A gated integrating laser-combined scanning tunneling microscope has been developed for high-fidelity investigation of photophysical processes at the atomic scale. This instrument integrates a low-repetition-rate, high-pulse-energy laser with a synchronized gated-integration scheme, enabling selective extraction of the laser-induced tunneling current. To demonstrate its performance, atomically resolved topography and surface photovoltage mapping were simultaneously obtained on the Si(111)-(7 × 7) surface. The surface photovoltage distribution is found to be strongly correlated with the underlying atomic structure. In addition, a highly localized enhancement of the laser-induced tunneling current is observed at a specific single-atom defect site. Detailed analysis, supported by local density of states measurements, reveals that this defect possesses an unusually high density of deep valence-band states. This distinctive electronic structure likely promotes Auger recombination between photogenerated holes accumulated under positive sample bias and electrons tunneling from the tip, thereby giving rise to the observed increase in the local tunneling current.
Mimicking the sophisticated oxidative machinery of natural monooxygenases for high-performance biosensing remains a grand challenge, primarily due to the elusive control over positive charge carriers (holes) required for efficient signal amplification. Here, we report an atomically precise Fe-Cu heteronuclear diatomic catalyst (Fe-Cu-HDC) that unlocks unprecedented analytical sensitivity through a novel asymmetric hole-confinement mechanism. Unlike traditional single-atom catalysts where charge carriers are delocalized, the Fe-Cu interface acts as a decisive "hole trap" spatially concentrating reactive charge carriers at the active center. This localized accumulation triggers the formation of potent high-valent iron species and facilitates barrierless oxygen activation, providing the rapid mineralization of >80% tetracycline within 80 min with a superior reaction rate (Vmax = 0.27 mM min-1). Leveraging this hole-driven enzymatic proficiency, we engineered an integrated 3D-printed platform comprising a continuous-flow filtration reactor and a smartphone-based colorimetric sensor array. This portable device enables the simultaneous rapid mineralization and fingerprint-like discrimination of tetracycline antibiotics in complex real-world matrices (raw milk and livestock wastewater) with a detection limit as low as 30 nM. The platform maintains >90% activity after 18 d of storage and demonstrates laboratory-grade accuracy in raw milk and livestock wastewater. Our findings not only demystify the electronic origin of bio-inspired oxidation but also establish hole-carrier engineering as a transformative dimension for designing the next generation of intelligent, cofactor-free biosensors for on-site diagnostics and environmental surveillance.
Self-assembly, a key approach in material science, enables modulation of nanostructures to achieve distinct materials properties. Atomically precise metal nanoclusters (NCs), consisting of a few metal atoms, exhibit distinctive optical and electronic properties due to their "molecule-like" discrete energy levels. Such NCs offer advantages over conventional metal nanoparticles by avoiding dispersity in size and uncontrolled aggregation. Here we demonstrate a study on crystalline aggregates of Au6 NCs, formed under varying conditions. Notably, the controlled aggregation of these Au6 NCs, synchronising by protonation or employing specific hydrogen bonding, yields self-assembled nanoribbons and percolated networks of nanofibers that further produce extended 3D fibrillar architectures. X-ray scattering and electron microscopy reveal two distinct packing modes: a monoclinic 2D oblique lattice with sparse NC arrangement, and a nematic 2D hexagonal packing, resembling liquid-crystalline rod-like assemblies. The resulting superstructures exhibit enhanced optical responses, retaining the photoluminescence of their constituents, and manifesting third-harmonic generation, slow photoluminescence decay driven by charge-migration effects, and polarization effects influenced by the ordered structure with the periodicity of the NCs. Overall, this work emphasizes the potential of NCs as versatile building blocks for tunable and responsive optoelectronic materials, providing insights into the mechanisms of self-assembly.
We present an all-atom model mimicking superparamagnetic iron oxide nanoparticles functionalized by alkyl phosphonic acids and demonstrate the prediction of grafting density, X-ray diffraction profiles, and solvent-dependent particle radii. The inherent complexity of this nanosystem calls for careful model preparation to avoid bias from human intuition. We suggest a cascade of simulated annealing steps for (i) providing reasonable starting points for the iron oxide particle and (ii) grafting by self-assembled monolayers. The latter was performed as a function of the number of phosphonic acid molecules deposited, thus offering an unbiased assessment of the grafting density and structural alignment of the tail groups that define the outer shell of the nanoparticle. The overall protocol is widely transferable and implies moderate computational costs as compared to the explicit modeling of phosphonic acid association from solution. In turn, solvent effects on the surface structure of the nanoparticle model initially prepared in the gas phase were considered using hexane, propanol, and water, respectively. Voronoi analyses clearly demonstrated the solvent-dependent bundling of the terminal alkyl groups of the phosphonic acids grafted onto iron oxide nanoparticles. To this end, the nanoparticle-solvent interface gives rise to nanometer-scale patterns of differently oriented monolayer structures.
Precisely introducing single-atom sites into metal oxide semiconductors (MOS) is essential for achieving ultrasensitive and selective detection of trace gases; however, the structure-dependent role of these atomically dispersed sites remains insufficiently understood. Here, we report a defect-assisted strategy to construct Ni-modified SnO2 with tunable surface Ni dispersion, enabling a direct correlation between Ni coordination structure and NO2 sensing behavior. Hydrogen treatment of SnO2 (H-SnO2) produces abundant surface defects that stabilize isolated Ni atoms through Ni-O-Sn coordination. Aberration-corrected scanning transmission electron microscopy and X-ray absorption spectroscopy unambiguously confirm the formation of atomically dispersed Ni sites and their aggregation into NiOx clusters at higher loading. Among them, the single-atom-dominated Ni/H-SnO2 sensor exhibits an ultrahigh response of 13,152 toward 1 ppm NO2 at 175 °C, together with excellent selectivity, good long-term stability, and a detection limit down to 10 ppb. Experimental results combined with density functional theory calculations reveal that the superior sensing performance originates from the synergy of strong and selective NO2 adsorption and efficient charge transfer via the single-atom Ni-O-Sn bonding structure. In contrast, the formation of NiOx clusters weakens NO2 adsorption and deteriorates charge-transfer efficiency, leading to reduced sensing performance. This work identifies the single-atom Ni-O-Sn bonding as the decisive active structure for ultrasensitive NO2 detection and provides an atomic-level bonding engineering strategy for high-performance MOS-based gas sensors.
The structural prediction of metal nanoclusters is hindered by the extremely complex potential energy surface and the prohibitive cost of first-principles calculations. Here, we develop an efficient structure-prediction framework that tightly integrates machine-learning interatomic potentials with global optimization. Neural network atomic potentials are iteratively trained to achieve density-functional-theory accuracy and coupled with a genetic algorithm to enable reliable exploration of complex energy landscapes. As a stringent benchmark, the framework is applied to neutral Aun clusters (n = 30-45), where it robustly identifies low-energy structures at an affordable computational cost and reveals a non-monotonic structural evolution from hollow cage-like motifs to multi-core-cage building blocks over a critical size range. Notably, this transition exhibits pronounced differences from that of the corresponding anionic clusters, highlighting the potential of the proposed active-learning workflow as an extensible strategy for investigating metal clusters with complex electronic structures.
A heterojunction photocatalyst composed of single-atom, atomically dispersed Ni sites on g-C3N4/TiO2 was developed for sacrificial-agent-free CO2-to-CO reduction under simulated solar irradiation. The optimized catalyst, containing 0.78 wt% Ni and 46 wt% g-C3N4, delivered 70% selectivity to CO over H2 and exhibited 16-fold enhancement in activity compared with bare g-C3N4/TiO2 and Ni-single-atom catalysts supported on either g-C3N4 or TiO2 alone. High-resolution transmission electron microscopy (HRTEM) revealed intimate interfacial coupling within the g-C3N4/TiO2 heterojunction, while atomically dispersed Ni species were predominantly anchored on g-C3N4 nanosheets coating the TiO2 surface. X-ray photoelectron spectroscopy revealed pronounced interfacial electronic redistribution following heterojunction formation and Ni incorporation, indicating strong electronic communication between the semiconductor components. Electrochemical impedance spectroscopy (EIS) and steady-state photoluminescence measurements showed significantly suppressed charge recombination, whereas transient absorption spectroscopy revealed that isolated Ni sites act as efficient electron traps, extracting photogenerated electrons and directing them toward catalytic reduction centers. Combined with the comparative photocatalytic performance of individual components, these findings identify the Ni-Nx moieties on g-C3N4 as active sites for CO2-to-CO conversion and support the S-scheme charge-transfer pathway, in which TiO2 preferentially consumes holes while highly reducing electrons accumulate on the g-C3N4-supported Ni single-atom sites to drive selective CO2 reduction in water.
Colloidal nanocrystals are generally regarded as rigid solid entities, rarely exhibiting the structural adaptability observed in molecular cages, such as fullerenes, which can undergo carbon framework reduction and encapsulate guest cations without structural reorganization. Here, by creating two enantiomeric pairs of high-nuclearity copper sulfide nanoclusters with a mixed-valence Cu(II)/Cu(I) configuration, we endow these nanoscale assemblies with an intrinsic capacity for electron uptake under mild reducing conditions. The resulting charge imbalance provides an effective thermodynamic driving force that realizes a positively charged metal ion migrating inward through multiple atomic layers and occupying the cluster core. This system thus represents a rare example of a nanocluster platform that simultaneously combines reduction tolerance and structural robustness, preserving its atomic framework despite the incorporation of a single atom effectively modifying the electronic structure, particularly the local chirality. In situ absorption and circular dichroism spectroscopies establish that the transformation proceeds through a continuous, single-particle process rather than a fragmentation-reconstruction pathway, while ex situ pair distribution function analysis resolves key local steps in the structural evolution, offering mechanistic insights into this unique migration behavior.
Bottom-up micro/nanofabrication complements photolithography in multilayer, 3D, and cost-effective manufacturing, but lacks resist patterning technology with photoresist-level reproducibility, processability, and universality. Here, we explore a surface-selective nucleation (SSN) effect to derive polymeric resist patterns with nanoscale resolution, inherent 3D compatibility, low defect density, clean lift-off, and broad applicability across fabrication platforms. The SSN phenomenon is achieved through solution-phase polymerization of dual-ended acrylic monomers on prepatterned substrates and surface-mediated creation of area-dependent nucleation barriers using adsorption inhibitors and chain terminators, which synergistically modulate surface and bulk free energy of nucleation, respectively. The resulting resist forms a coherent resin film physically adhered to the substrate, while featuring tunable thickness (13-150 nm) and minimal surface roughness (0.91 nm). This method delivers 15 nm linewidth patterning with 99.97% coverage across wafer-scale arrays within 10 s and demonstrates high compatibility with mainstream thin-film deposition techniques (e.g., e-beam evaporation, sputtering, and atomic layer deposition).
Pristine zinc-based layered double hydroxides (LDHs) possess remarkable antibacterial properties. The antibacterial activity of zinc-based LDHs could be explained by three possible mechanisms: (1) direct contact interactions between the LDH and bacterial surfaces, (2) release of antibacterial Zn2+ aq ions, and (3) generation of reactive oxygen species (ROS) by LDHs in response to irradiation by a suitable light source. In this work, the potential contribution of ROS generation in the antibacterial activity of ZnAl LDH nanoparticles (NPs) was determined by comparing their effect against Gram-positive Staphylococcus aureus bacteria in the presence and absence of UVA irradiation (λ = 365 nm, irradiation period = 4 h). The bactericidal efficacy of ZnAl LDH NPs was significantly enhanced in the presence of UVA light. The bactericidal activity was hindered in the presence of histidine acting as a ROS scavenger and giving indirect evidence of the role of ROS. Moreover, Fourier-transform infrared spectroscopy revealed denaturation and suppression of several structural components in S. aureus cells exposed to ZnAl LDH NPs under dark conditions and in the presence of UVA radiation, with more pronounced alterations for the latter. The impacts of such alterations on the topographical properties of S. aureus cells were determined by atomic force microscopy imaging. Treated cells with ZnAl LDH NPs were completely deformed and exhibited increased roughness, especially upon treatment in UVA conditions. All these results suggest the presence of a dual antibacterial effect between ZnAl LDH NPs and their generated ROS to provide amplified antibacterial activity.
Solid-binding peptides (SBPs) are versatile molecules that can control a range of atomic-scale interfacial processes, but they remain challenging to discover. Current approaches for discovery rely on directed evolution, which samples only a small fraction of possible sequences. Data-driven methods for therapeutic peptides are also not applicable as they rely on crystal structures whereas peptides adopt varied conformations at solid surfaces. To address this challenge, we recently combined biophysical modeling and machine learning to design plastic-binding peptides that were predicted to have strong adsorption enthalpies. Here, we evaluate these designs using steered molecular dynamics and single-molecule force measurements and identify de novo designed peptides that bind strongly to polyethylene. Experimental adhesion forces exceed those previously reported for SBPs, and adsorption free energies from metadynamics simulations support strong binding. Analysis of the designed peptides reveals blocks of non-polar and charged residues, which enables them to adopt conformations that segregate non-polar amino acids to the plastic surfaces (generating hydrophobic interactions) and charged amino acids away from the surfaces. The contact patterns within the non-polar blocks depend on sequence context and polyolefin type. Overall, we validate a general approach for de novo SBP discovery that has broad scientific and engineering applications.
Recently, photon-counting computed tomography (PC-CT) devices have become clinically available for X-ray diagnosis, and developments of analysis algorithms to generate various quantitative images have focused attention. This study proposes an algorithm to calculate the effective physical density (ρeff) of biological objects having an effective atomic number (Zeff) of 3-20. In our procedure, ρeff was determined when fitting the interaction cross sections (σs) to the measured linear attenuation coefficients (μs), which were determined from virtual monochromatic images (VMIs). In this process, the Zeff was analyzed in advance, and this information was fed back to the ρeff analysis. A key feature of our procedure is that it does not require calibration processes based on specific substances, which allow us to analyze any substance without making assumptions. To validate the availability of the proposed algorithm, we conducted an experiment using a clinical PC-CT scanner. A multi-energy CT phantom, a water phantom, an in-house low-density phantom, food samples, and a chest phantom were scanned. The results showed that our procedure can calculate ρeff of water with an uncertainty of 4.5%. The academic significance of the present research results lies in demonstrating that the factors contributing to contrast, previously obtained from CT values, can be physically interpreted using information from Zeff and ρeff. This analysis cannot be performed with conventional single-energy CT scanners and is possible with PC-CT and dual-energy CT scanners. Our novel procedure is expected to provide useful additional information in X-ray diagnosis.
The early hydration of calcium silicate hydrate (C-S-H) plays a crucial role in the development of key mechanical properties in cement, yet an atomic-level description of this reaction remains elusive. Here, to understand the early stages of the hydration reaction, we introduce a method to quantify dilute silicate species as a function of reaction time using ex-situ solid-state 29Si magic-angle spinning dynamic nuclear polarization (DNP) nuclear magnetic resonance (NMR) spectroscopy. Samples are flash-frozen and separated by centrifugation, allowing for kinetic analysis of the supernatant and structural studies of the precipitate over time. With DNP-enhanced 29Si NMR, we can determine the concentrations of various silicate species throughout the reaction and track the growth of the silicate chains, which form the dreierketten backbone of C-S-H. In our low Ca/Si ratio system, we observe a vast majority of the supernatant silicate species to be monomers, with small amounts of dimers. The initially precipitated C-S-H, which has a mean chain length of 2.6 and is composed primarily of dimers, is shown to significantly differ from the C-S-H present after 3 h of hydration, which has an average length of 4.2.
The application of cosmetic ingredients into hair formulations relies on their extensive characterization and on understanding their mechanisms of action. Specifically, in the case of hair conditioning agents, their efficiency in treating hair must be proved before testing them on real complex formulations. In this work, we investigate the deposition of three cationic polymers onto model surfaces that mimic the negative surface potential of highly damaged hair. Two CHPTAC-cationized lignins (CL0.34 and CL0.61) were evaluated and compared with a commercial polyquaternium (PQ11). The two selected lignin derivatives exhibited different degrees of cationic substitution (DS) and ζ-potential (CL0.34: DS = 0.34 ± 0.01 and ζ-potential = 12.8 ± 0.4 mV; CL0.61: DS = 0.61 ± 0.03 and ζ-potential = 18.8 ± 0.3 mV). Atomic force microscopy (AFM) and quartz crystal microbalance with dissipation monitoring (QCM-D) were used to evaluate the adsorbed layers formed by the polymers and their mechanical properties. Among the tested lignin conditioning agents, CL0.61 exhibited conditioning behavior, forming layers whose properties closely resembled those of the benchmark polymer PQ11. CL0.61 and PQ11 were both efficient at reducing the frizz effect on real bleached hair, effectively overcompensating the hair surface potential, which shifted from negative to positive values, confirming their effective adsorption after conditioning and rinsing. By combining advanced interfacial characterization with structure-property-function relationships, this work provides fundamental insights into polymer adsorption and performance at biointerfaces, supporting the rational design of functional materials and highlighting the potential of cationic lignin derivatives as viable, biobased conditioning agents for future hair-care formulations.
This investigation engineers multifunctional polydimethylsiloxane (PDMS) composites incorporating 0-50 wt% silica ash a valorized industrial byproduct as lightweight, sustainable gamma-ray shielding elastomers. Narrow-beam attenuation experiments spanning diagnostic-to-isotope energies (59.5-1332.5 keV) quantify a monotonic enhancement in linear attenuation coefficients (µ), escalating from 0.3011 cm⁻¹ (pure PDMS) to 0.3651 cm⁻¹ (50 wt% ash) at 59.5 keV, with concomitant reductions in half-value layer (HVL) from 2.30 cm to 1.90 cm. This stems from a paradigm shift in photon interaction physics: photoelectric dominance (< 100 keV) amplifies via elevated effective atomic number (Zeff), transitioning to density-mediated Compton scattering (≥ 661.66 keV), validated by < 3.76% deviation from NIST XCOM photon cross-sections. Lead-equivalence analysis reveals the 50 wt% composite demands merely 10-14× lead thickness in the Compton regime, underscoring superior mass efficiency. Hierarchical microstructural analysis (SEM, EDX, XRF) elucidate homogeneous nanofiller dispersion and robust siloxane-filler interfacial coupling, driving progressive stiffening (Young's modulus: 0.026 to 0.157 MPa at 40 wt%). Optimal mechano-elastic performance manifests at 15 wt% (tensile strength: 0.357 MPa; toughness: 0.591 MJ·m⁻³), beyond which agglomeration induces embrittlement. Thermogravimetric profiles reveal an initial stabilization peak at 10 wt% ash, followed by catalytic depolymerization at higher loadings, rationalized by Lewis acid-base interactions accelerating Si-O bond scission despite augmented char residue. These composites (optimized at 10-20 wt%) exhibit enhanced radiation attenuation together with improved mechanical resilience and elastomeric flexibility, demonstrating their potential for flexible radiation shielding applications.
This study presents a novel approach for fabricating photoelectrochemically homogeneous photocathodes composed of nickel oxide nanocrystals (NiO NCs) using supercritical hydrothermal synthesis and push-coating (PC) methods. NiO NCs were synthesized in supercritical water using oleic acid (OA) as a surface modifier. The NiO NCs exhibited high crystallinity, small particle size, and narrow size distribution. Compared with the Langmuir-Schaefer method, the PC method provided NiO-NC films with relatively low roughness and high photoelectrochemical performance. In the PC method, NiO-NC films with thicknesses of ∼100-500 nm were obtained by varying the NiO-NC and OA concentrations in the dispersions. The NiO-NC films can be regarded as photoelectrochemically homogeneous photocathodes, as their impedances are proportional to their thicknesses. This homogeneity, in turn, increases the design freedom of NiO photocathodes. In addition, atomic layer deposition allowed the filling of interparticle voids with NiO, improving the hole migration capability of the NiO-NC films. These findings demonstrate the potential of combining supercritical synthesis and PC methods as a green and economically advantageous process for the high-throughput manufacturing of NiO photocathodes, minimizing material loss and limiting the use of hazardous solvents.
Hypertrophic cardiomyopathy (HCM) variants in genes encoding the myosin heavy chain (MHC) (MYH7), myosin light chains (MYL2 and MYL3), and cardiac myosin binding protein-C (cMyBP-C, MYBPC3) lead to cardiac hypertrophy, with abnormal contractility, relaxation, and energy consumption. Here, we defined the structural consequences of pathogenic and benign missense variants in these genes by mapping 233 variants (MYH7, n = 175; MYBPC3, n = 41; MYL2, n = 12; MYL3, n = 5) onto a cryo-EM-based atomic model of the human cardiac thick filament. We identified HCM variants residing in 30 molecular interfaces of the complex thick filament interactome, including the two main interfaces of the myosin interacting-heads motif (IHM), and interfaces involving the MHC, essential and regulatory light chains, and cMyBP-C. None of the 21 variants classified as benign were within interfaces. We demonstrated earlier disease onset and adverse outcomes in HCM patients with pathogenic variants within vs. outside of molecular interfaces, emphasizing their importance in normal thick filament function and improving risk stratification of patients.
The unique qualities of carbon dots (CDs) have made them appealing for applications like bioimaging, ion sensors, anticounterfeiting, and many more. The heteroatom doping strategy is one of the best techniques used to improve the optical properties of carbon dots and overcome their low quantum yield percentage. Boron-doped carbon atoms enhance the fluorescence intensity of CDs and raise the quantum yield (QY) due to the unique characteristic of boron, which has the same atomic radius as carbon and structural properties. Codoping boron with other elements has been shown in recent research to have synergistic effects that improve optical qualities compared to single-doped CDs. This paper not only highlights the synthesis, structure, and applications of boron-doped CDs but also emphasizes computational approaches to determine the properties and applications of these materials. The electronic properties and application possibilities of boron-doped carbon nanostructures were partly estimated by mathematical calculations. Density functional theory (DFT) and time-dependent DFT (TD-DFT) are two computational techniques widely used in investigating the structure-activity relationships of boron-doped CDs and predicting their electronic and optical properties. Furthermore, the role of boron attribution plays very well in improving the performance of carbon-based materials for energy storage and electrocatalysis.
Integrating self-assembled colloidal nanocrystals with uniform orientation into optoelectronic devices may allow for the significant improvement of charge transport processes. In this work, for this purpose, using the liquid-air interface self-assembly technique and selectively controlling the orientation of CdSe nanoplatelets (NPLs) with short 2-ethylhexane-1-thiol (EHT) ligands in a vertical-configuration photodetector device, we show that the photoconductivity response is substantially improved by the selective arrangement of CdSe NPLs into two distinct assemblies of edge-up (EO) and face-down (FO) orientations compared to the randomly oriented (RO) NPL film deposited by spin-coating. Our devices reveal that EO nanoplatelets significantly enhance response speed, while RO yields higher photocurrent, responsivity and detectivity. The assembled devices, consisting of one-monolayer EO and three-monolayer FO NPL films of comparable vertical film thickness, demonstrate superior photocurrent responses of 8 ms/11.3, 13 ms/4.5, and 15.2 ms for the rise/decay time constants, respectively, compared to 17 ms/18, and 80 ms for the RO for the rise/decay time constants. Despite using only a monolayer of EO NPLs, we achieved a responsivity of 21.04 mAW-1 and a detectivity of 5.77 × 1010 Jones, compared with the best results from CdSe-based photodetectors reported in the literature. This work provides critical insight for charge transportation management in solution-processed photodetection devices by adjusting the orientation of the two-dimensional quantum structures, paving the way toward fast and atomically thin functional optoelectronic devices. This also demonstrates that facet-specific metal-semiconductor interfaces are another critical factor, in addition to the charge transportation pathway, which can modulate the interfacial electronic structure and recombination dynamics in vertical configuration photodetectors.
Toxic trace metals such as lead (Pb), cadmium (Cd), and arsenic (As) represent persistent environmental contaminants associated with significant human health risks. Reliable and rapid analytical strategies are therefore essential for toxicological surveillance of consumer and environmental matrices. In this study, a green and process-intensified ultrasonic extraction method was developed for the efficient recovery and determination of Pb, Cd, and As from complex matrices including herbal materials, cosmetic products, beverages, and wastewater, using Atomic Absorption Spectrometry. The approach utilizes ultrasonic cavitation to accelerate metal desorption and mass transfer, enabling rapid extraction under mild conditions with reduced reagent consumption. Galangal was selected as a representative plant matrix to establish and validate the analytical framework. A rotatable central composite design based on response surface methodology was applied to evaluate the influence of nitric acid concentration (0.40-1.20 M), ultrasonic time (5-15 min), and acid volume (20-40 mL) on metal recovery. The statistical model demonstrated strong predictive capability and identified acid concentration and solvent volume as significant factors influencing extraction performance (p < 0.05). Ultrasonic irradiation significantly enhanced metal release from the matrix through cavitation-induced disruption and accelerated diffusion processes. The optimized extraction conditions (0.68 M HNO3, 11 min ultrasonic time, and 32 mL acid volume) yielded predicted recoveries of 97.13%, 102.09%, and 103.26% for Pb, Cd, and As, respectively, with corresponding experimental recoveries of 95.17 ± 2.37%, 97.50 ± 5.13%, and 98.63 ± 0.25%. The developed method showed a very low matrix effect. The relative expanded uncertainty of metal extraction under optimized conditions ranged from 5.60 to 10.36%, which is within the acceptable criteria (≤15%). Based on the evaluation of trueness through comparison with results obtained from homogeneous proficiency testing (PT) materials, the developed method exhibited acceptable trueness for the quantitative determination of all trace metals, with z-scores less than 2. Application of the method to real samples demonstrated consistent analytical performance across seven galangal varieties and multiple complex matrices, with recoveries ranging from 87.00 to 109.00% (% RSD = 0.08-6.82). These findings demonstrate that ultrasonic processing can provide a rapid, low-reagent, and environmentally responsible extraction strategy for toxic trace metal determination. The developed protocol offers a practical analytical platform for toxicological monitoring, contaminant surveillance, and safety assessment of natural and industrial products.