Rational Strategy Research Articles

Development and validation of a clinical nomogram prediction model for surgical site infection following lumbar disc herniation surgery

Surgical site infection (SSI) following lumbar disc herniation (LDH) surgery leads to prolonged hospital stays, increased costs and reoperations. Therefore, we aim to develop and validate a nomogram to predict the risk of SSI following LDH surgery, thereby helping spine surgeons design personalized prevention strategies and promote early recovery. Data from 647 patients with SSI who underwent LDH surgery at the First Affiliated Hospital of Air Force Medical University (AFMU) from 2020 to 2023 were collected. Ultimately, 241 patients with SSI were selected based on inclusion and exclusion criteria. Patients were randomly divided into training and validation sets with a ratio of 7:3. LASSO regression, univariate, and multivariate logistic regression were utilized to identify target variables and establish the prediction model, which was subsequently validated. Six factors—Age, Body Mass Index (BMI), Postoperative Suction Drainage (PSD), Gelatin Sponge (GS), None-Preoperative Antibiotic (NPTA), and Thrombin Time (TT)—were selected to construct the nomogram model. In the training set, the area under the curve (AUC) for the nomogram was 0.818 (95% CI 0.779–0.857). In the validation set, the AUC was 0.782 (95% CI 0.717–0.846). Calibration curves for both sets showed satisfactory agreement between predicted and actual SSI probabilities. Decision curve analysis indicated that the nomogram is clinically useful with a threshold range of 1–90%. The Clinical Impact Curve (CIC) demonstrated an acceptable cost-benefit ratio. The developed nomogram model effectively predicts the risk of SSI following LDH surgery, enabling spine surgeons to formulate more professional and rational clinical prevention strategies.

Activating the Mn Single Atomic Center for an Efficient Actual Active Site of the Oxygen Reduction Reaction by Spin-State Regulation.

The ligand engineering for single-atom catalysts (SACs) is considered a cutting-edge strategy to tailor their electrocatalytic activity. However, the fundamental reasons underlying the reaction mechanism and the contemplation for which the actual active site for the catalytic reaction depends on the pyrrolic and pyridinic N ligand structure remain to be fully understood. Herein, we first reveal the relationship between the oxygen reduction reaction (ORR) activity and the N ligand structure for the manganese (Mn) single atomic site by the precisely regulated pyrrolic and pyridinic N4 coordination environment. Experimental and theoretical analyses reveal that the long Mn-N distance in Mn-pyrrolic N4 enables a high spin state of the Mn center, which is beneficial to reduce the adsorption strength of oxygen intermediates by the high filling state in antibond orbitals, thereby activating the Mn single atomic site to achieve a half-wave potential of 0.896 V vs RHE with outstanding stability in acidic media. This work provides a new fundamental insight into understanding the ORR catalytic origin of Mn SACs and the rational design strategy of SACs for various electrocatalytic reactions.

Progressive Fabrication of a Pt‐Based High‐Entropy‐Alloy Catalyst toward Highly Efficient Propane Dehydrogenation

High‐entropy alloys (HEAs) have emerged as burgeoning heterogeneous catalysts due to their vast material space, unique structure, and superior stability. However, the dominant trial‐and‐error approaches hamper the exploration of efficient catalysts, necessitating the development of rational design strategies. Here, we report a progressive approach to the design and fabrication of HEA catalysts guided by alloying effects toward propane dehydrogenation. Cu, Sn, Au, and Pd are selected and demonstrated to induce dilution, encapsulation, surface enrichment, and inhomogeneity effects on Pt. The fabricated HEA, PtCuSnAuPd/SiO2, exhibits excellent activity, selectivity, and stability. The propylene formation rates reach 256 and 390 molC3H6 gPt−1 h−1 at 550 and 600 °C, respectively. Systematic characterizations reveal that the random elemental mixing, structural stability, and high Pt exposure promote the exposure of abundant stable isolated Pt sites. This work comprehensively explores the rational design and fabrication of HEA catalysts from a unique perspective, offering opportunities for developing advanced catalysts.

Progressive Fabrication of a Pt-Based High-Entropy-Alloy Catalyst toward Highly Efficient Propane Dehydrogenation.

High-entropy alloys (HEAs) have emerged as burgeoning heterogeneous catalysts due to their vast material space, unique structure, and superior stability. However, the dominant trial-and-error approaches hamper the exploration of efficient catalysts, necessitating the development of rational design strategies. Here, we report a progressive approach to the design and fabrication of HEA catalysts guided by alloying effects toward propane dehydrogenation. Cu, Sn, Au, and Pd are selected and demonstrated to induce dilution, encapsulation, surface enrichment, and inhomogeneity effects on Pt. The fabricated HEA, PtCuSnAuPd/SiO2, exhibits excellent activity, selectivity, and stability. The propylene formation rates reach 256 and 390 molC3H6 gPt-1 h-1 at 550 and 600 °C, respectively. Systematic characterizations reveal that the random elemental mixing, structural stability, and high Pt exposure promote the exposure of abundant stable isolated Pt sites. This work comprehensively explores the rational design and fabrication of HEA catalysts from a unique perspective, offering opportunities for developing advanced catalysts.

Development of α-Helical Antimicrobial Peptides with Imperfect Amphipathicity for Superior Activity and Selectivity.

The advancement of antimicrobial peptides (AMPs) as therapeutic agents is hindered by their poor selectivity. Recent evidence indicates that controlled disruption of the amphipathicity of α-helical AMPs may increase the selectivity. This study investigated the role of imperfect amphipathicity in optimizing AMPs with varied sequences to enhance their activity and selectivity. Among these, the lead peptide RI-18, characterized by an imperfectly amphipathic α-helical structure, demonstrated potent and broad-spectrum antibacterial activity without inducing hemolytic or cytotoxic effects. RI-18 effectively eliminated planktonic and biofilm-associated bacteria as well as persister cells and exhibited high bacterial plasma membrane affinity, inducing rapid membrane permeabilization and rupture. Notably, RI-18 significantly reduced bacterial loads without promoting bacterial resistance, highlighting its therapeutic potential. Overall, this study identified RI-18 as a promising antimicrobial candidate. The rational strategy of tuning imperfect amphipathicity to enhance the AMP activity and selectivity may facilitate the design and development of AMPs.

The effectiveness and factors influencing frequency of endoscopic bougie dilatation in treating postoperative anastomotic stenosis of congenital esophageal atresia

ObjectiveThis study is to evaluate the effectiveness and frequency factors of endoscopic bougie dilatation in treating postoperative anastomotic stenosis of congenital esophageal atresia (CEA).MethodsThe clinical data of patients of anastomotic stenosis with endoscopic bougie were retrospectively analyzed. According to the number of dilation times (ND), patients were divided into two groups (Group 0: ND < 3; Grooup1: ND ≥ 3), and the differences in multiple clinical data were compared. Lasso regression and Ridge regression were used to screen important variables. Classification models were built utilizing various machine learning algorithms and their performance were evaluated. Finally, Kaplan-Meier model was used to estimate the probable-time distribution of children achieving normal feeding.ResultsSeventy-five patients underwent a total of 210 times of dilation, with a median of 3 times of dilation. The overall effectiveness was 98.67% (74/75), with perforation in 2 case (0.95%), and obvious bleeding in 3 cases (1.43%). Initial diameter of bougie, final diameter of bougie, treatment pattern (Regular: dilation each 4weeks; Wait-and-see: dilation until symptoms present), age at final dilation, esophageal obstruction by food were the factors related to ND. Random Forest (RF) and Logistic regression (LR) model were excellent models for predicting ND. The median age for achieving normal eating in Group0 was 120 days (95% CI: 90–160), while it was 270 days (95% CI: 240–460) in Group1 with a statistically significant difference (P < 0.0001).ConclusionEndoscopic bougie dilatation is a safe and effective treatment for anastomotic stenosis. Selecting the appropriate bougie, using symptoms as the criterion for dilation, and minimizing the dilations under 3 times constitute a rational strategy.

Nanosized boron nitride-incorporated polyvinyl alcohol composites with TEMPO-oxidized cellulose nanofibers as ultrathin thermal interface materials

With the miniaturization and dense packing of electrical devices and mobility platforms, the effective thermal management at the interfaces of components in compact form factors is essential to overcome the performance limits and ensure the stability. Herein, we report the development of assembly of nanosized boron nitrides (BN) and TEMPO-oxidized cellulose nanofibers (T-CNFs) in polyvinyl alcohol (PVA) composites as ultrathin thermal interface materials (TIMs). BN nanoparticles (average thickness of 3.8–4.0 nm, lateral size of 90–100 nm, and aspect ratio of 25) were produced with a yield exceeding 80 % from the chemical treatment of hexagonal BN with NaOH and subsequent ball milling. TEMPO-oxidized cellulose nanofibers (T-CNFs) were added to mechanically reinforce the PVA-based matrix, while by the functionalization with OH– groups, the BN particles dispersed readily in the PVA solution, obtaining ultrathin nanosized BN/PVA/T-CNF composite films (∼50 µm). In contrast to the expected low thermal conductivity due to surface defects and high contact resistances typical of nanosized BN, composite films containing 50 wt% nanosized BN exhibited significantly high in-plane and through-plane thermal conductivities of 11.13 and 1.22 W/mK, respectively. Comparative analysis based on the Lewis–Nielsen model revealed that the size, shape, and agglomeration state of the BN particles could highly influence the thermal conductivity of composite films. Furthermore, heat dissipation experiments reflecting practical conditions demonstrated the outstanding performance and thermal stability of nanosized BN/PVA/T-CNF films as TIMs. This study will inspire rational strategies to facilely incorporate nanosized BN to diverse composites, offering advanced thermal characteristics with mechanical robustness.

Designing Impact Resistance and Robustness into Slippery Lubricant Infused Porous Surfaces.

Slippery lubricant infused porous surfaces (SLIPS) have the potential to address daunting challenges such as undesirable surface fouling/biofouling, icing, etc. However, the depletion of lubricants hampers their practical utility. As a solution, here a rational strategy is introduced that operates synergistically in three parts. First, ultra-high capillary pressure is exploited from the reticular structure of metal-organic frameworks (MOFs) with sub-nanometer pores. Second, the need for geometric compatibility is demonstrated; the lubricant chain diameter must be smaller than the MOF pore to enable lubricant chain intercalation. Lastly, the MOF pore chemistry is tailored to achieve a strong intermolecular interaction for any given MOF/lubricant combination. The strategy is investigated through experiments and quantum/molecular simulations, which show that the approach helps lock the intercalated lubricant chains inside the MOF pores and forms a non-conventional supramolecular structure. The resulting SLIPS (including those with fluorine-free chemistry) not only show typical low wetting hysteresis, friction, and ice adhesion but are uniquely resistant to more stringent tests such as continuous dripping and sliding of water droplets (up to 50hrs), repeated impacts of high-speed water jets (liquid impact Weber number >4×104) and prevent bacterial biofilm formation even in dynamic flow conditions. The findings may widen the practical applications of SLIPS.

Computational chemistry facilitates the development of second near-infrared xanthene-based dyes.

The dyes in the second near-infrared (NIR-II) region play a crucial role in advancing imaging technology. However, developing small-molecule dyes in NIR-II poses a significant bottleneck to meet the substantial demands in biological fields, which may be attributed to the lack of a rational design strategy. Herein, we designed a series of rhodamine analogs with more red-shifted emission by replacing the oxygen-bridge atom in xanthene-based dyes with -C(CH3)2, -Si(CH3)2, -SO2, and -P(O)Ph. We investigated the frontier molecular orbital, electrostatic potential surfaces, the interaction region indicator, electron-hole distribution, and absorption and emission spectrum of xanthene-based dyes using (time-dependent) density functional theory. Our results demonstrated that these designed small molecular dyes exhibit long emission wavelengths covering 1377-1809nm. We expected these findings to enable the targeted design of long-wavelength rhodamines. Geometry optimization of dyes in the ground and excited states was carried out at ω-B97XD/Def2SVP level using Gaussian 16 A03. The absorption and emission wavelengths were evaluated using 13 functional, including TPSSH, O3LYP, B3LYP*, B3LYP, PBE0, MPW1B95, PBE-1/3, PBE38, MPWB1K, MN15, BHandHLYP, ω-B97XD, and CAM-B3LYP.

Bone-Targeting Radionuclides in the Treatment of Metastatic Castration-Resistant Prostate Cancer: A Review on Radium-223 Chloride (Alpharadin) in Combination with Other Therapies

Recent advances have broadened the range of therapeutic options for mCRPC, with several new treatments, including novel hormonal therapies (enzalutamide, abiraterone), chemotherapeutic agents (docetaxel, cabazitaxel), immunotherapies (sipuleucel-T), and bone targeting radiopharmaceuticals (radium-223) showing improved clinical outcomes and receiving U.S. Food and Drug Administration approval. These new treatments provide new avenues for improving patient survival and quality of life. Radium-223, a targeted alpha-emitter, specifically targets bone metastases, offering palliative benefits and a potential increase in life expectancy. The integration of radium-223 with other treatments shows promise for managing mCRPC. However, the optimal sequencing and combination of radium-223 with other therapies are still being explored, with various clinical trials investigating new therapeutic approaches. The integration of these therapies, especially to provide more effective, personalized treatment strategies, requires further investigation. A thorough literature review was conducted on current treatments for mCRPC, including chemotherapeutic agents, oral hormonal therapies targeting the androgen receptor axis, immunotherapies, and radium-223. Ongoing clinical trials investigating radium-233 in the context of other therapies for the treatment of mCRPC patients were also reviewed. Further studies should focus on determining the optimal sequencing and dosing and identifying biomarkers that predict treatment response to enhance outcomes of mCRPC patients. This review underlines the rational strategies of combining radium-223 with other therapies, investigating their impact on bone in terms of delaying skeletal-related events, and managing bone disease progression in mCRPC patients.

Evaluating robo-advisors through behavioral finance: a critical review of technology potential, rationality, and investor expectations

The mini review assesses the value propositions of robo-advisors through the lens of behavioral finance. Despite their promise of data-driven, rational investment strategies, robo-advisors may not fully replicate the personalized service of human financial advisors or eliminate human biases in decision-making. A content analysis of 80 peer-reviewed articles and publications was conducted, focusing on the intersection of financial technology and behavioral finance. Literature was retrieved using The Chicago School University Library's OneSearch and the EBSCO host database, with key terms including “robo-advisor,” “investment behavior,” “risk tolerance,” “financial literacy,” and “affective trust.” The review identifies four key limitations of robo-advisors: (1) their inability to replicate the service-relationship of human advisors; (2) the presence of human bias in supposedly rational algorithms; (3) the inability to minimize market risk; and (4) their limited impact on improving users' financial literacy. Instead, robo-advisors temporarily compensate for a lack of financial knowledge through passive investment strategies. The findings suggest that integrating behavioral finance principles could enhance the predictive power of robo-advisors, though this would introduce additional complexities. The review calls for further research and regulatory measures to ensure that these technologies prioritize investor protection and financial literacy as they continue to evolve.

Does Strategy Formulation Process Matter on Human Resource Strategy Outcome?

This article explores the way in which human resource strategies come into being. Using modes of strategy formulation process three hypotheses are established. A cross-sectional research design was adopted. Data was collected using Structure questionnaires while multiple regression analysis was performed to test for a number of hypothesized relationships. Findings shows that rational and adaptive human resource strategy formulation processes explain significant variation in human resource strategy outcome while interactive human resource strategy has no significant relationship with human resource strategy outcome. The contribution of this study to knowledge is that HR strategy formulation process that involves inputs from multiple stake holders has a significant effect on strategy outcome of human resource strategies hence a source of competitive advantage. More importantly, this article found that there is a problem of inability to formulate human resource strategies in the public sector. Therefore the study recommends that State corporations should adopt interactive HR strategy formulation process to facilitate formulation and implementation of HR strategies in their organizations.

Customized Preparation of Heat-Resistant Fully Flexible Sensors Based on Coaxial 3D Printing.

The conventional behavior recognition strategy for wearable sensors used in high-temperature environments typically requires an external power supply, and the manufacturing process is cumbersome. Herein, we present a rational design strategy based on fully flexible printable materials and a customized device-manufacturing process for skin-conformable triboelectric nanogenerator sensors. In detail, using high temperature-resistant ink and 3D printing technology to manufacture a coaxial triboelectric nanogenerator (C-TENG) sensor, the C-TENG exhibits high stretchability (>400%), a wide working range (>250 °C), and high output voltage (>100 V). The C-TENG can be worn on various parts of the human body, providing a robust skin-device interface that recognizes diverse human behaviors. Using machine learning algorithms, behaviors such as walking, running, sitting, squatting, climbing stairs, and falling can be identified, achieving 100% behavior recognition accuracy through the selective input and optimization of an appropriate dataset. This paper provides a research perspective for the customization, extension, and rapid fabrication of heat-resistant, fully flexible TENGs.

A Ni-based metal hydroxide-organic framework mesh membrane with ultra-durable underwater superoleophobicity for high-efficient oil/water separation

Recently, MOF-based oil/water separation membranes with superwettability have attracted great attention in the treatment of oily wastewater due to their uniform chemical composition and intrinsic porosity. However, the real separation performance is still limited by broking the metal-ligand bonds of conventional MOF materials in extreme chemical and mechanical environments, such as acidic, alkaline, saline, organic, and abrasion. Herein, we provide a metal hydroxide-organic framework (MHOF) composite mesh membrane for high-efficient oil/water separation by simply growing Ni2(OH)2 clusters onto a polydopamine (PDA)-modified stainless-steel mesh (SSM). Compared with conventional MOF materials, our membrane possesses ultra-durable underwater superoleophobicity by taking advantages of its strong chemical bridging, rich hydrophilic groups, and rough surface morphology, which enables a 1 μL water droplet to spread to 0° contact angle within <100 ms and also obtains an ultra-low underwater oil adhesion force ∼1.9 μN. Separation of both oil/water mixtures and oil-in-water emulsions can be achieved by this Ni-based MHOF mesh membrane with high separation efficiency >99.7 % and large permeate flux >57,000 L m−2 h−1. Furthermore, the Ni2(OH)2@PDA-SSM mesh membrane exhibits excellent anti-oil-fouling, chemical stability and abrasion resistance, which shows a promising candidate for practical applications. This study provides a rational strategy to construct high-performance MHOF membranes for oil/water separation.

The Journey of Antibody-Drug Conjugates: Lessons Learned from 40 Years of Development.

Antibody-drug conjugates (ADC) represent one of the most rapidly expanding treatment modalities in oncology, with 11 ADCs approved by the FDA and more than 210 currently being tested in clinical trials. Spanning over 40 years, ADC clinical development has enhanced our understanding of the multifaceted mechanisms of action for this class of therapeutics. In this article, we discuss key insights into the toxicity, efficacy, stability, distribution, and fate of ADCs. Furthermore, we highlight ongoing challenges related to their clinical optimization, the development of rational sequencing strategies, and the identification of predictive biomarkers. Significance: The development and utilization of ADCs have allowed for relevant improvements in the prognosis of multiple cancer types. Concomitantly, the rise of ADCs in oncology has produced several challenges, including the prediction of their activity, their utilization in sequence, and minimization of their side effects, that still too often resemble those of the cytotoxic molecule that they carry. In this review, we retrace 40 years of development in the field of ADCs and delve deep into the mechanisms of action of these complex therapeutics and reasons behind the many achievements and failures observed in the field to date.

Long‐term Durability of Seawater Electrolysis for Hydrogen: From Catalysts to Systems

AbstractDirect electrochemical seawater splitting is a renewable, scalable, and potentially economic approach for green hydrogen production in environments where ultra‐pure water is not readily available. However, issues related to low durability caused by complex ions in seawater pose great challenges for its industrialization. In this review, a mechanistic analysis of durability issues of electrolytic seawater splitting is discussed. We critically analyze the development of seawater electrolysis and identify the durability challenges at both the anode and cathode. Particular emphasis is given to elucidating rational strategies for designing electrocatalysts/electrodes/interfaces with long lifetimes in realistic seawater including inducing passivating anion layers, preferential OH−adsorption, employing anti‐corrosion materials, fabricating protective layers, immobilizing Cl− on the surface of electrocatalysts, tailoring Cl− adsorption sites, inhibition of OH− binding to Mg2+ and Ca2+, inhibition of Mg and Ca hydroxide precipitation adherence, and co‐electrosynthesis of nano‐sized Mg hydroxides. Synthesis methods of electrocatalysts/electrodes and innovations in electrolyzer are also discussed. Furthermore, the prospects for developing seawater splitting technologies for clean hydrogen generation are summarized. We found that researchers have rethought the role of Cl− ions, as well as more attention to cathodic reaction and electrolyzers, which is conducive to accelerate the commercialization of seawater electrolysis.

Virtual Ligand-Assisted Optimization: A Rational Strategy for Ligand Engineering

Virtual Ligand-Assisted Optimization: A Rational Strategy for Ligand Engineering

Development and validation of a machine learning-based nomogram for prediction of unplanned reoperation post-spinal surgery within 30 days

Unplanned reoperation post-spinal surgery (URPS) leads to prolonged hospital stays, higher costs, decreased patient satisfaction, and adversely affects postoperative rehabilitation. This study aimed to develop and validate prediction models (nomograms) for early URPS risk factors using machine learning (ML) methods, aiding spine surgeons in designing prevention strategies, promoting early recovery, reducing complications and improving patient satisfaction. Medical records of 639 patients who underwent reoperation post-spinal surgery (RPS) from the First Affiliated Hospital of Air Force Medical University (2018 - 2022) were collected, including baseline indicators, perioperative indicators, and laboratory indicators. After applying inclusion and exclusion criteria, 122 URPS and 155 non-URPS patients were identified and randomly divided into training (82 URPS, 111 non-URPS) and validation (40 URPS, 44 non-URPS) cohorts. Three ML methods (LASSO regression, Random Forest, and SVM-RFE) were used to select feature variables, and their intersection was used to develop the prediction model, tested on the validation cohort. Six factors-implant, postoperative suction drainage (PSD), gelatin sponge (GS), anticoagulants (ATG), antibiotics (ATB), and disease type (DT)-were identified to construct a nomogram diagnostic model. The area under the curve (AUC) of this nomogram was 0.829 (95% CI 0.771-0.886) in the training cohort and 0.854 (95% CI 0.775-0.933) in the validation cohort. Calibration curves demonstrated satisfactory agreement between predictions and actual probabilities. The decision curve indicated clinical usefulness with a threshold between 1% and 90%. The established model can effectively predict URPS in patients and can assist spine surgeons in devising personalized and rational clinical prevention strategies.

Membrane Composition Allows the Optimization of Berberine Encapsulation in Liposomes.

Berberine (BBR) is a natural molecule with noteworthy pharmacological properties, including the prevention of antibiotic resistance in Gram-negative bacteria. However, its oral bioavailability is poor, thus resulting in an impaired absorption and efficacy in humans. In combination with other drugs, liposomes have been shown to enhance the availability of the drug, representing a smart delivery system to target tissues and reduce negative side effects. To date, there is a lack of studies on BBR and liposomes that enable the rationalization and molecular-based design of such formulations for future use in humans. In this work, the encapsulation of BBR into liposomes is proposed to overcome current limitations using a combination of experimental and computational assays to rationalize the membrane composition of liposomes that maximizes BBR encapsulation. First, the encapsulation efficiency was measured for several membrane compositions, revealing that it is enhanced by cholesteryl hemisuccinate and, to a lesser extent, by cholesterol. The physical basis of the BBR encapsulation efficiency and permeability was clarified using molecular dynamics simulation: using the lipid composition, one can tune the capability of membranes to attract, i.e., to adsorb, the molecules onto their surface. Overall, these findings suggest a rational strategy to maximize the encapsulation efficiency of liposomes by using negatively charged lipids, thus representing the basis for designing delivery systems for BBR, useful to treat, e.g., antibiotic resistance.

Controlling Long-Term Plasticity in Neuromorphic Computing Through Modulation of Ferroelectric Polarization.

Electrolyte-gated transistors (EGTs) have significant potential for neuromorphic computing because they can control the number of ions by mimicking neurotransmitters. However, fast depolarization of the electric double layer (EDL) makes it difficult to achieve long-term plasticity (LTP). Additionally, most research utilizing organic ferroelectric materials has been focused on basic biological functions, and the impact on nonvolatile memory properties is still lacking. Herein, we present a polyvinylidene fluoride (PVDF)-based ion-gel synaptic device using PVDF and poly(vinylidene fluoride-co-hexafluoropropylene) (P(VDF-HFP)) to implement LTP through the introduction of ferroelectric materials. The PVDF-based polymer slows the escape rate of TFSI anions from the electrolyte/channel layer through residual polarization. The fabricated synaptic devices successfully demonstrate LTP by controlling ion adsorption under the influence of PVDF-based polymers. Furthermore, it implements synaptic functions including paired pulse facilitation (PPF), high-pass filtering, and neurotransmitter control. To validate the potential of neuromorphic computing, we successfully achieved high recognition rates for artificial/convolutional neural network (A/CNN) simulations via sequential adsorption and desorption under ferroelectric polarization with long-term potentiation/depression (LTP/D). This study provides a rational ion adsorption strategy utilizing the ferroelectric polarization caused by the introduction of a PVDF-based polymer in the dielectric layer.