyst Efficiency

In photoredox reactions, charge recombination (CR) limits quantum yields, hindering the efficient conversion of light energy into catalytic activity. To address this, we drew inspiration from redox relays in photosystem II (PSII) and developed a new series of iridium(III) complexes featuring covalently attached benzimidazole-phenol-pyridine (BIP-Py) groups to facilitate intramolecular multiproton-coupled electron transfer (MPCET). Herein, we evaluate the effects of MPCET through an extended and well-defined hydrogen-bond network to improve photocatalytic activity and mitigate rapid charge recombination. Infrared spectroelectrochemistry reveals pyridine protonation upon phenol oxidation, while visible spectroelectrochemistry and transient absorption spectroscopy confirm the electro- and photochemical formation of chargeseparated states (CSS) involving oxidized BIP, resulting from intramolecular proton-coupled electron transfer (PCET). The application of the BIP-Py platform in a photocatalytic Nhydroxyphthalimide ester reduction reaction resulted in a ∼106-fold reduction in CR rate and a quantum yield enhancement of up to 157%. Our findings suggest that incorporating MPCET-based redox relays into photocatalyst frameworks is an effective strategy to enhance the efficiency of photocatalytic systems.

Catalysts↗

Self-Assembled Bolaamphiphile-Based Organic Nanotubes as Efficient Cu(II) Ion Adsorbents

Self-assembled organic nanotubes (ONTs) have been actively examined for various applications such as chemical separations and catalysis owing to their well-defined tubular nanostructures with distinct chemical environments at the wall and internal/external surfaces. Adsorption of heavy metal ions onto ONTs plays an essential role in many of these applications, but it has rarely been assessed quantitatively. Herein, we investigated interactions between Cu 2+ and single-/quadruple-wall bolaamphiphile-based ONTs having inner carboxyl groups with different inner diameters, COOH-ONT 10nm and COOH-ONT 20nm . We first examined the effects of Cu 2+ on their nanotubular structures using SAXS, STEM, and AFM. COOH-ONT 10nm was stable in aqueous Cu 2+ solution in contrast to COOH-ONT 20nm owing to the presence of polyglycine-II-type hydrogen bonding networks within its wall. Subsequently, we studied the Cu 2+ adsorption behavior of COOH-ONT 10nm by monitoring the concentration of unbound Cu 2+ using linear sweep anodic stripping voltammetry. The Cu 2+ adsorption was quick, attributable to efficient Cu 2+ partitioning through the open ends of the ONT, followed by fast Cu 2+ diffusion in the uniform, relatively large nanochannel. More importantly, the Cu 2+ adsorption capacity and affinity of COOH-ONT 10nm were measured at different pH using the Langmuir adsorption model. The adsorption capacity was similar at the pH range examined, showing the participation of approximately 25% of the inner carboxyl groups in the adsorption. The adsorption affinity increased with pH, indicating the essential role of the deprotonated carboxyl groups in the Cu 2+ adsorption. Most interestingly, the Langmuir adsorption constant was significantly higher than those of previously reported synthetic adsorbents and planar monolayer based on carboxyl binding sites. The high Cu 2+ affinity of the ONT was attributable to the highly dense binding sites on the well-defined nanoscale concave structure of the inner channel. Furthermore, these results provide a valuable guideline to designing self-assembled nanomaterials for efficient chemical separations, detection, and catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Red-Light-Driven Biophotochemical Diode Based on a Microorganism–Silicon Nanowire Interface for Stable and Efficient Bias-Free CO 2 Reduction

Artificial photosynthesis offers a promising route for sustainable liquid fuel and feedstock production, yet integrating efficient CO 2 reduction catalysts with light-harvesting systems remains challenging. Here, in this study, we present a biophotochemical diode that couples microorganism-driven CO 2 reduction with glycerol oxidation, enabled by silicon nanowire photoelectrodes under varying red-light intensities. Tuning the biotic-abiotic interface─by increasing biocatalyst loading and adjusting the catholyte pH to mitigate local alkalization─significantly improves performance and stability. The enhanced-loading biocathode maintains a high faradaic efficiency across a wide potential range, even under elevated light intensities. At 60 mW/cm 2 , the system achieves a bias-free current density of 3.5 mA/cm 2 . Long-term stability testing at 40 mW/cm 2 demonstrates stable operation for over 100 h. The photoanode generates valuable C 3 products, primarily glycerate and lactate, enhancing the economic viability. This work showcases the importance of microenvironmental control at the biotic-abiotic interface and establishes a scalable platform for light-driven CO 2 reduction using earth-abundant silicon.

Artificial Photosynthesis↗

Mild-Annealed Molecular Layer Deposition (MLD) Tincone Thin Film as Photoelectrochemically Stable and Efficient Electron Transport Layer for Si Photocathodes

Metalcone thin films, composed of inorganic–organic hybrids, are synthesized using molecular layer deposition (MLD) through reactions between organometallic precursors (e.g., Sn, Al, and Ti) and organic reactants (e.g., ethylene glycol and glycerol). Despite their unique properties, metalcones exhibit significant vulnerability to water due to their organic components, limiting their potential in electrochemical applications. This study focuses on enhancing the photoelectrochemical stability of tincone thin films in aqueous electrolyte while preserving their hybrid characteristics through mild annealing in air at 250 °C. As-deposited and vacuum-annealed tincone thin films exhibited significant degradation under these conditions, while high-temperature-annealed (500 °C) tincone thin films offered improved stability with a significant decline in charge transfer efficiency. In contrast, mild annealing in air maintained the C–O bond at half level and improved the stability and charge transport without compromising the unique characteristics of tincone. This was confirmed by ellipsometry, X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared spectroscopy (FTIR). Mild-annealed tincone deposited on a lightly doped p-type silicon (p-Si) photocathode produced a 20-fold increase in CO volume compared to high-temperature annealed tincone in a CO 2 -saturated potassium bicarbonate (KHCO 3 ) electrolyte with dispersed graphene oxide–cobalt phthalocyanine (GO-CoPc) under 1 sun illumination at 0.9 V vs reversible hydrogen electrode (RHE), while maintaining the faradaic efficiency for CO and H 2 . These results suggest that mild-annealed tincone thin films hold significant potential as protective charge transport layers on silicon photocathodes for the aqueous CO 2 reduction reaction (CO 2 RR).

Annealing (metallurgy)↗

Doping in Efficient Polycrystalline CdSeTe Solar Cells via AsCl 3 Vapor Annealing

Doping in cadmium telluride (CdTe) thin-film solar cells is a critical step in producing highly efficient CdTe solar modules. To date, copper (Cu) ex-situ diffusion doping and group V in situ doping (such as arsenic, As) have been effectively used in manufacturing CdTe solar modules. However, Cu doping is prone to rapid degradation, whereas the low activation ratio of the dopants constrains group V in situ doping. Recently, ex-situ group V doping has been developed, showing an improved doping activation ratio through a solution process. Here, in this study, we developed a vapor-based AsCl 3 doping method for diffusion doping of polycrystalline CdSeTe devices. AsCl 3 vapor annealing can promote the diffusion of As into the bulk CdSeTe through a surface chemical reaction between CdTe and AsCl 3 . This approach has led to a long carrier lifetime of over 72 ns, V oc of 850 mV, and power conversion efficiency of ~18% with Au metal electrodes. The vapor-based ex situ group V doping approach offers an effective means to perform group V diffusion doping into the CdSeTe device.

14 SOLAR ENERGY↗

Benchmarking Density Functional Theory Methods for Efficient Calculations of a Strongly Correlated Li 1– x Ni 1– y O 2−δ System

Transition metal oxides (TMOs), such as LiNiO 2 , are promising candidates for energy storage and electronic devices due to their unique electronic properties, exceptional physical and chemical characteristics, and ability to adopt multiple oxidation states. However, accurately predicting their properties using mean-field density functional theory (DFT) is challenging due to the presence of strongly correlated d-electrons and the complex interplay between their structural, electronic, and magnetic responses. These challenges are further exacerbated by the need to model defects, surfaces, and interfaces, which require computationally efficient, large-scale simulations. To address these issues, we carry out a benchmark study on the Li 1–x NiO 2 system, evaluating the performance of several popular functionals. Our findings demonstrate that combining SCAN functional relaxation with single-step HSE calculations provides a practical and scalable computational strategy. This approach balances accuracy and efficiency, enabling high-throughput simulations of strongly correlated TMOs and improved predictive modeling capability of TMOs for practical applications.

25 ENERGY STORAGE↗

Elucidating the Structural and Electronic Effects of Ni and Mn Cationic Incorporation on CoOOH for Efficient Benzyl Alcohol Electrooxidation

Transition-metal oxyhydroxides such as CoOOH are promising low-cost electrocatalysts for the selective electrooxidation of organic molecules, yet the influence of ubiquitous transition-metal impurities on their performance and durability remains poorly understood. Here, we experimentally probed the individual and synergistic electrochemical and structural effects of Ni and Mn incorporations into model CoOOH electrocatalysts toward an efficient benzyl alcohol oxidation reaction (BAOR). Comprehensive electrochemical, microscopic, and spectroscopic analyses reveal that Ni incorporation enhances charge-transfer kinetics and overall activity through the formation of catalytically active Ni 3+ sites, whereas Mn exhibited a more complex but interesting role. At the early stages of operation, Mn 4+ acts as a stabilizing surface layer that mitigates catalyst degradation but partially blocks Co sites before they undergo gradual leaching. The concurrent incorporation of both Ni and Mn yields a trimetallic 2NMC@NF electrocatalyst that integrates the activity benefits of Ni with the stability conferred by Mn, achieving 92.9% benzyl alcohol conversion and 91.4% Faradaic efficiency after 24 h at 1.5 V vs RHE. These findings elucidate how trace Ni and Mn impurities, often introduced from electrolytes or external sources, can modulate the lattice and electronic structure of CoOOH, offering a design strategy for enhancing both activity and long-term stability in electrocatalytic organic oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Post-Modification of Crystalline Peptoid Nanomembranes with Active Nanoparticles for Efficient Photooxidation of a Mustard Gas Simulant

Peptoids (or poly-N-substituted glycines) hold immense potential for assembling into hierarchically structured functional materials via controlled molecular interactions. To create self-assembled materials with tailored functionalities, peptoid sequences are often conjugated with reactive or recognition motifs to enable applications including specific binding, biomimetic catalysis, and fluorescence imaging. However, the direct integration of bulky functional motifs into peptoid sequences can disrupt assembly processes and structural outcomes. Herein, we present a post-modification strategy for functionalizing pre-formed 2D crystalline assemblies. Through introducing clickable active sites, such as azide, alkyne, or thiol groups into a peptoid sequence, site-specific conjugation is achieved post-assembly via efficient “click”-type reactions. This strategy enables the ordered alignment of functional groups and gold nanoparticles (Au NPs) on the surface of 2D peptoid nanomaterials with controlled density, while preserving their high crystallinity and structural integrity. Furthermore, we demonstrated that nanomembranes functionalized with both Au NPs and porphyrins enhance the efficiency and selectivity of the photooxidation of 2-chloroethyl ethyl sulfide, a simulant of sulfur mustard. This innovative strategy lays the groundwork for advancing peptoid-based functional materials across diverse applications, from catalysis to biomedicine.

Chemistry↗

Nickel Sulfide-Nanowire-Filled Carbon Nanotubes as an Efficient Overall Water Splitting Electrocatalyst

Pursuing stable, efficient, and cost-effective nanostructured bifunctional electrocatalysts is crucial for advancing the electrochemical water splitting process and enabling clean hydrogen energy production. In recent years, considerable efforts have focused on developing highly efficient and durable commercial electrocatalysts for the oxygen evolution reaction (OER) and overall water splitting (OWS). This research introduces an OWS electrocatalyst-nickel sulfide-filled carbon nanotubes grown on a carbon cloth substrate (Ni 3 S 2 @CNTs/CC), synthesized via a one-step in-situ process. The synergistic integration of metal sulfide (Ni 3 S 2 ) and carbon nanotubes provides abundant active sites for catalytic reactions, ensuring a robust composite nanostructure with enhanced durability. Furthermore, the electrocatalytic performance for OER and OWS has been significantly improved by a simple acid treatment to the electrocatalysts, which introduces physical and chemical defects, particularly oxygen functional groups (the acid-treated sample is termed as Ni 3 S 2 @CNTs/CC-AT). As OER electrocatalysts, Ni 3 S 2 @CNTs/CC and Ni 3 S 2 @CNTs/CC-AT present overpotentials of 304 and 200 mV, respectively, for achieving a current density of 10 mA/cm 2 in the OER process. Furthermore, for complete water splitting in 1.0 M KOH electrolyte, Ni 3 S 2 @CNTs/CC and Ni 3 S 2 @CNTs/CC-AT exhibit potentials of 1.63 and 1.44 V, respectively, to achieve a current density of 10 mA/cm 2 when employed as both anode and cathode. Moreover, Ni 3 S 2 @CNTs/CC and Ni 3 S 2 @CNTs/CC-AT demonstrate durable nature for 22 and 20 h durability in the OER and OWS processes, respectively, offering a promising alternative to ruthenium- and iridium-based electrocatalysts for electrochemical hydrogen production through water splitting. In conclusion, the in-situ synthesis method and acid treatment strategy described in this research are promising approaches to fabricating high-performance encapsulated carbon-nanotube-based electrocatalysts.

36 MATERIALS SCIENCE↗

Fluorine-Tuned Carbon-Based Nickel Single-Atom Catalysts for Scalable and Highly Efficient CO 2 Electrocatalytic Reduction

Electrocatalytic CO 2 reduction is garnering significant interest due to its potential applications in mitigating CO 2 and producing fuel. However, the scaling up of related catalysis is still hindered by several challenges, including the cost of the catalytic materials, low selectivity, small current densities to maintain desirable selectivity. In this study, Fluorine (F) atoms were introduced into an N-doped carbon-supported single nickel (Ni) atom catalyst via facile polymer-assisted pyrolysis. This method not only maintains the high atom utilization efficiency of Ni in a cost-effective and sustainable manner but also effectively manipulates the electronic structure of the active Ni-N 4 site through F doping. The catalyst has also been further optimized by controlling the F states, including convalent and semi-ionic states, by adjusting the fluorine sources involved. Consequently, this catalyst with unique structure exhibited comparable electrocatalytic performance for CO 2 -to-CO conversion, achieving a Faradaic efficiency (FE) of over 99% across a wide potential range and an exceptional CO evolution rate of 9.5 x 10 4 h -1 at -1.16 V vs reversible hydrogen electrode (RHE). It also delivered a practical current of 400 mA cm -2 while maintaining more than 95% CO FE. Experimental analysis combined with density functional theory (DFT) calculations have also shown that F-doping modifies the electron configuration at the central Ni-N 4 sites. In conclusion, this modification lowers the energy barrier for CO 2 activation, thereby facilitating the production of the crucial *COOH intermediate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient Measurement of Length Distribution of 1D Nanoparticles in Solution via Optical Polarimetry

The efficient measurement of the length distribution of nanotubes, nanowires, and other one-dimensional (1D) nanoparticles in solution is important to enable their incorporation into materials and devices and to optimize their processing for properties of interest, such as thermal/electrical conductivity or mechanical strength, in suspensions and composites. We report an electric-field (E-field)-assisted optical-polarimetry technique to measure the length distribution of ensembles of high-aspect-ratio particles in dilute suspension. The degree of alignment of polarizable 1D particles suspended in a fluid under Brownian motion explicitly depends on the E-field strength and the particle length. We show that it is possible to extract the length distribution of 1D nanoparticles suspended in an insulating fluid by applying a range of E-fields and using optical polarimetry to measure the corresponding alignment order parameter. Notably, the method is relatively insensitive to the diameter of the 1D particles, which can be poorly known or vary within a sample. The technique is validated with silver nanowires and carbon nanotubes of known lengths, as well as polymer-depletion-length-separated single-wall carbon nanotube samples with length distributions independently measured with analytical ultracentrifugation. Finally, we demonstrate the ability of the optical-polarimetry technique to quantify changes in the length distribution of ultranarrow, sub-nanometer-diameter single-wall carbon nanotubes under different types and durations of ultrasonication. Within its range of applicability (polarizable 1D nanoparticles in the 0.5 to 15 μm length range, constrained by the voltage stability of the media and the suspended particles), the E-field-assisted optical-polarimetry method is a particularly efficient and accurate method to measure the length distribution of nanowires and nanotubes in suspension.

1D nanoparticles↗

Efficient Capture and Release of the Rare-Earth Element Neodymium in Aqueous Solution by Recyclable Covalent Organic Frameworks

Rare-earth elements (REEs) are present in a broad range of critical materials. The development of solid adsorbents for REE capture could enable the cost-effective recycling of REE-containing magnets and electronics. In this context, covalent organic frameworks (COFs) are promising candidates for REE adsorption due to their exceptionally high surface area. Despite having attractive physical properties, COFs are heavily underutilized for REE capture applications due to their limited lifecycle in aqueous acidic environments, as well as synthetic challenges associated with the incorporation of ligands suitable for REE capture. Here, in this work, we show how the Ugi multicomponent reaction can be leveraged to postsynthetically modify imine-based COFs for the introduction of a diglycolic acid (DGA) moiety, an efficient scaffold for REE capture. The adsorption capacity of the DGA-functionalized COF was found to be more than 40 times higher than that of the pristine imine COF precursor and more than four times higher than that of the next-best reported DGA-functionalized solid support. This rationally designed COF has appealing characteristics of high adsorption capacity, fast and efficient capture and release of the REE ions, and reliable recyclability, making it one of the most promising adsorbents for solid–liquid REE ion extractions reported to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient Self-Sensitized Photochemical CO 2 Reduction Using [Re(bpy 2+ )(CO) 3 (I)] 2+ and [Re(bpy 2+ )(CO) 3 (CH 3 CN)] 3+ Photocatalysts with Pendent Ammonium Cations

Rhenium(I) tricarbonyl complexes fac-[Re(bpy)(CO) 3 (L)]n + are the classical examples of self-sensitized photocatalysts capable of the dual roles of light absorption and catalysis. Here, in this work, a series of dicationic halido or tricationic solvento complexes fac-[Re(bpy 2+ )(CO) 3 X] n+ (PF 6 ) n (where X = Cl - or I - (n = 2), or CH 3 CN (n = 3) and bpy 2+ is bipyridine modified by two -CH 2 -(NMe3) + tetra-alkylammonium cations) have been investigated as self-sensitized and sensitized CO 2 reduction photocatalysts. Four structural isomers differing in the cation position have been tested in N,Nʹ-dimethylacetamide solvent (DMA) using 1,3-dimethyl-2-phenyl-2,3-dihydro-1H-benzimidazole (BIH) as the electron donor, and the position of the cationic pendants has a significant impact on the catalyst turnover number and quantum efficiency (ϕ). Up to 455 self-sensitized turnovers of CO and a high photon efficiency (ϕ CO ) of 22% have been achieved. Time-resolved infrared spectroscopy and theoretical calculations were used to characterize the catalytic cycle including the ligand exchange between one-electron reduced (OER) halido and solvento species as well as the binding of CO 2 to the putative two-electron reduced (TER) species. The CO 2 -reactive TER catalyst was formed by disproportionation or intramolecular electron transfer between two forms of the OER catalyst as indicated by the formation of the fully oxidized catalyst concurrent with CO 2 binding. When [Ru(bpy) 3 ] 2+ was used as a sensitizer, catalyst durability improved, and the selectivity toward formate increased as high as 3.3:1 over CO (total TON = 1370) due to acidification of the reaction, which promotes formation of the hydride intermediate, as BIH was consumed and deprotonated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lattice-Nitrogen-Mediated Chemistry Suppresses Hydrogen Evolution for Record Faradaic Efficiency in Ammonia Synthesis

Ammonia (NH 3 ) production using air, water, and electricity offers a transformative route to carbon-free chemical synthesis, addressing global sustainability challenges. However, the hydrogen evolution reaction (HER) in aqueous systems significantly hinders NH 3 selectivity, limiting Faradaic efficiency (FE) to below ~15%. Here, we report an FE of approximately 48%, the highest recorded for aqueous NH 3 synthesis, using two-dimensional (2D) nitride catalysts. These catalysts enable lattice nitrogen protonation through the Mars-van Krevelen (MvK) mechanism, effectively suppressing HER. Using operando spectroelectrochemistry, we identified active sites and tracked nitrogen vacancy cycles, providing unprecedented insights into the reaction pathways. Our findings, supported by advanced computational techniques and complementary spectroscopic analyses, highlight the stability and efficiency of the MvK cycle, setting a new benchmark for sustainable NH 3 production.

catalysts↗

Autonomous Synthesis and Inverse Design of Electrochromic Polymers with High Efficiency and Accuracy

Here, the design and synthesis of functional polymers, aimed at targeted properties through specific structures, have long been challenged by their complex and often nonlinear structure–property relationships. Key processes, including knowledge accumulation for predictive design and experimental refinement and validation, are traditionally labor-insensitive and time-consuming, making it difficult to balance accuracy and efficiency. Here, we introduce an accelerated, autonomous system for the on-demand synthesis of electronic polymers that achieves the desired electrochromic functionality with high accuracy and efficiency. Our approach leverages large language model-assisted data mining, a physics-informed copolymer machine learning model, and an AI-driven autonomous robotic workflow in the Polybot lab. Within 72 h, Polybot autonomously synthesized electrochromic polymers (ECPs) with targeted, previously-unreported color values, including green polymers with specific absorption profiles, precisely fine-tuning copolymer structures with a 5% step size in comonomer composition within a three-monomer system. A publicly accessible ECP informatics database has also been created to foster knowledge exchange.

AI-driven Robotic Lab↗