Bromine and iodine radicals oxidize gaseous mercury, influencing its lifetime and deposition. Using CCSD(T) and CASPT2 calculations combined with variational transition-state theory, we compare the thermochemistry and kinetics of key reactions forming and destroying Hg-halide species. We investigate the atmospheric oxidation of mercury Hg(0) by Br and I to yield the corresponding Hg(I) halides and the subsequent oxidation reactions yielding Hg(II) compounds (or Hg(0)) via I, Br, BrO, ClO, IO, NO2, and HO2. The rate coefficient for ·HgI + I· → HgI2 (4.2 × 10-13 cm3 molecule-1 s-1) is about half that for the bromine analogue, and ·HgI + IO· → IHgOI is roughly seven times slower than ·HgBr + BrO· → BrHgOBr. The combined electronic-structure and kinetic analysis demonstrates that the employed methods reproduce periodic halogen trends within chemical accuracy, supporting the conclusion that bromine remains the dominant oxidant of atmospheric mercury under current conditions.

ABSTRACT Intermittent demand is common in practice. Inventory managers expect to know the future demand of each period over a long horizon for inventory control. Most existing studies on forecasting intermittent demand can only forecast one future period. Though the multi-period demands can be forecasted by some existing estimators, of which the trend coefficients are static, which may not align with the trend of future periods. In this paper, a multi-period forecasting method based on non-overlapping temporal aggregation is proposed. Firstly, the framework of the proposed method can forecast the future demand of each period over a long forecasting horizon by the patterns of non-overlapping aggregated time series with different aggregation level. Secondly, three principles are extracted, and then three strategies are proposed based on the principles. The three strategies, abridging or extending the original time series, can cope with the circumstance that the quantity of original historical periods cannot be divided by the aggregation level. Thirdly, four properties of the proposed method are discussed and illustrated in theory. Then, seven basic estimators and two accuracy measurement methods are introduced. The results of numerical and empirical investigations illustrate that the method is practical and efficient.

Background: Dementia is an increasing public health challenge in Mexico, yet recent national data on mortality patterns remain limited. This study examines temporal trends in dementia-related mortality and its sociodemographic and ecological characteristics among adults aged ≥65 years from 2017 to 2023. Methods: National mortality records from the General Directorate of Health Information were analyzed. Annual dementia-related mortality rates were calculated based on mid-year population estimates from CONAPO. Trends were assessed with regression analysis, including population offsets, and individual- and state-level characteristics were evaluated. Results: Between 2017 and 2023, dementia-related deaths increased from 761 to 1425, corresponding to an observed rise from 7.9 to 14.6 deaths per 100,000 inhabitants aged ≥65 years. Period trend indicated an average annual expected increase of 18.6% in dementia related mortality. A transient decline occurred in 2020–2021, coinciding with the COVID-19 pandemic. At the individual level, higher education was associated with greater odds of dementia certification, whereas Indigenous ethnicity appeared protective, which may reflect patterns consistent with diagnostic and reporting disparities. Higher state-level life expectancy correlated with higher dementia mortality, while greater population aging was inversely associated. Conclusions: Dementia-related mortality in Mexico shows a sustained upward trend with regional heterogeneity and apparent inequities in diagnosis and reporting. Strengthening mortality surveillance, improving certification quality, and integrating dementia indicators into national non-communicable disease registries are essential to guide equitable policy responses.

This systematic computational study investigates carbodiphosphorane ligated E(II) (CDPE, E = Si, Ge, Sn, Pb) catalyzed hydrodefluorination (HDF) and C-C coupling reactions involving E(II)/E(IV) redox cycle. While CDPSn is known to catalyze HDF of pentafluoropyridine through sequential C-F oxidative addition (OA), F-H ligand metathesis (LM), and C-H reductive elimination (RE) steps, our density functional theory (DFT) calculations reveal distinct reactivity across the group. CDPSi undergoes C-F OA reaction but fails to proceed further, whereas CDPGe and CDPPb successfully complete the full catalytic cycle. Mechanistic analysis reveals that OA energy barriers are correlated with the nucleophilicity of the catalyst, LM energy barriers are primarily influenced by E-F bond strength, and RE energy barriers vary depending on the specific reaction pathway rather than following clear periodic trends. Although C-C coupling remains thermodynamically disfavored under standard conditions, the relevant energy substantially reduced through electronic tuning via electron-withdrawing substituents on the aryl ring. These findings provide a rational framework for designing main group catalysts, thereby advancing the field of main group catalysis.

Environmental element monitoring is essential for assessing environmental quality, identifying pollution sources, evaluating ecological risks, and understanding long-term contamination trends. Modern monitoring campaigns routinely generate large volumes of complex data that require advanced analytical strategies. This study applied chemometric techniques to analyze elements and BVOCs (biogenic volatile organic compounds) measured from Posidonia oceanica and related environmental matrices (seawater, sediment, and rhizomes) during three sampling campaigns in the Tremiti Islands (Italy). Twenty-two trace elements were quantified, and BVOC profiles were obtained from the leaf samples. The dataset was analyzed using a combination of univariate visualizations, unsupervised and supervised multivariate techniques, and multi-way methods. PCA (Principal Component Analysis) and PLS-DA (Partial Least Squares-Discriminant Analysis) revealed distinct spatial (leaf section) and temporal (sampling period) trends, supported by consistent elemental markers. A low-level data fusion approach integrating BVOC and element data improved group discrimination and interpretability. PARAFAC (PARAllel FACtor analysis) applied to a three-way array successfully separated background trends from meaningful compositional changes, uncovering latent structures across chemical, spatial, and temporal dimensions. This work illustrates the usefulness of chemometrics in environmental monitoring and the effectiveness of combining multivariate tools and data fusion to improve the interpretability of complex environmental datasets. The methodology used in this study is fully generalizable and applicable to other environmental multi-way datasets.

Trends in opioid use among adults with cardiovascular disease, 2001 - March 2020.

A comparative analysis of methods for evaluating an integral indicator of population health, based on the summation of weighted arithmetic group averages, has shown that their advantage lies in the use of weighting coefficients, which improve the accuracy of the integral assessment. However, their disadvantage is the quality of expert assessments of the weighting coefficients, which depend on the segment selection and the number of experts, which requires their further improvement. The goal of the work is to develop a comprehensive integral indicator to assess the state of population health for the purpose of prompt situation assessment and decision-making. Methods Used: Modeling of the integral indicator of population health, based on the theory of mathematical statistics, systems of linear algebraic equations, and regression-correlation analysis. Novelty: The developed model of the integral indicator of population health, in the form of a function of individual statistical health indicators over time, allows for comparison and analysis of population health in spatial and temporal aspects. Results: The use of the presented methodological approach for creating a research base and developing an algorithm for calculating the integral indicator using regression-correlation analysis, the range amplitude of statistical indicators, situation analysis methods, event theory, and averages, allows for the assessment of the medical-demographic state both at the current moment and based on trend assessments using linear trends in the forecast period.

Abstract Tailoring the coordination sphere of the metal atoms represents a highly promising strategy to modulate Fe single‐atom catalysts. However, modifications in the first coordination shell often led to reduced catalyst stability, while those in the second shell exhibit limited efficacy in enhancing catalytic activity. In this work, we introduce N‐group elements to engineer N‐X VA dipoles, leveraging their characteristic “high density near the source but sparse at a distance” electric field to modulate the 3d orbitals of Fe. The introduction of N‐X VA dipoles enhances the polarization of Fe single atoms, especially, with the increase of the periods, Fe 3d orbitals rearrangement occurs, resulting in an optimized binding energy for OH* intermediates that approaches the peak of the volcano plot. The resulting FeN4‐Sb/C catalyst exhibits a high half‐wave potential of 0.833 V and a degradation of only 18 mV after 30,000 cycles accelerated durability testing, superior to commercial Pt/C. Furthermore, PEMFCs assembled with the FeN4‐Sb/C catalyst deliver impressive performance (H 2 –O 2 : 1.1 W cm −2 ; H 2 ‐air: 0.6 W cm −2 ), outperforming nearly all recently reported single‐atom and dual‐atom catalysts. This work not only reveals the periodic trend of dipole‐modulated ORR activity in Fe single atom catalysts, but also demonstrates its potential for application in PEMFCs.

Tailoring the coordination sphere of the metal atoms represents a highly promising strategy to modulate Fe single-atom catalysts. However, modifications in the first coordination shell often led to reduced catalyst stability, while those in the second shell exhibit limited efficacy in enhancing catalytic activity. In this work, we introduce N-group elements to engineer N-XVA dipoles, leveraging their characteristic "high density near the source but sparse at a distance" electric field to modulate the 3d orbitals of Fe. The introduction of N-XVA dipoles enhances the polarization of Fe single atoms, especially, with the increase of the periods, Fe 3d orbitals rearrangement occurs, resulting in an optimized binding energy for OH* intermediates that approaches the peak of the volcano plot. The resulting FeN4-Sb/C catalyst exhibits a high half-wave potential of 0.833V and a degradation of only 18mV after 30,000 cycles accelerated durability testing, superior to commercial Pt/C. Furthermore, PEMFCs assembled with the FeN4-Sb/C catalyst deliver impressive performance (H2-O2: 1.1W cm-2; H2-air: 0.6W cm-2), outperforming nearly all recently reported single-atom and dual-atom catalysts. This work not only reveals the periodic trend of dipole-modulated ORR activity in Fe single atom catalysts, but also demonstrates its potential for application in PEMFCs.

Abstract. Tropospheric ozone trends are important indicators of climate forcing and surface pollution, yet relevant satellite observations are too uncertain for assessments. The assessment project TOAR-II has used multi-instrument, ground-based data for global trends over 2000–2022 (Van Malderen et al., 2025a, b). For the tropics, trends are derived from SHADOZ ozonesonde profiles (Thompson et al., 2021, “T21”; Stauffer et al., 2024) or combinations of satellite, SHADOZ and IAGOS aircraft measurements (Gaudel et al., 2024). We extend T21 that covered 1998–2019, analyzing SHADOZ data at five sites with a Multiple Linear Regression (MLR) model for 1998–2023 and reporting trends for two free-tropospheric (FT) segments, the lowermost stratosphere and the total tropospheric column (TrCOsonde). Trends for the Aura period, 2005–2023, are computed from OMI/MLS TrCOsatellite. We find the following: Extending SHADOZ analyses 4 years shows little change from T21; TrCOsonde trends are small (0.5–1 DU/decade) except over SE Asia. Annual trends for TrCOsonde and OMI/MLS TrCOsatellite agree within uncertainties at four of five sites, with the largest differences at Samoa. Sensitivity tests show the following: (a) Adding thousands of FT IAGOS profiles to SHADOZ yields little change in trends; SHADOZ sampling is sufficient. (b) Quantile Regression (QR) and MLR median trends are both near zero, but QR captures extremes (5th percentile, 95th percentile) with changes up to ±1 DU/decade (p< 0.10). (c) Twelve-year analyses for trends lead to uncertainty changes too large for an assessment. This study and Van Malderen et al. (2025a, b) provide the most reliable TOAR-II trends to date: over the past ∼ 25 years, tropical FT ozone changes have been modest, ∼ (−3–+3) %/decade, except over SE Asia.

In molecular dynamics, conventional atomistic models of metals fail to respond to ionic environments, whereas quantum calculations are accurate but computationally expensive. Here, a simple yet accurate two-point all-atom polarisable model of silver is developed capable of instantaneous induced-charge effects. This model contains a positive silver atom, and a negative virtual site attached to the core via spring, allowing rotation and harmonic motion. The site represents the electron cloud around the metal atoms and responds to the charges in strong coherence with the classical image potential. The energy equation of the model encompasses two non-bonded and one bonded contributions. The parameters developed are not merely empirical fitting but follow the periodic trend. The model was tested to reproduce lattice parameters, density, surface energy, water interfacial energy and mechanical properties in consistency with the experimental results. Further, nanoindentation was performed on [100], [110] and [111] surfaces, producing results complying with Hertz theory. To examine its response to organic compounds, benzene was adsorbed onto three facets; computed adsorption and coverage exploration were in excellent agreement with the experiments. Robust ready-to-use model (consistent with PCFF and CVFF) is useful for interfacial studies. Besides, a comprehensive summary of earlier models of metals is also reported.

BackgroundPrimary care diabetes management lacks objective, scalable methods for continuous physical activity surveillance. Bioelectrical impedance analysis (BIA), routinely collected in diabetes care, offers untapped potential as an automated digital biomarker but requires validation for behavioral phenotyping.ObjectiveThis study aims to evaluate the feasibility and predictive validity of multifrequency bioimpedance for physical activity detection and its association with glycemic control in type 2 diabetes.MethodsThis was a pragmatic quasi-experimental study using temporal allocation across three 4-month periods (January 2021-July 2023) in a Japanese primary care clinic, including comprehensive tracking with BIA-guided counseling (n=65), partial tracking (n=31), and standard care (n=100). Adults with type 2 diabetes (hemoglobin A1c [HbA1c] 7.0%‐10.0%) underwent monthly segmental multifrequency BIA. The primary outcome was HbA1c <7% at 4 months. Intervention-outcome associations were examined using chi-square trend tests and multivariable logistic regression adjusted for baseline HbA1c, the Walk Score (0‐100), and medication indicators. To assess temporal confounding, we conducted ANCOVA on 4-month HbA1c with baseline adjustment (age and BMI added in sensitivity analyses). Effect modification by built environment was tested via Walk Score×Intervention interaction. Predictive validity of left-arm 50-kHz reactance was assessed using area under receiver operating characteristic curve with 95% CI via 10-fold cross-validation.ResultsAmong 196 participants, the baseline characteristics (age, BMI, HbA1c, diabetes duration, and medications) did not differ across periods (all P>.05). HbA1c <7% achievement showed a gradient: 80% (52/65) comprehensive, 58% (18/31) partial, and 56% (56/100) standard care (χ²4 for trend=14.23; P<.001). ANCOVA of 4-month HbA1c (baseline-adjusted) showed no linear period trend (P=.25). A significant Walk Score×Intervention interaction was observed (β per 10-point Walk Score=−.55; 95% CI −1.03 to −0.06; P=.028), indicating differential effectiveness by neighborhood walkability. Left-arm 50-kHz reactance predicted target achievement (adjusted odds ratio per 1-SD increase =3.04; 95% CI 1.86‐4.97; P<.001; area under receiver operating characteristic curve=0.847, 95% CI 0.784‐0.910). Among achievers, reactance change correlated with HbA1c change (r=−0.392; P=.032) but not among nonachievers (r=−0.089; P=.54). After the inverse probability weighting was stabilized, each 1-SD increase in left-arm reactance was associated with a 12.1 percentage-point higher probability of target achievement (95% CI 5.2%‐19.0%).ConclusionsThis pragmatic implementation study demonstrates that automated BIA is feasible for routine diabetes care and suggests potential as a digital biomarker of activity-related glycemic control. While temporal allocation precludes definitive causal inference, and findings should be interpreted as associational, the observed Walk Score moderation and bioimpedance-HbA1c dose-response patterns are consistent with behavioral mechanisms rather than pure confounding. Left-arm reactance warrants randomized validation as a scalable, passive surveillance tool for precision diabetes management.

Lanthanide/actinide (Ln/An) separation is a critical step in the reprocessing of spent nuclear fuels, enabling a more efficient utilization of nuclear resources and reducing nuclear waste contamination. However, separating Ln/An ions remains a significant challenge due to the similarity in their physicochemical properties. The periodic table and periodic law offer powerful tools for guiding chemical research. As Ln/An nuclides fall within the periodic trends, this provides possibilities for the optimized design of selective extractants. In this study, we systematically investigated the periodic patterns through which nitrilotriacetamide (NTAamide) selectively separates actinide-lanthanide ion pairs. The results indicate that separating ion pairs within the same group follows the Difference Model, while separating ion pairs of the same period follows the Similarity Model. Furthermore, our modified extractants exhibited enhanced separation selectivity for Ln/An ion pairs from the same group or period, which was validated by retrosynthetic analysis based on machine learning models. Detailed computational characterizations reveal that the modulation of the metal-oxygen bond strength is the microscopic origin underlying the enhanced separation performance.

When the leakage inlet of a levee embankment is sealed, a transient flow similar to "water hammer" occurs, and the instantaneous cyclic changes in pressure can cause deformation or damage to the sealing material. At the same time, it can cause the alternating expansion and compression of the soil in the inlet section, which can further intensify erosion and collapsing, and lead to secondary damage to the leakage. This paper regards the sealing of levee embankment leakage as a valve closure operation of a thick-walled pipe inlet section, and based on simulation calculation methods, analyzes the pressure of sealing blockage at floodgate leakage inlet. The simulation results show that the pressure peak value appears at the inlet of the leakage, and the instantaneous pressure at the hole gradually decreases in a periodic trend. When the water depth at the inlet is 2.0m, the instantaneous static pressure of the seal drops from 1.05atm to 0.02atm and lasts for about 0.25s. Within the next 0.61s, the pressure continuously increases to a maximum value of 2.0atm. The first cycle of pressure change is about 1.62s, and the average cycle is about 1.20s. In order to ensure the success rate of sealing leakage, the water hammer pressure generated by the instantaneous sealing should be reduced, and the pressure that the sealing materials and equipment bear should be reduced or dispersed. Based on this, the concept of "step-by-step sealing" inside the hole is proposed, instead of single-level sealing of the hole.

This study analyzes the temporal patterns and transaction volume trends in the Ripple (XRP) network using time series analysis. The dataset comprises over 1.2 million transactions spanning three years, allowing for a comprehensive examination of long-term trends and seasonal fluctuations. Summary statistics reveal a right-skewed distribution of transaction volume, where a majority of transactions involve relatively small amounts, while a few high-value transactions contribute disproportionately to overall network activity. Time series decomposition identifies a clear upward trend in transaction volume, with notable seasonal patterns corresponding to weekly and monthly cycles. These periodic trends suggest institutional trading behaviors, liquidity management strategies, and external market influences. Comparative forecasting analysis between ARIMA and LSTM models demonstrates that LSTM achieves superior predictive accuracy, with a 30% lower Mean Absolute Error (MAE) and a 25% reduction in Root Mean Squared Error (RMSE) compared to ARIMA. These results highlight the effectiveness of deep learning in capturing non-linear transaction dynamics within the blockchain ecosystem. Furthermore, anomaly detection using Isolation Forest successfully identifies transactional irregularities, particularly during periods of high market volatility and regulatory shifts. Several anomalous transaction spikes coincide with major market events, such as sudden exchange inflows and network congestion, reinforcing the role of external factors in influencing transaction activity. These findings emphasize the need for advanced forecasting techniques and real-time anomaly detection systems to improve transaction monitoring and enhance security within blockchain networks. Future research could integrate additional on-chain metrics, off-chain factors, and alternative deep learning models to refine predictive capabilities and support more resilient blockchain analytics frameworks.

Abstract The electrochemical reduction of CO 2 into multicarbon (C 2⁺ ) products is a promising strategy for producing sustainable fuels and chemicals, but conventional Cu catalysts suffer from poor selectivity and limited efficiency. Single‐atom alloys (SAAs), in which isolated dopants are incorporated into a Cu host, offer an atomic‐scale platform to modulate surface chemistry. Here we report a systematic theoretical investigation of 29 Cu‐based SAAs, combining grand‐canonical density functional theory, surface Pourbaix diagrams, and constant‐potential ab initio molecular dynamics with explicit solvation. We uncover a general non‐monotonic periodic trend in adsorbate binding strength—strong → weak → strong—arising from dopant‐induced perturbations of the Cu electronic structure. This universal trend provides a guiding principle: asymmetric active sites, formed by the coexistence of strong‐ and weak‐binding motifs, enable more favorable *CO–*CO coupling and thereby enhance selectivity toward C 2⁺ products. Importantly, we identify net electron transfer from dopant to host as an effective and easily computable descriptor for rapidly screening SAA candidates with low C─C coupling barriers. Guided by this framework, we highlight ScCu, VCu, ZrCu, NbCu, and TaCu as promising SAAs, exhibiting suppressed hydrogen evolution, electrochemical robustness, and efficient C─C bond formation. In particular, NbCu(111) displays a low C─C coupling barrier of 0.87 eV and a thermodynamically viable pathway to ethanol, confirmed under realistic electrolyte conditions. These findings establish atomic‐scale asymmetry as a general design paradigm for advancing SAAs catalysts in CO 2 electroreduction.

The electrochemical reduction of CO2 into multicarbon (C2⁺) products is a promising strategy for producing sustainable fuels and chemicals, but conventional Cu catalysts suffer from poor selectivity and limited efficiency. Single-atom alloys (SAAs), in which isolated dopants are incorporated into a Cu host, offer an atomic-scale platform to modulate surface chemistry. Here we report a systematic theoretical investigation of 29 Cu-based SAAs, combining grand-canonical density functional theory, surface Pourbaix diagrams, and constant-potential ab initio molecular dynamics with explicit solvation. We uncover a general non-monotonic periodic trend in adsorbate binding strength-strong → weak → strong-arising from dopant-induced perturbations of the Cu electronic structure. This universal trend provides a guiding principle: asymmetric active sites, formed by the coexistence of strong- and weak-binding motifs, enable more favorable *CO-*CO coupling and thereby enhance selectivity toward C2⁺ products. Importantly, we identify net electron transfer from dopant to host as an effective and easily computable descriptor for rapidly screening SAA candidates with low C─C coupling barriers. Guided by this framework, we highlight ScCu, VCu, ZrCu, NbCu, and TaCu as promising SAAs, exhibiting suppressed hydrogen evolution, electrochemical robustness, and efficient C─C bond formation. In particular, NbCu(111) displays a low C─C coupling barrier of 0.87eV and a thermodynamically viable pathway to ethanol, confirmed under realistic electrolyte conditions. These findings establish atomic-scale asymmetry as a general design paradigm for advancing SAAs catalysts in CO2 electroreduction.

ABSTRACT Groundwater in Pakistan, especially in the 6,498 km2 area between the Chenab and Sutlej Rivers, is a critical yet stressed resource. Levels decline by 0.08–0.6 m annually due to increasing domestic, agricultural demands, urbanization, climate change, and poor groundwater management governance. Using the MODFLOW model, this study simulates groundwater dynamics over a 15-year historical period and projects trends up to 2045. Projections indicate that, under current abstraction rates, groundwater levels could decline by 0.84–0.97 m/year by 2045. Mitigation via artificial recharge, like constructing six cascade dams on the Sutlej River, could boost recharge from 80 to 103.3 MCM daily, but abstraction may stay high at 117.8 MCM/day. On the supply side, supplementary interventions such as recharge lakes and infiltration wells can further enhance recharge potential. Climate projections also indicate a favorable 17–20% increase in rainfall from 2015 to 2064 compared with 1965 to 2014, supporting recharge initiatives. Sustainable abstraction is estimated at 0.12684 MCM/day for urban areas and 55 MCM/day across the study area. To ensure long-term water security and sustainable groundwater management, the study emphasizes policy actions such as integrating recharge strategies, issuing permits, enforcing safe yield limits, and community engagement.

The burden of vastly different diseases has been used to predict National Institutes of Health (NIH) research funding, typically including only 1 year of data. A multi-year analysis of related diseases would provide a more accurate assessment of which diseases are funded appropriately compared to their burden, enabling targeted lobbying efforts and policy changes to ensure equitable funding. Determining under- or over-funded psychiatric and neurological diseases over a 13-year period. This ecological study utilized disability-adjusted life years (DALYs) to quantify disease burden. Quantile regression residuals and 95% CIs at several quantiles determined under- or over-funding. Joinpoint regression delineated DALY trends using average annual percent change (AAPC). The United States. Persons contributing DALYs from attention-deficit/hyperactivity disorder, autism, depressive disorders, eating disorders, schizophrenia, epilepsy, headache disorders, multiple sclerosis, Parkinson's disease, or stroke. None. The difference between actual and predicted funding. Changes in DALYs had a greater impact at higher funding levels. Eating and headache disorders were significantly underfunded at all quantiles. The severity of underfunding at the 50th quantile decreased for eating (363% [CI: 329%, 386%] to 190% [CI: 170%, 204%]) and headache (1497% [CI: 1164%, 1665%] to 676% [CI: 514%, 759%]) disorders from 2011 to 2023. Disability-adjusted life years for eating disorders decreased (AAPC=-1.0% [CI:-1.1%,-0.9%]), whereas DALYs for headache disorders increased marginally (AAPC=0.1% [CI: 0.1%, 0.1%]). Changes in disease burden were correlated with more significant funding changes in diseases with greater baseline funding. The 2 lowest-funded diseases, eating and headache disorders, are being drastically underfunded compared to their disease burden. While this was not correlated with significant aberrations in disease burden trends in the study period, further lobbying efforts and policy changes must be considered to ensure these diseases receive equitable funding.

ABSTRACT The accurate characterisation of contact stress at rotor mating surfaces is of critical importance for ensuring the assembly quality of aero-engines. The ultrasonic method serves as an important method for contact stress quantification at mating surfaces, where the focusing performance of ultrasonic waves at mating surfaces is the key factor in achieving precise characterisation. An in-depth analysis of the acoustic field focusing characteristics of phase-reversal Fresnel zone plate (PR-FZP) in direct contact with solids is presented. Comparative analysis of the focusing performance of PR-FZP fabricated from different materials indicates that the PR-FZP made of T2 achieves the highest acoustic intensity of 1.89 × 107 W/m2, along with a smaller full width at half maximum (FWHM). Adding a matching layer structure to PR-FZP does not enhance its focusing performance. Incorporating a reflective layer significantly improves the focusing capability of PR-FZP, with tungsten-based reflective layers demonstrating optimal performance by achieving 1.349 times the acoustic intensity of PR-FZP without a reflective layer. Finally, the influence of lens thickness parameters on PR-FZP focusing characteristics was analysed. The study revealed that the acoustic intensity of PR-FZP exhibits periodic variation trends with changes in remaining lens thickness and groove depth.