Sulfide superionic conductors (e.g., argyrodite Li6PS5Cl, LPSCl) are extremely promising for all solid‐state batteries, but poor atmospheric stability and high interfacial reactivity limit widespread adoption. Coating LPSCl powders with ultrathin coatings using atomic layer deposition (ALD) mitigates these problems, protecting against atmospheric degradation and reducing reactivity with Li metal, yielding more stable cycling. Despite significant promise, the ALD mechanism is unknown, hampering the development of new coating chemistries. In this study, we elucidate the mechanism for Al2O3 ALD on LPSCl using trimethyl aluminum (TMA) and H2O by combining in situ Fourier transform infrared spectroscopy, ex situ solid‐state magic angle spinning nuclear magnetic resonance, UV Raman spectroscopy, X‐ray photoelectron spectroscopy, and density functional theory calculations. We determine that ALD Al2O3 nucleates promptly via TMA reaction with native OH, SH, and PS3‐OH groups to form transient C–Al–O(S) species that are rapidly hydrolyzed during the subsequent H2O exposure. This reversible transformation maintains surface nucleophilicity and prevents sulfide decomposition. The resulting layer‐by‐layer growth leads to highly conformal Al2O3 coatings on LPSCl that are readily scalable to ≥50 g quantities using a rotating drum fixture. This detailed understanding of ALD surface reactions provides critical insights guiding the selection of future ALD chemistries with improved performance.

Neuromorphic ionic computing is inspired by the brain's use of ions for ultralow-energy computation-its massive parallelism, adaptability, and learning capabilities. This emerging paradigm can overcome limitations of conventional silicon-based computing by enabling colocated memory and processing, multicarrier information streams, and massive three-dimensional connectivity. However, substantial knowledge gaps remain in understanding and engineering ionic transport, energy dissipation, materials design, and scalable device architectures. This Review explores these critical challenges across seven key domains, highlighting the need for new theoretical approaches, materials, device concepts, and fabrication strategies. We argue that advancing ionic neuromorphic systems requires an interdisciplinary approach, integrating insights from biology and neuroscience, nanofluidics, materials science, and systems engineering to enable a new class of energy-efficient, robust, and reconfigurable computing technologies.

Molecule-electrode hybrid materials based on cobalt phthalocyanine (CoPc) supported on carbon nanostructures have emerged as highly effective electrocatalysts for the selective six-electron reduction of CO 2 to methanol (e-methanol). However, the strong π-stacking tendency of CoPc leads to poor solubility and hinders its uniform integration with conductive supports such as multiwalled carbon nanotubes (CNTs), limiting the controlled preparation of well-defined hybrid architectures. Here, we introduce a thermocleavable CoPc-ester precursor strategy that enables the synthesis of a highly dispersed CoPc-acid@CNT hybrid catalyst. Controlled thermal activation cleaves the solubilizing ester groups, generating insoluble CoPc-acid species that molecularly anchor onto the CNT surface. This approach promotes efficient active-site dispersion, confirmed through electron microscopy, and strengthens Co-CNT electronic coupling, as evidenced by operando IR spectroscopy, which reveals a steeper Stark tuning rate for the adsorbed *CO intermediate compared to conventionally prepared CoPc@CNT materials. The optimized hybrid catalyst delivers efficient aqueous CO 2 reduction to methanol, achieving a Faradaic efficiency (FE) of 44% and a total current density of 19 mA/cm², modestly surpassing the benchmark CoPc@CNT system (38%, 26 mA/cm²). To assess the commercial relevance of e-methanol electrolyzers employing such molecular hybrid catalysts, we also present a detailed techno-economic analysis (TEA) and life-cycle analysis (LCA). The TEA indicates that continued technical improvements could lower the minimum selling price of e-methanol to $0.41/kg, while the LCA shows a 34% reduction in carbon intensity (CI) relative to fossil-derived methanol, with the potential for near-zero CI when coupled with strategic renewable-energy integration. Collectively, these results highlight the promise of thermocleavable molecular precursors for achieving tailored catalyst anchoring and dispersion on conductive substrates, advancing the development of highly efficient and selective CO 2 -to-methanol electrocatalysts.

The U.S. Department of Energy (DOE) national laboratories represent a unique class of government-owned, contractor-operated research institutions dedicated to conducting research and development (R&D) related activities that address national priorities, supporting and advancing the DOE mission. They play a vital role in sustaining U.S. innovation capacity, stewarding the nation's technical base, and nurturing science and technologies. In this perspective, we highlight the processing science and scaleup capabilities of the Materials Engineering Research Facility (MERF) at DOE's Argonne National Laboratory to demonstrate how DOE National Laboratories bridge fundamental science and applied technology development to accelerate deployment. Case studies are presented on selective membranes for critical mineral recovery, sensors for per- and polyfluoroalkyl substances (PFAS) detection, surface functionalization via atomic layer deposition (ALD) and sequential infiltration synthesis (SIS), and lithium recovery from battery recycling waste streams using a novel electrodialysis process. These examples underscore MERF's role in translating innovative technologies into practical solutions for renewable water and critical resource recovery, which also leverage Argonne's analytical and computational capabilities. This perspective also outlines mechanisms for collaborating with the DOE national laboratories to strengthen partnerships across government, the national laboratories, academia, and industry.

This study investigated the effect of synthesis temperature (550 to 1050 degrees C) on the performance of Magneli phase titanium suboxide electrodes for electrochemical nitrate (NO3 -) reduction. Different synthesis temperatures produced distinct Magneli phases, which were characterized using X-ray diffraction and X-ray photoelectron spectroscopy. Higher temperatures increased oxygen vacancy and Ti3+ concentrations. The electrode synthesized at 850 degrees C consisted of a mixed Magneli phase with predominant Ti9O17 structure and demonstrated the highest NO3 - removal (similar to 60%) and low nitrite selectivity (similar to 2.8%) at -0.8 V/SHE with an 8.3 s hydraulic residence time (pH similar to 8). This electrode achieved a Faradaic efficiency of 72% for ammonia production at -1.4 V/SHE with 100 mM NO3 - concentration. The pseudo-first-order rate constant (172 h-1) exceeded those of other nonprecious and precious metal electrodes, attributed to the high specific surface area per volume (similar to 1.3 x 106 m-1) and efficient mass transfer enabled by the flow-through reactor design. Superior performance was attributed to optimized electronic properties, including band gap (1.31 eV) and flat band potential (-1.10 V/SHE), which facilitated efficient electron transfer at the electrode/electrolyte interface. These results underscore the critical role of synthesis temperature in tuning the electrochemical properties of Magneli phase electrodes, providing insights for developing efficient, nonprecious-metal-based electrodes for nitrate remediation.

Abstract Interfacial solar evaporation has shown promise as an inexpensive method to produce potable water with limited infrastructure and to accelerate resource concentration processes. However, higher evaporation rates and more scalable evaporator designs are needed to achieve practical implementation. In this work, we assessed the integration of conical reflectors with three-dimensional evaporator materials to enhance light capture for boosted evaporation efficiency. Across varying geometric parameters, we observed multifold enhancements in the quantity of water evaporated but a decrease in the normalized evaporation rate due to the large projected area of the reflectors. Both of these phenomena correlated directly with the reflector angle and the exposed height of the evaporator, as wider and taller structures captured more light and offered greater surface area for evaporation. We explored how reflectors could be arranged in large-scale arrays for more efficient space utilization and suggest that the evaporation rate normalized to the active or projected area of a single evaporator may not be a suitable indicator of its potential performance at larger scales.

Two-dimensional (2D) materials are physical building blocks of laminar membranes with interlayer channels for ion and molecular transport. Here, we systematically investigate the influence of lateral sheet size on the ion permeability and structural organization of vermiculite membranes. We show that the sheet size plays a significant role in governing the microstructure of these laminar systems. High resolution x-ray diffraction analysis reveals changes in mosaic distribution and vertical domain size depending upon exfoliate lateral size, leading to changes in the degree of polycrystallinity of the membrane. As these structural variations influence ion transport processes through the membrane, we highlight the need of careful size control of exfoliated 2D materials and structural disorder analysis for 2D laminar membrane development.

ABSTRACT Separating crude oil from water remains one of the most stubborn challenges in environmental remediation, especially for surfactant‐stabilized emulsions that resist conventional demulsification methods. Here, we report a scalable strategy for achieving near‐zero‐discharge separation of crude oil emulsions using a single superhydrophilic membrane. By applying low‐temperature atomic layer deposition (ALD) of various metal oxides onto activated polyvinylidene fluoride (PVDF) membranes, we create atomically precise surface‐engineered (SE) membranes that maintain an exceptionally strong hydration layer at the membrane‐feed interface, even at high oil loadings. Among the various metal oxides, TiO 2 ‐modified SE membranes exhibit superior interfacial water stability, enabling sustained dewatering of complex crude oil‐water emulsions with >98% separation efficiency and >97% water recovery, compared to only 24.6% water recovery for the pristine membrane. This separation performance surpasses conventional hydrophilic membranes and is comparable to complex Janus channel membrane systems, demonstrating near‐complete emulsion separation using a single membrane. This low‐temperature membrane surface engineering process with atomic‐level precision and potential for scalability via roll‐to‐roll fabrication is promising for industrial‐scale, energy‐efficient water treatment and oil spill remediation applications.

Magic-size metal chalcogenide clusters of molecular size exhibit well-defined structure and unique properties that might be further expanded with the incorporation or substitution of a second metal. We report the postmodification of magic-size clusters synthesized in polymer thin films via exposure to volatile metal organic precursors commonly utilized for atomic layer deposition. Exposure of In6S6(CH3)6 clusters to dimethylcadmium results in exposure-dependent incorporation of Cd2+, which extends the optical absorbance of the clusters into the visible spectrum. The mechanism for Cd2+ incorporation is consistent with Cd2+ replacement of In3+ that includes methyl ligand removal to maintain charge neutrality. Even for clusters embedded in a polymer matrix, ligand loss leads to sintering and transformation into larger nanoscale aggregates with zinc blende-type structure. The extent of Cd incorporation can be modulated by varying the process temperature and volatile metal organic exposure as well as the choice of volatile metal organic precursor. A computational thermodynamic analysis of heteroatom incorporation for several metals and chemistries reveals that both the stability of the substituted cluster and the favorability of reaction byproducts jointly determine the favorability of cation incorporation.

CsPbBr3 perovskite semiconductors have emerged as a leading candidate for next-generation radiation detectors because of their exceptional charge transport properties, defect tolerance, and record-breaking sensitivity and energy resolution. Their long-term stability, however, is hindered by electrode-driven electrochemical decomposition, which is accelerated by moisture- and oxygen-assisted ion migration during operation. Here, we investigated organic and inorganic encapsulation strategies as both environmental barriers and means to suppress interfacial degradation pathways. Atomic layer deposition of Al2O3 provided a conformal passivation layer that blocked environmental ingress, suppressed ionic diffusion, reduced leakage current, enhanced energy resolution, and expanded the operational electric-field window beyond 5 kV cm-1. By contrast, organic encapsulants such as paraffin wax and polystyrene slowed moisture diffusion but did not suppress interfacial reactions, with wax extending stability to over 90 days. These results show that ALD-Al2O3 suppresses dominant interfacial degradation pathways, enabling stable, high-field operation and advancing the practical deployment of CsPbBr3 gamma-ray detectors.

Rapid industrial growth has increased the need for efficient membranes to separate oil-water emulsions. Polyvinylidene fluoride (PVDF) membranes, although widely used due to their chemical inertness and favorable mechanical properties, suffer from fouling due to their intrinsic hydrophobicity. Modifying these membranes after fabrication offers a practical solution as it easily fits into existing large-scale manufacturing processes. Atomic layer deposition (ALD), an atomically-precise vapor phase surface modification technique, can create ultrathin metal oxide layers that greatly improve membrane hydrophilicity without significantly affecting the original pore size. However, PVDF's lack of reactive chemical moieties makes ALD challenging. Here, we present a simple alkali treatment that greatly enhances ALD nucleation and growth on PVDF membranes. This treatment imparts exceptional oil-water emulsion separation capabilities and antifouling behavior in PVDF membranes after just a few ALD cycles, surpassing the performance of PVDF membranes coated with hundreds of ALD cycles. This dramatic reduction in the number of ALD cycles required could enable cost-effective modification of commercial PVDF membranes at scale using spatial, roll-to-roll ALD. These modified membranes outperform reported modified PVDF membranes, with >99 % permeance recovery and <1 % irreversible loss of permeance and >98 % oil rejection from oil-water emulsions over 100 h continuous operation, making them promising for advanced water purification technologies.

Atomic layer deposition (ALD) of zinc oxide (ZnO) has been widely researched using diethyl zinc (DEZ)-based methods. The significant importance of thin films of ZnO as transparent conductive oxides (TCO) in optoelectronic devices and photovoltaics warrants examining alternative Zn precursors for ZnO ALD as potential replacements for the pyrophoric DEZ. In this study, we investigated three alternative Zn precursors: Zn(EEKI)2, Zn(DMP)2, ZnEt(HMDS), in the process development for high-quality ZnO thin films and compared them to DEZ. The ALD processes were studied using in situ spectroscopic ellipsometry. The properties of the ALD ZnO films were characterized using ex situ X-ray photoelectron spectroscopy (XPS), Rutherford backscattering spectrometry and nuclear reaction analysis (RBS/NRA), X-ray diffraction (XRD), atomic force microscopy (AFM), transmission electron microscopy (TEM), and ultraviolet-visible (UV/Vis) spectrophotometry. These measurements confirmed the formation of pure, stoichiometric, and polycrystalline ZnO films using all four Zn precursors. Although the selected precursors are chemically diverse Zn compounds, they all yielded saturating ALD processes and high-quality ZnO thin films at 200 °C. This study highlights the potential benefits of alternative zinc precursors in designing ALD processes for ZnO thin films.

Atomic layer deposition (ALD) is widely used to deposit conformal thin films but is often limited in the tunability of the resulting material's properties. Substrate bias and electric fields alter precursor-surface interactions and provide means to tune material properties. To explore this, we performed zinc oxide (ZnO) ALD using diethylzinc (DEZ) and water on silicon native oxide substrates at 150 degrees C in a sample holder designed to create a static electrical field by biasing one plate of a parallel plate capacitor-style sample holder during deposition. ZnO films prepared in an electric field/on a biased sample holder were thinner, changed relative crystalline composition, and contained more carbon compared to samples grown in identical sample holders without bias. The thickness was independent of the magnitude of the eletric field between plates, indicating that the primary driver for the change was substrate biasing not the electric field between plates of the parallel plate capacitor-style sample holder. Density functional theory calculations showed enhanced electron migration between dissociatively adsorbed DEZ molecules and the ZnO (002) facet with increasing force from an electric field at the substrate surface, which strengthens the electronic interactions between the surface and the adsorbate. These models offer a compelling explanation for the inhibited growth, changes in the crystallinity, and increase in carbon content of films grown in an electric field/on biased plates.

In this work, we introduce the design of an atomic layer deposition (ALD) reactor augmented with an AI interface for autonomous materials synthesis. Our modular design encapsulates the particularities of the hardware behind a Python interface that communicates with the ALD control software via transmission control protocol. This interface is compatible with model context protocol interfaces used in agentic frameworks. We have integrated our tool with a simple AI agent that leverages a large language model to transform user-supplied queries into ALD processes that are then run in our reactor. Our approach uses a JavaScript object notation schema to encode ALD processes. Our experimental results show that the AI interface does not impose a significant overhead to our control software, at least within our fastest 10 ms scale. We also carried out a detailed evaluation of the agent performance using leading models in two classes of tasks: basic instruction and process discovery tasks, where the agent is presented with a target material and needs to identify the correct ALD process compatible with the reactor configuration. Despite the simplicity of our agent design, we observed that most of the advanced models excelled at the instruction tasks. However, only recent models, such as o1, o3, GPT-5, and Claude Opus 4, performed well in process discovery tasks. We also observed significant variability in the response for the hardest challenges. While the results obtained are promising, we identify areas where AI research could improve the performance of agents for ALD.

Sulfide-based all-solid-state batteries (ASSBs) are considered a promising alternative to state-of-the-art Li-ion batteries due to their high gravimetric and volumetric energy density, as well as improved safety. Unfortunately, sulfide solid-state electrolyte, such as Li 6 PS 5 Cl (LPSCl), can undergo chemical and electrochemical reactions with cathode materials during cycling, leading to significant chemo-mechanical challenges. Moreover, LPSCl is highly sensitive to moisture and air, resulting in the evolution of H 2 S gas and the formation of electrochemically inactive and resistive interfacial layers. Atomic layer deposition (ALD) can play a critical role in suppressing the decomposition of LPSCl by forming an ultra-thin, conformal, and chemically/electrochemically stable buffer layer that protects the particle surface from degradation. With proper design, this layer can also enhance ionic conductivity and mechanical properties while reducing electronic conductivity. However, the reaction mechanism of ALD on LPSCl has not yet been systematically studied. Here, we elucidate the mechanism for Al 2 O 3 ALD using trimethyl aluminum (TMA) and H 2 O on LPSCl for ASSBs through a combination of in situ and ex situ experiments supported by density functional theory (DFT) calculations. In situ Fourier transform infrared (FTIR) spectroscopy measurements identified the functional groups on the LPSCl surface that participate in the TMA chemisorption and the subsequent H 2 O reaction during the first Al 2 O 3 ALD cycle. The FTIR measurements also revealed the steady Al 2 O 3 growth on the LPSCl with repeated ALD cycles. Ex situ X-ray photoelectron spectroscopy (XPS) measurements unveiled the chemical bonding following the TMA and H 2 O reactions and ex situ Raman spectroscopy measurements showed that there are no bulk changes in the LPSCl structure as a result of the Al 2 O 3 ALD. DFT calculations helped to discriminate between candidate reactions of the ALD precursors on the LPSCl surface. This work not only provides insights into optimizing ALD process parameters for LPSCl but also informs broader efforts in designing interfacial modifications for a wide range of sulfide-based solid electrolytes.

While neutral aqueous metal batteries, featuring cost-effectiveness and non-flammability, hold significant potential for large-scale energy storage, their practical application is hampered by the limited specific capacity of cathode materials (<500 mAh g(-1)). Herein, capacity-oriented CoS2 and rate-optimized Co9S8 cathodes are developed based on the aqueous copper ion system. The charge-storage mechanism is systematically investigated through a series of ex-situ tests and density functional theory calculations, focusing on the reversible transitions of Co9S8 -> Cu7S4 -> Cu9S5/Cu1.8S and CoS2 -> Cu7S4 -> Cu2S, which are associated with the redox reactions of Cu2+/Cu+& Vert;Co2+/Co and Cu2+/Cu+& Vert;S-2(2-)/S2-, respectively. The electrochemical results show that CoS2 can exhibit a superior capacity of 619 mAh g(-1) at 1 A g(-1) after 400 cycles, while Co9S8 maintains an outstanding rate performance of 497 mAh g(-1) at 10 A g(-1) (the retention rate is 95 % compared to 521 mAh g(-1) at 1 A g(-1)). As a proof of concept, an advanced CoS2//Zn hybrid aqueous battery demonstrates a working voltage of 1.20 V and a specific energy of 663 Wh kg(cathode)(-1). This work provides an alternative direction for developing sulfide cathodes in energetic aqueous metal batteries. (c) 2025 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.

Area-selective atomic layer deposition (AS-ALD) is a promising bottom-up strategy for enabling self-aligned patterning in semiconductor manufacturing, reducing process complexity, cost, and edge placement errors. In particular, AS-ALD of metals on dielectric surfaces (MoD) is gaining increasing attention for advanced interconnect applications, such as middle-of-line, back-end-of-line, etc. The AS-ALD MoD process enables metal deposition on a target dielectric surface while blocking growth on other metal or dielectric surfaces. However, achieving selectivity between chemically similar dielectric surfaces – MoD/D (metal on dielectric with a non-growth dielectric area) remains highly challenging due to their comparable surface terminations, surface energies, and reactivity toward metal precursors. In this work, we explore the selective deposition of Ru on SiO 2 versus Al 2 O 3 surfaces using an aldehyde-based inhibitor, butyraldehyde (BTA), and a novel Ru precursor, C 4 H 6 Ru(CO) 3 . The results reveal selective Ru growth on SiO 2 , but not on the BTA-inhibited Al 2 O 3 surface. Interestingly, the aldehyde-based inhibitor was previously reported to adsorb on nitride surfaces but not on hydroxyl-terminated oxide surfaces. The adsorption behavior of the inhibitor on various surfaces was investigated via water contact angle (WCA) and Fourier transform infrared spectroscopy (FTIR) analysis. Selectivity was calculated using ellipsometry, X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM). This work presents a new approach for AS-ALD of MoD/D and self-aligned Ru patterning for next-generation semiconductor fabrication.

Trimethylaluminum (TMA) is a widely used precursor for atomic layer deposition (ALD) of aluminum-based coatings, such as Al₂O₃ (with H₂O), AlF₃ (with HF-pyridine), and Al₂S₃ (with H₂S), all achieved via well-established ALD reaction mechanisms. These processes have enabled the deposition of ultrathin, conformal coatings on a range of substrates, including critical components of battery systems. While TMA-based ALD is frequently applied to enhance the electrochemical performance of cathodes, anodes, and solid electrolytes, most prior studies have focused primarily on the resulting battery performance, rather than the underlying surface chemistry involved. In our recent work, we have investigated the unique chemical interactions between TMA and reactive battery materials, with a particular emphasis on lithium-containing cathodes (i.e., Nickel Manganese Cobalt oxide, NMC). We discovered that TMA can directly react with surface impurities—especially lithium carbonate—present on the cathode surface, leading to the formation of protective interfaces that deviate from conventional ALD growth pathways. This reactive surface functionalization not only improves interfacial stability but also offers a new approach for modifying cathode surfaces without full ALD cycling. In this presentation, we will highlight the novel surface chemistry observed between TMA and LIB cathode materials, supported by in situ FTIR, in situ quadruple mass spectroscopy (QMS), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy with elemental analysis (SEM-EDS), and Raman spectroscopy. Our findings provide insight into how TMA can serve as a standalone surface functionalization precursor, opening up new opportunities for simplified, scalable surface engineering of battery cathodes.

In this work, we introduce an open-ended question benchmark, ALDbench, to evaluate the performance of large language models (LLMs) in materials synthesis, and, in particular, in the field of atomic layer deposition, a thin film growth technique used in energy applications and microelectronics. Our benchmark comprises questions with a level of difficulty ranging from the graduate level to domain expert current with the state of the art in the field. Human experts reviewed the questions along the criteria of difficulty and specificity, and the model responses along four different criteria: overall quality, specificity, relevance, and accuracy. We ran this benchmark on an instance of OpenAI’s GPT-4o. The responses from the model received a composite quality score of 3.7 on a 1–5 scale, consistent with a passing grade. However, 36% of the questions received at least one below average score. An in-depth analysis of the responses identified at least five instances of suspected hallucination. Finally, we observed statistically significant correlations between the difficulty of the question and the quality of the response, the difficulty of the question and the relevance of the response, the specificity of the question, and the accuracy of the response as graded by the human experts. This emphasizes the need to evaluate LLMs across multiple criteria beyond difficulty or accuracy.