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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Enhanced matter power spectrum from axion kination after Big Bang nucleosynthesis

Despite stringent constraints from Big Bang Nucleosynthesis (BBN) and cosmic microwave background (CMB) observations, it is still possible for well-motivated particle physics models to substantially alter the cosmic expansion history between BBN and recombination. In this work we consider two different axion models that can realize a period of first matter domination, then kination, in this epoch. We perform fits to both primordial element abundances as well as CMB data and determine that up to a decade of late axion domination is allowed by these probes of the early universe. We establish the implications of late axion domination for the matter power spectrum on the scales 1/Mpc ≲ k ≲ 10 3 /Mpc. Our 'log' model predicts a relatively modest bump-like feature together with a small suppression relative to the standard ΛCDM predictions on either side of the enhancement. Our 'two-field' model predicts a larger, plateau-like feature that realizes enhancements to the matter power spectrum of up to two orders of magnitude. These features have interesting implications for structure formation at the forefront of current detection capabilities.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2026

Satellite Optical Remote Sensing of Clouds and Aerosols: From Particle Single-Scattering and Gaseous Absorption Through Radiative Transfer to Retrieval Products

Clouds and aerosols are fundamental regulators of Earth’s radiation budget and climate system, influencing both solar and terrestrial radiation through scattering, absorption, and emission processes. Accurate characterization of their physical and radiative properties from space requires a rigorous understanding of particle single-scattering, gaseous absorption, and radiative transfer in the atmosphere, as well as reliable inversion methods. This review synthesizes the physical foundations and algorithmic implementations of satellite-based passive optical remote sensing of clouds and aerosols, spanning the ultraviolet to thermal infrared spectral range. Beginning with electromagnetic scattering theory and state-of-the-art methods for computing single-scattering by nonspherical particles and computationally efficient methods for accounting for atmospheric absorption, we discuss the radiative transfer framework underpinning cloud and aerosol retrievals. The connection between single-scattering and multiple-scattering is rigorously formulated. We then summarize operational and research-grade retrieval techniques, including cloud masking and thermodynamic phase determination, CO₂ slicing for cloud-top pressure, the Nakajima-King shortwave bi-spectral, and infrared split-window approaches for cloud optical thickness and effective particle size, inversion algorithms for determining aerosol properties from multi-spectral and/or multi-angle radiometric and polarimetric measurements, and active-passive sensing synergy. Examples of the global cloud and aerosol climatologies are illustrated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR). Furthermore, the unique strengths of active remote sensing techniques based on spaceborne lidar observations are briefly elaborated in the context of studying ice clouds composed of randomly and horizontally oriented ice crystals, which is a significant challenge for conventional passive remote sensing techniques. By connecting physical theory to practical retrievals, this review highlights both the maturity of current methodologies and the remaining challenges in reducing uncertainties in particle morphology, vertical structure, absorption, and aerosol-cloud interactions. Furthermore, the impact of artificial intelligence (AI) on atmospheric remote sensing is briefly addressed.

Aerosols↗
DOE OSTI2026

From Rules to Reasoning: A Survey of Large Language Model-Based Approaches to Scientific Hypothesis and Idea Generation

Scientific hypothesis generation represents a fundamental challenge in contemporary research due to exponentially expanding literature volumes and increasing disciplinary specialization. Large language models (LLMs) have emerged as transformative tools for automated scientific discovery, moving beyond traditional rule-based and literature-mining approaches. Four paradigmatic approaches define current LLM-driven hypothesis generation: direct prompting and fine-tuning methods, knowledge-enhanced frameworks integrating retrieval-augmented generation (RAG), multi-agent collaborative systems simulating research teams, and reasoning-focused approaches implementing cognitive architectures. Domain-specific applications demonstrate statistical equivalence to human expert performance in social psychology, experimental validation in biomedical research, and near-expert quality in astronomy. Evaluation methodologies encompass human expert assessment, LLM-as-judge frameworks, and comprehensive benchmarking systems. Technical challenges include hallucination management, knowledge integration limitations, and balancing novelty with feasibility. Future directions emphasize hybrid neural-symbolic architectures and sophisticated human-AI collaboration models for responsible scientific discovery acceleration.

AI-driven discovery↗
NASA NTRS2025

Metallurgical and Thermal Properties of 57Ni-40Ti-3Hf (wt%)

Selected properties of 57Ni-40Ti-3Hf (wt%) were measured to further develop this material for use in aerospace rolling-element bearings. The average grain size and microindentation hardness of the material at room temperature were 90 μm and 549 HV, respectively. From room temperature to 500 °C, electrical resistivity increased from 8.9×10–7 to 11.3×10–7 Ω⋅m, thermal expansion coefficients varied from 1.1×10–5 to 1.2×10–5 mm/mm⋅°C, specific heat increased from 0.44 to 0.53 W⋅sec/g⋅K, thermal diffusivity rose from approximately 0.003 to 0.005 cm2/sec and thermal conductivity increased from approximately 0.09 to 0.19 W/cm⋅K. The behavior of the material can be explained by well-known metallurgical theory. These results are expected to provide a basis for design and modeling of future aerospace components.

rule of mixtures↗
NASA NTRS2026

Does the International Space Station Leak DNA? Preliminary Results from the ISS External Microorganisms Payload

Existing crewed spacecraft like the ISS (International Space Station) leak by design. The ISS routinely releases gas to maintain life support systems and when astronauts exit the station to perform space walks. The chemical component of this leakage is well characterized, but the biological components are not. The ISS is not subject to planetary protection requirements, but planned missions to Mars will use similar systems and will be subject to planetary protection requirements. If detectable microorganisms are escaping through vents and or airlocks we may need to redesign our crewed habitats to minimize this type of contamination. To test the hypothesis that microorganisms from inside ISS are detectable on exterior surfaces an astronaut used the ISS External Microorganisms sampling kit (Rucker et al. 2018) to sample exterior surfaces of the ISS during an EVA (Extra Vehicular Activity) in January of 2025. These samples were returned to Earth for DNA extraction and sequencing. We successfully, extracted and sequenced bacterial, fungal and viral DNA from these samples that was not present in the negative controls. These results should help NASA refine the planetary protection requirements for crewed missions. Methods: The samples were collected using sterile, DNA free, buccal swabs (23 mm. diameter) housed in custom canisters. Each canister uses a 0.2 μm Teflon filter to maintain sterility as the caddy, holding 8 swabs moves in and out of vacuum. The astronaut sampled the: 1) airlock vestibule, 2) airlock thermal cover, 3) a gap in the micrometeorite shielding near the airlock, 4) a handrail near the airlock, 5) the Carbon Dioxide Removal Assembly vent, and 6) the Vacuum Exhaust System vent. The seventh swab was exposed to vacuum during the EVA without touching it to a surface. The eighth swab, a negative control, was not opened until the caddy returned to Earth. DNA was extracted from the swabs using a QIamp UCP Pathogen kit and prepared for sequencing on an Aviti (Element Biosciences) sequencer (Arslan et al. 2024). The resulting sequences were analyzed using the EDGE Bioinformatics platform (Li et al. 2017). The sequences were analyzed individually using tools like BLAST, GOTTCHA2, Kraken2, and PanGIA. The data were also assembled into metagenome assembled genomes) using tools like CONCOCT, MaxBin2 and MetaBAT2. Results: We successfully extracted and sequenced bacterial, archaeal, fungal and viral DNA from all seven samples. The handrail swab had the lowest number of reads (768,651) and the airlock thermal cover had the highest number of reads (8,819,230). These samples contain DNA from human associated bacteria (e.g. Crynebacterium riegelii ), fungi (.e.g. Penicillium rubens ), and viruses (e.g Alphapapillomavirus ). Conclusion: Preliminary interpretation suggest that the airlock and the space suits themselves are the largest sources of contaminant DNA. Most if not all of the DNA is from organisms known to be present inside the ISS. Vents attached to life support systems may be a lesser source of biological contamination. Further analysis should help NASA address planetary protection knowledge gaps for crewed missions.

Aaron B Regberg↗
DOE OSTI2024

Mechanically and Thermally Robust Gel Electrolytes Built from A Charged Double Helical Polymer

Polymer electrolytes have received tremendous interest in the development of solid-state batteries, but often fall short in one or more key properties required for practical applications. Herein, a rigid gel polymer electrolyte prepared by immobilizing a liquid mixture of a lithium salt and poly(ethylene glycol) dimethyl ether with only 8 wt% poly(2,2′-disulfonyl-4,4′-benzidine terephthalamide) (PBDT) is reported. The high charge density and rigid double helical structure of PBDT lead to formation of a nanofibrillar structure that endows this electrolyte with stronger mechanical properties, wider temperature window, and higher battery rate capability compared to all other poly(ethylene oxide) (PEO)-based electrolytes. The ion transport mechanism in this rigid polymer electrolyte is systematically studied using multiple complementary techniques. Li/LiFePO 4 cells show excellent capacity retention over long-term cycling, with thermal cycling reversibility between ambient temperature and elevated temperatures, demonstrating compelling potential for solid-state batteries targeting fast charging at high temperatures and slower discharging at ambient temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2025

From PINNs to PIKANs: recent advances in physics-informed machine learning

Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the past few years, significant advancements have been made in the training and optimization of PINNs, covering aspects such as network architectures, adaptive refinement, domain decomposition, and the use of adaptive weights and activation functions. A notable recent development is the Physics-Informed Kolmogorov-Arnold Networks (PIKANS), which leverage a representation model originally proposed by Kolmogorov in 1957, offering a promising alternative to traditional PINNs. In this review, we provide a comprehensive overview of the latest advancements in PINNs, focusing on improvements in network design, feature expansion, optimization techniques, uncertainty quantification, and theoretical insights. We also survey key applications across a range of fields, including biomedicine, fluid and solid mechanics, geophysics, dynamical systems, heat transfer, chemical engineering, and beyond. Lastly, we review computational frameworks and software tools developed by both academia and industry to support PINN research and applications.

Kolmogorov-Arnold networks↗
DOE OSTI2026

Role of Amorphous Chains in Nanoplastic Formation from Semicrystalline Polymers

Semicrystalline polymers, e.g., polyethylene terephthalate (PET), release micro- (100 nm to 1 mm) and nanoplastics (up to 100 nm) [MNPL] when they are degraded under quiescent conditions. However, the exact molecular mechanisms leading to material fragmentation into MNPL are unknown. Here, we monitor the evolution of chain molecular weight and the MNPL production kinetics during hydrolysis of PET pellets. We find that only ~0.6% of the amorphous phase ester bonds are hydrolyzed at the onset of MNPL release. Then, by combining a random scission model with measured amorphous spacings, we estimate that only ~15% of the stress transmitters in the amorphous phase, namely, bridges and entangled loops, have failed by this point. Thus, spontaneous fragmentation of the semicrystalline nanostructure occurs despite significant intercrystalline connectivity. We resolve this apparent contradiction by proposing that fragmentation can only occur when progressive tie-chain scission causes the material to undergo the ductile/brittle transition. Mechanistically, we speculate that the internal stresses responsible for material fragmentation are caused by processing (i.e., residual stresses) and/or sample densification induced by chemi-crystallization. We discuss additional factors that may affect our analysis and thus require further investigation, such as skin-core effects, preferential degradation of stress transmitters and/or recrystallization processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Smart building HVAC control challenge: experience and solutions from the ADRENALIN project

A smart building HVAC control competition crowdsourced and compared algorithms on fair and equal ground using the standardized BOPTEST framework. The competition attracted 138 participants, but only 9% submitted valid solutions for the final stage, highlighting the complexity of advanced HVAC control design. The winning solutions showed significant potential to reduce energy use and cost by shifting demand, without compromising occupant comfort. Across scenarios, thermal energy cost reductions of 36–76% relative to a baseline, were achieved. In peak heat periods, the cost reduction leveraged limited energy use reduction (0–15%), but more significant energy price reduction (34–62%). This shows smart controls' ability to avoid as much as possible consumption during the morning peak hours, when spot prices are tendentially the highest. Hosting the competition has highlighted challenges in creating competitions that both are fair and promotes solutions that are transferable to real life implementation.

BOPTEST↗
DOE OSTI2026

Spin‐Polarized Interfaces Redirect CO 2 Reduction From CO to Formate

Achieving high product selectivity in electrocatalytic carbon dioxide reduction (CO 2 RR) remains a critical challenge due to competition between multiple proton-coupled electron-transfer pathways on catalyst surfaces. Meanwhile, chirality-induced spin selectivity (CISS), which enables spin-polarized electron transport through chiral interfaces, has recently emerged as a promising strategy to modulate interfacial electrochemical reactions. Although the CISS effect has been shown to enhance selectivity and efficiency in the spin-sensitive oxygen evolution reaction (OER), its role in regulating CO 2 RR pathways and in stabilizing intermediates remains largely unexplored. Here, chiral molecules (R- and S-1,1′-bi-2-naphthyl-2,2′-diyl hydrogen phosphate, BNP) were integrated with SnO 2 to construct chiral-modified catalysts (R-BNP/SnO 2 and S-BNP/SnO 2 ). Compared with bare SnO 2 and racemic BNP-modified SnO 2 (Rac-BNP/SnO 2 ), the chiral catalysts exhibited a pronounced shift in product selectivity from CO toward formate production. Importantly, in-situ attenuated total reflectance surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS) reveals that the chiral interface selectively stabilizes the O-bound *OCHO intermediate associated with the formate pathway and modulates interfacial water structure and hydrogen-bonding dynamics. These findings demonstrate that spin-polarized interfacial electron transfer can regulate CO 2 RR pathway selectivity by modulating the stabilization of key intermediates. More broadly, this work establishes chiral spin-selective interfaces as a new strategy for regulating competitive electrocatalytic reaction pathways.

14 SOLAR ENERGY↗
DOE OSTI2025

From Pollutant Removal to Renewable Energy: MoS2-Enhanced P25-Graphene Photocatalysts for Malathion Degradation and H2 Evolution

The widespread presence of pesticides—especially malathion—in aquatic environments presents a major obstacle to conventional remediation strategies, while the ongoing global energy crisis underscores the urgency of developing renewable energy sources such as hydrogen. In this context, photocatalytic water splitting emerges as a promising approach, though its practical application remains limited by poor charge carrier dynamics and insufficient visible-light utilization. Herein, we report the design and evaluation of a series of TiO2-based ternary nanocomposites comprising commercial P25 TiO2, reduced graphene oxide (rGO), and molybdenum disulfide (MoS2), with MoS2 loadings ranging from 1% to 10% by weight. The photocatalysts were fabricated via a two-step method: hydrothermal integration of rGO into P25 followed by solution-phase self-assembly of exfoliated MoS2 nanosheets. The composites were systematically characterized using X-ray diffraction (XRD), Raman spectroscopy, transmission electron microscopy (TEM), UV-Vis diffuse reflectance spectroscopy (DRS), and photoluminescence (PL) spectroscopy. Photocatalytic activity was assessed through two key applications: the degradation of malathion (20 mg/L) under simulated solar irradiation and hydrogen evolution from water in the presence of sacrificial agents. Quantification was performed using UV-Vis spectroscopy, gas chromatography–mass spectrometry (GC-MS), and thermal conductivity detection (GC-TCD). Results showed that the integration of rGO significantly enhanced surface area and charge mobility, while MoS2 served as an effective co-catalyst, promoting interfacial charge separation and acting as an active site for hydrogen evolution. Nearly complete malathion degradation (~100%) was achieved within two hours, and hydrogen production reached up to 6000 µmol g−1 h−1 under optimal MoS2 loading. Notably, photocatalytic performance declined with higher MoS2 content due to recombination effects. Overall, this work demonstrates the synergistic enhancement provided by rGO and MoS2 in a stable P25-based system and underscores the viability of such ternary nanocomposites for addressing both environmental remediation and sustainable energy conversion challenges.

Chemistry↗
DOE OSTI2026

A Multicopper Oxidase from Paenibacillus Polyethylenelyticus JNU01 Oxidizes Polyethylene

Polyethylene (PE) is a widely used plastic that persists in the environment and resists breakdown via microbial degradation. In this work, we discovered a new bacterium, Paenibacillus polyethylenelyticus JNU01, that grows on a PE-like wax (PELW, 4 kDa) as its sole carbon source, causing chemical modifications to the substrate and releasing small-molecule products. Genomic and transcriptomic analyses identified a multicopper oxidase (PpMmcO) as a key enzyme candidate for this observed activity. PpMmcO promoted surface oxidation, increased hydrophilicity, and the release of small-molecule products such as ketones, alkanes, and alkenoic acids. Scanning electron microscopy confirmed surface damage on both PELW and post-use greenhouse PE films. Weight loss analysis showed mass losses of 5.2% for the PELW powder and 1.6% for the greenhouse PE film after treatment with wild-type PpMmcO. We propose a radical-mediated pathway catalyzed by PpMmcO. These findings identify a new bacterium and enzyme capable of promoting partial PE oxidation and provide insight into biological processes that may act on polyethylene.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Plasma flow generation and particle acceleration from expanding magnetic bubbles

Impulsive plasma dynamics in the laboratory are often driven by rising electric currents, yet their quantitative plasma response has not been well established. By means of fully kinetic particle-in-cell simulations and laser-driven capacitor-coil experiments, we show that a rising current expels plasma, forming an expanding magnetic bubble and accelerating particles. The expansion front velocity scales with the Alfvén speed determined by the magnetic field at its inner edge and the plasma density at its outer edge. This mechanism establishes impulsive current drive as a fundamental way that generates plasma flows and accelerates particles in laboratory plasmas, with potential relevance to astrophysics.

Zhang, Yang [Princeton University, NJ (United Stat↗
DOE OSTI2024

In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back

Computational chemistry is an indispensable tool for understanding molecules and predicting chemical properties. However, traditional computational methods face significant challenges due to the difficulty of solving the Schrödinger equations and the increasing computational cost with the size of the molecular system. In response, there has been a surge of interest in leveraging artificial intelligence (AI) and machine learning (ML) techniques to in silico experiments. Integrating AI and ML into computational chemistry increases the scalability and speed of the exploration of chemical space. However, challenges remain, particularly regarding the reproducibility and transferability of ML models. This review highlights the evolution of ML in learning from, complementing, or replacing traditional computational chemistry for energy and property predictions. Starting from models trained entirely on numerical data, a journey set forth toward the ideal model incorporating or learning the physical laws of quantum mechanics. This paper also reviews existing computational methods and ML models and their intertwining, outlines a roadmap for future research, and identifies areas for improvement and innovation. Ultimately, the goal is to develop AI architectures capable of predicting accurate and transferable solutions to the Schrödinger equation, thereby revolutionizing in silico experiments within chemistry and materials science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Multi-Ion Complexes and Competition from Bulky BArF – Anions for Chloride Binding in Ion Pairing Conditions

Cationic charges have long been used to enhance anion binding. Embedding charge introduces strong ion pairing for target anions but also for off-target ions, ultimately generating a mixture of multi-ion species that are hard to identify and quantify. While many sidestep this problem using polar solvents and weakly coordinating ions, these approaches exclude a substantial cross-section of conditions found in applications spanning recognition, assembly, separations, templation, and catalysis. To confront this complexity, we study the binding of an anion to a cationic receptor featuring low shape complementarity in a low-polarity solvent to maximize ionic interactions. We prepared the receptor as a salt of the weakly coordinating tetrakis­[3,5-bis­(trifluoromethyl)­phenyl]­borate (BArF – ) anion and studied the binding of small chloride (Cl – ) and medium-sized iodide (I – ) anions. Surprisingly, the use of the bulky BArF – anion does not suppress ion pairing interactions, with 65% of the receptor being paired at 0.5 mM in dichloromethane. We observe multi-ion receptor-Cl – complexes (2:1, 1:1, 1:2), reinforcing the complexity that emerges when working in low-polarity media. Here, we reveal the dependence of affinity on anion charge density and size and that bulky BArF – counteranions compete for chloride binding. These studies reveal the noninnocence of BArF – anions and strategies to quantify multi-ion species.

Ion pairing↗
NASA NTRS2019

The operational environment and rotational acceleration of asteroid (101955) Bennu from OSIRIS-REx observations

During its approach to asteroid (101955) Bennu, NASA's Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer (OSIRIS-REx) spacecraft surveyed Bennu's immediate environment, photometric properties, and rotation state. Discovery of a dusty environment, a natural satellite, or unexpected asteroid characteristics would have had consequences for the mission's safety and observation strategy. Here we show that spacecraft observations during this period were highly sensitive to satellites (sub-meter scale) but reveal none, although later navigational images indicate that further investigation is needed. We constrain average dust production in September 2018 from Bennu's surface to an upper limit of 150g s −1 averaged over 34 min. Bennu's disk-integrated photometric phase function validates measurements from the pre-encounter astronomical campaign. We demonstrate that Bennu's rotation rate is accelerating continuously at 3.63+- 0.52 x10 −6 degrees A day -2 , likely due to the Yarkovsky-O'Keefe-Radzievskii-Paddack (YORP) effect, with evolutionary implications.

Carl William Hergenrother↗
DOE OSTI2026

Adsorption of hydroxamic acid ligands for improved extraction of rare earth elements from monazite ores

Efficient separation of rare earth element (REE) ores via froth flotation requires the development of novel ligands with enhanced adsorption capacity and selectivity. To realize these advances, understanding the mechanisms underlying interactions between the ligand and mineral surfaces is essential. This study systematically evaluates the adsorption behavior of alkyl- and aromatic alkyl-substituted hydroxamic acid ligands on monazite surfaces using complementary spectroscopic techniques, including UV–visible (UV–vis) spectroscopy, Raman spectroscopy, infrared spectroscopy, and vibrational sum frequency generation (SFG) spectroscopy, together with the ab initio molecular dynamics (AIMD) simulations. Among the studied ligands, octanohydroxamic acid (OHA) and 4-ethoxy-N,2-dihydroxybenzamide (EDHBA) exhibit high adsorption capacity under basic pH (8–10) by forming multilayers on the surface. OHA has a higher equilibrium adsorption capacity compared to EDHBA, but it forms a less stable multilayer susceptible to disruption in the presence of interfering ions. AIMD results show that OHA adopts a single stable chelating geometry, while EDHBA exhibits multiple binding modes involving distinct interactions with La surface atoms and phosphate-bound oxygens, resulting in more complex adsorption kinetics. The variations in surface binding and intermolecular interactions observed between alkyl and aromatic molecules influence the differences in adsorption kinetics, equilibrium adsorption capacities on the mineral surface, and their flotation performance. This work provides valuable insight into the adsorption mechanism of ligands at mineral interfaces, which is crucial for guiding the design of new ligands with enhanced separation performance.

Zhou, Muchu [ORNL] (ORCID:0000000182650215)↗
DOE OSTI2024

Broadband and Tunable Microwave Absorption Properties from Large Magnetic Loss in Ni–Zn Ferrite

Highly effective electromagnetic (EM) wave absorber materials with strong reflection loss (RL) and a wide absorption bandwidth (EBW) in gigahertz (GHz) frequencies are crucial for advanced wireless applications and portable electronics. Traditional microwave absorbers lack magnetic loss and struggle with impedance matching, while ferrites are stable, exhibit excellent magnetic and dielectric losses, and offer better impedance matching. However, achieving the desired EBW in ferrites remains a challenge, necessitating further composition design. In this study, impedance matching is successfully enhanced and EBW in Ni–Zn ferrite is broadened by successive doping with Mn and Co , without incorporation of any polymer filler. It is found that Ni 0.4 Co 0.1 Zn 0.5 Fe 1.9 Mn 0.1 O 4 material exhibits exceptional EM wave absorption, with a maximum RL of −48.7 dB. It also featured a significant EBW of 10.8 GHz, maintaining a 90% absorption rate (RL < −10 dB) for a thickness of 4.5 mm. These outstanding properties result from substantial magnetic losses and favorable impedance matching. These findings represent a significant step forward in the development of microwave absorber materials, addressing EM wave pollution concerns within GHz frequencies, including the frequency band used in popular 5G technology.

36 MATERIALS SCIENCE↗