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At least 19 records

Ultrawide bandgap semiconductor h-BN for direct detection of fast neutrons

III-nitride wide bandgap semiconductors have contributed on the grandest scale to many technological advances in lighting, displays, and power electronics. Among III-nitrides, BN has another unique application as a solid-state neutron detector material because the isotope B-10 is among a few elements that have an unusually large interaction cross section with thermal neutrons. A record high thermal neutron detection efficiency of 60% has been achieved by B-10 enriched h-BN detectors of 100 μm in thickness in our group. However, direct detection of fast neutrons with energies above 1 MeV is highly challenging due to the extremely low interaction cross section of fast neutrons with matter. We report the successful attainment of 0.4 mm thick freestanding h-BN 4"-diameter wafers, which enabled the demonstration of h-BN fast neutron detectors capable of delivering a detection efficiency of 2.2% in response to a bare AmBe neutron source. Furthermore, it was shown that the energy information of incoming fast neutrons is retained in the neutron pulse-height spectra. A comparison of characteristics between h-BN fast and thermal neutron detectors is summarized. Neutron detectors are vital diagnostic instruments for nuclear and fusion reactor power and safety monitoring, oil field exploration, neutron imaging and therapy, as well as for plasma and material science research. With the outstanding attributes resulting from its ultrawide bandgap (UWBG), including the ability to operate at extreme conditions of high power, voltage, and temperature, the availability of h-BN UWBG semiconductor detectors with the capability of simultaneously detecting thermal and fast neutrons with high efficiencies is expected to open unprecedented applications that are not possible to attain by any other types of neutron detectors.

36 MATERIALS SCIENCE

Probing room temperature indirect and minimum direct band gaps of h-BN

Abstract Hexagonal boron nitride (h-BN) has attracted considerable interest as an ultrawide bandgap (UWBG) semiconductor. Experimental studies focused on the detailed near band-edge structure of h-BN at room temperature are still lacking. We report a direct experimental measurement of the near band-edge structure performed on h-BN quasi-bulk wafers via photocurrent excitation spectroscopy (PES). PES resolved the band-to-band transitions near M- and K-points in the Brillion zone (BZ), from which the room temperature indirect band gap of E g M K ∼6.02 eV, minimum direct bandgap at M-point of E g M = 6.36 eV and next lowest direct energy bandgap at K-point of E g K = 6.56 eV , have been simultaneously determined for the first time experimentally. The measured energy differences between K- and M-points in the conduction band minimum (CBM) and valence band maximum (VBM) are Δ E C M K = 0.54 eV and Δ E V M K = 0.34 eV, respectively, in good agreement with the calculation results. Significantly differing from its III-nitride wurtzite counterparts, in which only electrons and holes in the conduction and valence band extremes at the Γ-point are predominantly involved in the optical and transport processes, the results highlighted that charge carriers associated with both M- and K-valleys control to the optical excitation, recombination and charge transport processes in h-BN.

Physics

Exciton Enhanced Nonlinear Optical Responses in Monolayer h-BN and MoS 2 : Insight from First-Principles Exciton-State Coupling Formalism and Calculations

Excitons are vital in the photophysics of materials, especially in low-dimensional systems. The conceptual and quantitative understanding of excitonic effects in nonlinear optical (NLO) processes is more challenging compared to linear ones. Here, we present an ab initio approach to second-order NLO responses, incorporating excitonic effects, that employs an exciton-state coupling formalism and allows for a detailed analysis of the role of individual excitonic states. Taking monolayer h-BN and MoS 2 as two prototype 2D materials, we calculate their second harmonic generation (SHG) susceptibility and shift current conductivity tensor. We find strong excitonic enhancement in the NLO responses requires that the resonant excitons are not only optically bright themselves but also able to couple strongly to other bright excitons. Our results explain the occurrence of two strong peaks in the SHG of monolayer h-BN and why the A and B excitons of MoS 2 unexpectedly exhibit minimal excitonic enhancement in both SHG and shift current generation.

36 MATERIALS SCIENCE

Sieving Hydrogen Isotopes via Machine Learning Assisted Chemical Vapor Deposition (CVD) of High‐Quality Monolayer Hexagonal Boron Nitride (h‐BN) on Iron Foils

Atomically thin two-dimensional (2D) ceramics, such as monolayer hexagonal boron nitride (h-BN), present potential for disruptive advances in separations. However, sub-atomic scale separation of hydrogen isotopes (H + /D + ) require near pristine 2D material membranes, and scalable synthesis of such high-quality h-BN comparable to mechanically exfoliated crystals remains a significant challenge. Here, we report a scalable Fe-catalyzed chemical vapor deposition (CVD) process for bottom-up synthesis of large-area, high-quality monolayer h-BN films, overcoming key limitations of conventional ammonia-based routes. By leveraging mechanistic insights and higher CVD temperatures, we suppress multilayer formation and achieve uniform monolayer h-BN coverage on commercially available Fe foils. Machine learning enables systematic exploration of the complex, multi-dimensional CVD parameter space (growth time, temperature, precursor temperature, multilayer faction, coverage), providing data-driven approaches to visualize and identify process regimes facilitating predominantly monolayer h-BN growth with minimal secondary nuclei/ad-layers. The optimized Fe-catalyzed CVD h-BN membranes show high-quality as observed by proton/deuteron (H + /D + ) selectivity ≈8.45, approaching the highest quality benchmark of mechanically exfoliated h-BN (H + /D + selectivity ≈10) as well as significantly outperforming Cu-catalyzed CVD h-BN membranes (H + /D + selectivity ≈3.62, control selectivity ≈1.7). Our work provides a scalable cost-effective route for high-quality monolayer h-BN synthesis for sub-atomic scale separations (H + /D + ) and demonstrates the broader potential of machine learning-guided optimization of CVD for advancing synthesis of 2D materials.

36 MATERIALS SCIENCE

Fundamental optical transitions in hexagonal boron nitride epilayers

Fundamental optical transitions in hexagonal boron nitride (h-BN) epilayers grown on sapphire by metal–organic chemical vapor deposition (MOCVD) using triethylboron as the boron precursor have been probed by photoluminescence (PL) emission spectroscopy. The low temperature (10 K) PL spectrum exhibits two groups of emission lines. The first group includes the direct observation of the free exciton and impurity bound exciton (BX) transitions and phonon replicas of the BX transition, whereas the second group is attributed to the direct observation of the band-to-band transition and its associated phonon replicas. The observations of zero-phonon lines of the band-to-band and exciton transitions, which are supposedly forbidden or “dark” in perfect h-BN crystals, result from a relaxed requirement of momentum conservation due to symmetry-breaking in the presence of high concentrations of impurities/defects and strain, which in turn provided more deterministic values of the energy bandgap (E g ), exciton binding energy (E x ), and binding energy of impurity bound excitons (E BX ) in h-BN epilayers. Excitonic parameters of h-BN epilayers grown by MOCVD, carbon-free chemical vapor deposition, and high purity h-BN bulk materials are compared and discussed. The present results, together with available information in the literature, represent a significant improvement in the understanding of the fundamental optical properties and excitonic parameters of h-BN ultrawide bandgap semiconductors.

36 MATERIALS SCIENCE

Scalable Bottom-Up Synthesis of Nanoporous Hexagonal Boron Nitride ( h -BN) for Large-Area Atomically Thin Ceramic Membranes

Nanopores embedded within monolayer hexagonal boron nitride (h-BN) offer possibilities of creating atomically thin ceramic membranes with unique combinations of high permeance (atomic thinness), high selectivity (via molecular sieving), increased thermal stability, and superior chemical resistance. However, fabricating size-selective nanopores in monolayer h-BN via scalable top-down processes remains nontrivial due to its chemical inertness, and characterizing nanopore size distribution over a large area remains extremely challenging. Here, we demonstrate a facile and scalable approach of exploiting the chemical vapor deposition (CVD) process temperature to enable direct incorporation of subnanometer/nanoscale pores into the monolayer h-BN lattice, in combination with manufacturing compatible polymer casting to fabricate centimeter-scale nanoporous atomically thin ceramic membranes. We leverage diffusive transport of analytes including size-selective Ficoll sieving to characterize subnanometer-scale and nanoscale defects that manifest as pores in centimeter-scale h-BN membranes, overcoming previous limitations in large-area characterization of nanoscale defects in h-BN. Our approach opens a new frontier to advance atomically thin membranes to 2D ceramic materials, such as h-BN via facile and direct formation of nanopores, for size-selective separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Room-temperature high-purity single-photon emission from carbon-doped boron nitride thin films

Hexagonal boron nitride (h-BN) has emerged as a promising platform for generating room temperature single photons exhibiting high brightness and spin-photon entanglement. However, improving emitter purity, stability, and scalability remains a challenge for quantum technologies. Here, we demonstrate highly pure and stable single-photon emitters (SPEs) in h-BN by directly growing carbon-doped, centimeter-scale h-BN thin films using the pulsed laser deposition (PLD) method. These SPEs exhibit room temperature operation with polarized emission, achieving a g (2) (0) value of 0.015, which is among the lowest reported for room temperature SPEs and the lowest achieved for h-BN SPEs. It also exhibits high brightness (~0.5 million counts per second), remarkable stability during continuous operation (>15 min), and a Debye-Waller factor of 45%. First-principles calculations reveal unique carbon defects responsible for these properties, enabled by PLD’s low-temperature synthesis and in situ doping. Our results demonstrate an effective method for large-scale production of high-purity, stable SPEs in h-BN, enabling robust quantum optical sources for various quantum applications.

36 MATERIALS SCIENCE

First-Principles Simulations Correlating X-ray Absorption Spectroscopy Features to Point Defects in h -BN

Hexagonal boron nitride (h-BN) is a promising material for a range of emerging applications in electronics, quantum information technology, and energy storage. Soft X-ray absorption spectroscopy (XAS) is powerful to reveal atomic details of BN, especially in the presence of defects. However, correlating XAS spectral features with specific defect types remains elusive. In this Letter, we report B K-edge XAS measurements of sputter-deposited turbostratic h-BN films and use a combination of first-principles spectroscopic simulations and analysis of detailed electronic structure and local charge transfer characteristics to elucidate their unique spectroscopic features. Our results show that the two main defect-related peaks, between the main π* resonances of h-BN and B2O3, as typically observed in BN films deposited by energetic condensation or bombarded with energetic ions, are associated with electronic states of H-passivated B atoms bonded to one and two oxygen impurity atoms, respectively. These conclusions hold significant implications for applications relying on defect-mediated properties of h-BN.

chemical structure

First-Principles Study of Molecular Hydrogen Activation by Defects in Boron Nitride

Here, we used density functional theory simulations in combination with ab initio thermodynamics to determine the H 2 partial pressure (p H2 )-dependent energetics associated with H 2 activation and recovery at various defect sites in hexagonal boron nitride (h-BN). We found that some defects are very reactive with hydrogen, thereby definitely trapping hydrogen in defective h-BN. However, depending on hydrogen partial pressure, less reactive defect sites can be populated. Because of the lower binding capability of these sites, they would allow hydrogen to be recycled and recovered. For small defect sizes, we found that hydrogen preferentially binds to nitrogen sites by forming N–H bonds, and if no N sites are available then boron sites would be the next to bind hydrogen. Hydrogen dissociation via frustrated Lewis pair is found to be more favorable than forming only N–H bonds but only if the defect size is large enough to accommodate steric effects. For specific conditions such as T = 400 K, p H2 = 1 bar, and only considering one molecular H 2 per defect, three defects, namely, the N monovacancy, 3V(1B2N), and hexagonal 6V(3B3N) could play a role in both the activation and recycling of H 2 as they would be reacting enough to allow a favorable splitting of H 2 while not binding too strongly to allow its recovery. More broadly, a range of p H2 and hydrogen loading conditions were investigated for different types of defects and the finding suggests that p H2 could be used to fine-tune the Gibbs free energy of hydrogenation, thereby allowing several types of defects at different hydrogen loading contents to play a role in the activation/recovery process of H 2 in defective h-BN.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Transforming Boron Carbon Nitride: A Carbon-to-Oxygen Switch to Boost Propane Oxidative Dehydrogenation

Hexagonal boron nitride (h-BN) catalysts exhibit high alkene selectivity in the oxidative dehydrogenation of propane (ODHP). Nevertheless, the conversion-selectivity trade-off persisted primarily due to the low density of oxygen-containing boron active species, while simple and controllable modification strategies for h-BN still face challenges. Herein, we developed an in situ carbon-to-oxygen switch strategy within a tailored boron carbon nitride (BCN) framework, in which uniformly embedded B–C 3 were transformed into B–O 3 via oxidative treatment (denoted as BNO x ). The structural evolution from B–C 3 to B–O 3 was well characterized by spectroscopy and soft X-ray absorption techniques. The resulting BNO x catalysts, enriched with B–O 3 units, demonstrated performance in ODHP, achieving a propane conversion of 50.4% with 32.7% olefin yield at 500 °C. Density functional theory (DFT) calculations confirmed that B–O 3 species preferentially lower activation barriers, rendering the process thermodynamically more favorable. In conclusion, this work introduced an in situ reconstruction method for atomic-level heteroatom-engineered h-BN catalysts, opening an avenue for advanced catalyst design across energy conversion systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Origin of large variations of current on/off ratio and switching voltage in atomically thin memristors: an exascale ab initio transport study

Nonvolatile resistive switching in two-dimensional monolayers opens a new avenue for high-density memory/computing devices. However, questions remain as to why the current on/off ratio and switching voltage vary significantly among different devices. Here, we simulate electronic transport of large systems consisting of a h-BN monolayer sandwiched by gold electrodes, enabled by an implementation of the nonequilibrium Green’s function method in the exascale density functional theory (DFT) code: Real-space MultiGrid. Systematic calculations reveal that the wide range of on/off ratios is due to variations in interface distances between the electrode and h-BN that significantly modulate their wavefunction overlap. In addition, DFT calculations demonstrate that the energy barrier of a gold atom dissociating from the electrode to h-BN increases dramatically with the interface distance, thereby explaining the strong dependence of the switching voltage on distance. Our work demonstrates the significance of interface distance in governing the current on/off ratio and switching voltage.

Electronic devices

Energy Barriers for H 2 Uptake and Release by Defects in Boron Nitride

Density functional theory simulations (DFT) have been used in combination with the climbing image nudged elastic band method (CI-NEB) to determine the energy barriers required to dissociate H 2 at four types of h-BN defects and evaluate the potential for reacted H species to hop to adjacent available sites. The defects were selected based on previous work in which ab initio thermodynamics was used to identify specific defects with optimal thermodynamics for reversible H 2 storage, that is, the defects would dissociate molecular H 2 while not binding H species too strongly so that hydrogen release is favorable. The four defects investigated are the N and B monovacancies, which only offer either B or N defective sites respectively, as well as larger cluster vacancy defects named 3V(1B2N) and hexagonal 6V(3B3N), which present a mixture of B and N defect sites available for H binding. While homogeneous H 2 dissociation by B and N monovacancies have energy barriers larger than 0.4 eV, we found that mixed BN terminated defects have energy barrier lower than 0.4 eV for H 2 dissociation. In particular, H 2 dissociation by the hexagonal 6V(3B3N) defect, exclusively made of Frustrated Lewis Pairs (FLPs), is almost barrierless. The energy barrier for subsequent H hopping to available adjacent B or N sites of the defect were also calculated. It was found that the hopping of H species generally involves high energy barriers ranging from 0.26 eV to 2.57 eV. In conclusion, this work completes previous thermodynamic theoretical investigations and provides a more comprehensive picture of H 2 reaction with defective h-BN for potential H 2 storage and recovery.

Sassi, Michel J. [Pacific Northwest National Labor

Ionic‐Liquid Free and Flexible Transistors Made of 2D Material Inks

The development of thin-film transistors (TFTs) using 2D materials is crucial for enabling scalable, low-cost, and flexible electronics. Currently, 2D TFTs with the highest performance have been achieved by using ionic-liquid gating (ILG), a technique suited for proof-of-concept studies. However, ILG suffers from slow switching speeds, temperature sensitivity, poor long-term stability, and integration challenges, making it unsuitable for practical use. Moreover, typical fabrication methods for 2D TFTs involve harsh conditions such as strong acids or high temperatures (>300 °C), limiting integration with flexible substrates. This work provides the first demonstration of an ILG-free, all-2D-material TFT fabricated onto a flexible substrate. Water-based graphene and hexagonal boron nitride (h-BN) inks are printed to deposit the electrodes and dielectric layers, respectively. The MoS 2 channel is produced via supramolecular interfacial self-assembly, yielding uniform, monolayer-rich films transferable to rigid and flexible substrates. The resulting TFTs operate below 3 V, exhibit negligible leakage current, and achieve field-effect mobilities up to 0.46 cm 2 V −1 s −1 (rising to 2.47 cm 2 V −1 s −1 with silver electrodes) measured under ambient conditions, while maintaining excellent mechanical flexibility. This work establishes a low-cost and scalable solution-processable platform for flexible electronics based on 2D materials that match requirements for practical applications.

2D materials

Intrinsic Layer-Dependent Surface Energy and Exfoliation Energy of van der Waals Materials

Stacking and twisting 2D van der Waals (vdW) layers have become versatile platforms to tune the electron correlation. These platforms rely on exfoliating vdW materials down to a single vdW layer and a few vdW layers. We calculate the intrinsic layer-dependent surface and exfoliation energies of typical vdW materials such as graphite, h-BN, black P, MX 2 (M = Mo or W; X = S, Se, or Te), MX (M = Ga or In; X = S, Se, or Te), Bi 2 Te 3 , and MnBi 2 Te 4 using density functional theory. For exchange-correlation functionals with explicit vdW interaction, a single vdW layer always has the smallest surface energy, giving a surface energy reduction when compared to that of thicker vdW layers. Furthermore, the magnitude of this surface energy reduction quickly decreases with an increase in the number of atomic layers inside the single vdW layer for different vdW materials. Such atomic-layer dependence in surface energy reduction helps explain the different effectiveness of exfoliation for different vdW materials down to a single vdW layer.

Anode materials

Transferable dispersion-aware machine learning interatomic potentials for multilayer transition metal dichalcogenide heterostructures

Stacking atomically thin transition metal dichalcogenides (TMDs) into heterostructures enables exploration of exotic quantum phases, particularly through twist-angle-controlled moiré superlattices. These structures exhibit novel electronic and optical behaviors driven by atomic-scale structural reconstruction. However, studying such systems with DFT is computationally demanding due to their large unit cells and van der Waals (vdW) interactions between layers. To address this, we develop a transferable neural network potential (NNP) that includes long-range vdW corrections up to 12Å with minimal overhead. Trained on vdW-corrected DFT data for Mo- and W-based TMDs with S, Se, and Te, the NNP accurately models monolayers, bilayers, heterostructures, and their interaction with h-BN substrates. It reproduces equilibrium structures, energy landscapes, phonon dispersions, and matches experimental atomic reconstructions in twisted WS2 and MoS2/WSe2 systems. We demonstrate that our NNP achieves DFT-level accuracy and high computational efficiency, enabling large-scale simulations of TMD-based moiré superlattices both with and without substrates.

materials for energy and catalysis

Restoration of weak localization in bilayer graphene by a molecular thin film

Quantum coherent effects can be probed in multilayer graphene through electronic transport measurements at low temperatures. In particular, bilayer graphene (BLG) is known to be susceptible to quantum interference corrections of the conductivity, presenting weak localization at all electronic densities, and dependent on different scattering mechanisms such as those related to the trigonal warping of the electron dispersion near the K and K′ valleys. Proximity effects with a molecular thin film influence these scattering mechanisms, which can be quantified through the known theory of magnetoconductance for BLG. Here, we present electronic transport measurements in a copper-phthalocyanine (CuPc) / BLG / hexagonal boron nitride (h-BN) heterostructure that suggest the restoration of weak localization in BLG, associated to a reduction of trigonal warping effects, that are known to suppress weak localization in BLG. Additionally, we observe a charge transfer of 3.6×10 12 cm −2 from the BLG to the molecules, as well as a very small degradation of the mobility of the BLG/h-BN heterostructure upon the deposition of CuPc. The molecular arrangement of the CuPc thin film is characterized in a control sample through transmission electron microscopy, that we relate to the electronic transport results.

bilayer graphene

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo

Editorial: Functionalization of porous materials for sustainable energy applications

Global energy demands are shifting toward a more sustainable future, with the goal of achieving carbon neutrality by 2050. Emerging technologies are driving this transition. The industry, academia, government, non-profit organizations, and the broader community are collaboratively working to reduce greenhouse gas (GHG) emissions and address climate change to ensure a sustainable future. According to the International Energy Agency, in 2022, the production, transportation, and processing of oil and gas resulted in 5.1 billion tons of CO 2 -equivalent emissions, representing nearly 15% of all energy-related GHG emissions. Moreover, the end-use of oil and gas accounted for an additional 40% of emissions. The IEA’s Net Zero Emissions by 2050 Scenario calls for immediate, collective action from the industry, transportation and other stakeholders to mitigate these emissions. In this effort, the development of energy materials will play a critical role in reducing emissions. Among these, porous materials offer an innovative solution, leveraging their high surface area, adjustable pore sizes, and chemical versatility to address these pressing challenges effectively. By carefully designing their nanostructures, the architecture and properties of these materials can be tailored for specific applications. Key factors such as chemical composition, particle size, pore distribution, and surface area optimization enhance the reactivity and energy conversion efficiency. Additionally, pre- and post-functionalization processes can introduce targeted chemical properties, further improving their performance. This Research Topic explores recent advancements in energy and materials science through four scholarly papers, showcasing innovative solutions for sustainable energy technologies while providing valuable insights into the unique properties and structure of porous materials (Figure 1). Li et al. present their work on highly defective NiFeV layered triple hydroxides, highlighting enhanced electrocatalytic activity and stability for oxygen evolution reactions (OER). Kovalskii et al. contribute a mini-review on hydrogen storage using hexagonal boron nitride (h-BN) and BN-based materials, offering an insightful overview of these promising materials. Chava et al. discuss their recent achievements in ceramic electrolytes used for improvement of performance of solid-state batteries. Lastly, Li et al. review the properties of porous materials with a focus on shrinkage behavior during the drying process, shedding light on key considerations for material design.

36 MATERIALS SCIENCE