Chemical Potential Research Articles

Real-time chiral dynamics at finite temperature from quantum simulation

In this study, we explore the real-time dynamics of the chiral magnetic effect (CME) at a finite temperature in the (1+1)-dimensional QED, the massive Schwinger model. By introducing a chiral chemical potential μ5 through a quench process, we drive the system out of equilibrium and analyze the induced vector currents and their evolution over time. The Hamiltonian is modified to include the time-dependent chiral chemical potential, thus allowing the investigation of the CME within a quantum computing framework. We employ the quantum imaginary time evolution (QITE) algorithm to study the thermal states, and utilize the Suzuki-Trotter decomposition for the real-time evolution. This study provides insights into the quantum simulation capabilities for modeling the CME and offers a pathway for studying chiral dynamics in low-dimensional quantum field theories.

Information theoretic measures for Lifshitz system

In this work, we have studied various mixed state information theoretic quantities for an excited state of Lifshitz spacetime in 3 + 1-dimensions. This geometry is the gravity dual to a class of 2 + 1-dimensional quantum field theories having Lifshitz symmetry. We have holographically calculated mutual information, entanglement wedge cross section, entanglement negativity and mutual complexity for strip like subsystems at the boundary. For this we have used the results of holographic entanglement entropy and complexity present in the literature. We first calculate all of these mentioned quantities for the pure state of Lifshitz spacetime. Then we have moved on to calculate all these quantities for excited state of the Lifshitz spacetime. The gravity dual of excited state of Lifshitz systems in field theory can be obtained by applying constant perturbations along the boundary direction. Further, we would like to mention that for the simplicity of calculation we are only considering results up to the first order in perturbation. The change in the obtained holographic information theoretic quantities are then related to entanglement entropy, entanglement pressure, entanglement chemical potential and charge using the stress tensor complex. These relations are analogous to the first law of entanglement thermodynamics given earlier in the literature. All the calculations are carried out for both values of dynamical scaling exponent (z) present in the Lifshitz field theory.

Unleashing the Power of Domino Reactions on Carbohydrates: State of the Art

AbstractThe intricate nature of carbohydrate structures has prompted the scientific community to seek efficient protocols for their manipulation. Lengthy synthetic pathways, often necessary to achieve complex sugar structures, pose challenges not only in terms of time and cost but also regarding environmental sustainability. Consequently, domino transformations serve as valuable tools in streamlining drug discovery processes. Sequential procedures involving fewer steps and minimal isolation/purification steps are particularly appealing to organic chemists in the field of carbohydrate chemistry. This review highlights several examples of domino transformations applied to carbohydrates, aiming to summarize their chemical potential in delivering sugar‐based compounds with significant applications in the generation of new chemical scaffolds for drug discovery and chemical biology.

Development of new sustainable pyridinium ionic liquids: From reactivity studies to mechanism-based activity predictions.

This study addresses the development of sustainable pyridinium ionic liquids (ILs) because of their potential applications in agriculture and pharmaceuticals. Pyridinium-based ILs are known for their low melting points, high thermal stability, and moderate solvation properties. We synthesized three novel pyridinium-based ILs: 1-(2-(isopentyloxy)-2-oxoethyl)pyridin-1-ium chloride, 1-(2-(hexyloxy)-2-oxoethyl)pyridin-1-ium chloride, and 1-(2-(benzyloxy)-2-oxoethyl)pyridin-1-ium chloride. The biological activities of these compounds were evaluated through plant growth promotion, herbicidal, and insecticidal assays. Our results show that the benzyloxy derivative significantly enhances wheat and cucumber growth, whereas the isopentyloxy compound has potent herbicidal effects. Computational methods, including DFT calculations and molecular docking, were applied to understand the structure‒activity relationships (SARs) and mechanisms of action. The computational techniques involved dispersion-corrected density functional theory (DFT) with the B3LYP functional and the 6-311G** basis set. Grimme's D3 corrections were included to account for dispersion interactions. The calculations were performed via GAMESS-US software. Quantum descriptors of reactivity, such as ionization potential, electron affinity, chemical potential, and electrophilicity index, were derived from the HOMO and LUMO energies. Molecular docking studies were conducted via the CB-Dock server via AutoDock Vina software to predict binding affinities to cancer-related proteins. Petra/Osiris/Molinspiration (POM) analysis was used to predict the drug likeness and other pharmaceutical properties of the synthesized ILs.

Machine Learning-Based Toxicological Modeling for Screening Environmental Obesogens.

The emerging presence of environmental obesogens, chemicals that disrupt energy balance and contribute to adipogenesis and obesity, has become a major public health challenge. Molecular initiating events (MIEs) describe biological outcomes resulting from chemical interactions with biomolecules. Machine learning models based on MIEs can predict complex toxic end points due to chemical exposure and improve the interpretability of models. In this study, a system was constructed that integrated six MIEs associated with adipogenesis and obesity. This system showed high accuracy in external validation, with an area under the receiver operating characteristic curve of 0.78. Molecular hydrophobicity (SlogP_VSA) and direct electrostatic interactions (PEOE_VSA) were identified as the two most critical molecular descriptors representing the obesogenic potential of chemicals. This system was further used to predict the obesogenic effects of chemicals on the candidate list of substances of very high concern (SVHCs). Results from 3T3-L1 adipogenesis assays verified that the system correctly predicted obesogenic or nonobesogenic effects of 10 of the 12 SVHCs tested, and identified four novel potential obesogens, including 2-benzotriazol-2-yl-4,6-ditert-butylphenol (UV-320), 4-(1,1,5-trimethylhexyl)phenol (p262-NP), 2-[4-(1,1,3,3-tetramethylbutyl)phenoxy]ethanol (OP1EO) and endosulfan. These validation data suggest that the screening system has good performance in adipogenic prediction.

Exploring Tsallis thermodynamics for boundary conformal field theories in gauge/gravity duality

Inspired by AdS/CFT interpretation Karch and Robinson (2015), we analyze thermodynamics for thermal boundary conformal field theories (CFT) that are dual to four-dimensional charged anti-de Sitter (AdS) black holes embedded in 11-dimensional M-theory-inspired models with AdS4×S7 space–time, employing the framework of Tsallis entropy. The latter is recognized as a nonadditive extension of the Boltzmann–Gibbs entropy that can satisfy the thermodynamic extensivity for black holes. Specifically, we consider AdS black holes in AdS4×S7 spacetime, interpreting the number of M2-branes as a thermodynamic variable. Using the Tsallis entropy enables us to highlight peculiar thermodynamic features, resorting to essential tools such as the chemical potential and Gibbs energy while examining phase transitions along iso-charge partitions. Then, we leveraged a class of geometrothermodynamic formalisms, including Weinhold, Ruppeiner, Quevedo I, and II metrics. Quevedo’s formulations provide richer information about phase transitions than the first two methods. Our study sheds new light on AdS black holes in a thermodynamically proper context, deepening our understanding of the role of non-extensivity in the critical behavior of such complex systems.

Synthesis, Characterization, Bioactivity Evaluation, and POM/DFT/Docking Analysis of Novel Thiazolidine Derivatives as Potent Anticancer and Antifungal Agents

AbstractA series of 2,2′‐(1,4‐phenylene)bis(N‐substituted phenylthiazolidine‐4‐amide) derivatives, denoted as (A3–9), were synthesized, and characterized for their potential applications against prostate cancer cells (PC3), and Candida albicans fungi. These compounds incorporate various substituents on the phenyl ring such as 4‐NO2, 3‐NO2, 4‐COCH3, 4‐H, 4‐OCH3, 4‐OCH2CH3, and 4‐Cl. The chemical structures of these derivatives were confirmed by NMR, FTIR, and mass spectroscopy. Biological assays, utilizing the MTT assay for prostate cancer cells (PC3) and the disk diffusion assay for Candida albicans fungi, were conducted to evaluate the bioactivity of these compounds. The results revealed promising cytotoxic and antifungal activities. Specifically, compounds A3 (IC50=69.74±0.96), A4 (IC50=63.64±0.950), and A9 (IC50=57.14±0.88 μg/mL) exhibited notable potency against PC3 cells, while A7 and A8 exhibited considerable antifungal efficacy against Candida albicans with MIC of 312 μg/mL. Moreover, density functional theory (DFT) simulations were used to study electronic properties and reactivity descriptors such as energy gap (Eg), ionization potential (IP), electron affinity (EA), chemical potential (μ), chemical hardness (η), global softness (σ), electronegativity (χ), and electrophilicity (ω) to gain a better understanding of the Structure‐Activity Relationship (SAR). Molecular docking analysis against DNA Gyrase and EGFR tyrosine kinase enzymes revealed strong binding interactions of the investigated molecules within their active sites, making them valuable candidates for further development as therapeutic agents against prostate cancer and fungal infections. POM analysis indicates the presence of two antifungal pharmacophore sites (O1δ−, O2δ−) and (O3δ−, O4δ−), as well as two antitumor pharmacophore sites (O1δ−, NH1δ+) and (O4δ−, NH2δ+).

On Theoretical Aspect of Photons Emission From Quark-Gluon Interaction Upon Hard Collision

Abstract This work applies a quantum chromodynamics theory QCD to photon emission from heavy quark-gluon scattering in the strong interaction quark-gluon to study and calculate photon flow in hard interaction processes. The photon flow from the dense quark-gluon interaction was calculated using critical temperature, quantum chromodynamic coupling and fugacity at chemical potential μq (500 MeV) for the anti-top with gluon interaction in t ¯ g → s ¯ γ system. The photon flow spectrum in hard collisions is described under the first leading order approximation for QCD theory at finite chemical potential and critical temperature using various photon energy values dependent on the fugacity of quark and gluon. Photon flux calculation provided valuable insights into QGP conditions. The coupling strength αc (T) calculation is a strongly decreasing function of critical temperature ranging 107MeV ≤ Tc ≤ 145MeV and also find appreciable increasing as a result of increasing temperature of system ranging 180MeV ≤ T ≤ 360MeV. The photon flow produced in the t ¯ g → s ¯ γ system was observed in the low range of photon energy with two critical temperatures. The total photon emission strongly decreases marginally as a function of the increase in photon energy. The photon flow emission was found to have appreciable enhancement at the anti-top quark interaction with gluon and it increases highly as a result of the increased temperature of the system and reaches to maximum near 360 MeV at minimum strength coupling in the energy of the photon 1GeV≤E≤2 GeV.

Investigation of aluminum nitrate nanotube as the smart carriers for targeted delivery of gemcitabine anti-lung cancer drug

The potential of aluminum nitrate nanotube as a drug carrier for anti-lung cancer drug gemcitabine is examined based on the density functional theory (DFT) calculations. The adsorption geometries of gemcitabine drug onto the surface of nanotube are investigated for various orientation in order to attain the most stable configuration. Significant interaction is observed between the double bonded oxygen atom of the gemcitabine drug and aluminum atom of the nanocage. The charge transfer analysis indicates that there is significant interaction along with considerable charge transfer between gemcitabine and the aluminum nitrate nanotube. The electronic properties such as highest occupied molecular orbital, lowest unoccupied molecular orbitals energy levels, energy gap, chemical hardness, chemical potential, electrophilicity index, and dipole moment for the best three configurations of the complexation are examined. The recovery time calculations are also performed at 298.15 K temperature in order to study the drug desorption process on the targeted site. The stability of the complex is compared in both gas and aqueous medium. Eventually, this work interprets that aluminum nitrate nanotube can be considered to be suitable candidates for delivering gemcitabine anti-lung cancer drug in a biological system.

Comparing phase sensitive detection and Fourier analysis of modulation excitation spectroscopy data exemplified by Ambient Pressure X-ray Photoelectron Spectroscopy

Dynamic processes in catalysis are gaining increased attention and could very well be one of the next frontiers in surface science. One way to study such processes is to induce chemical changes on the surface for example by periodically adjusting the (electro)chemical potential in situ and identify the resulting spectral changes. Often this is referred to as Modulation Excitation Spectroscopy (MES). Using Ambient Pressure Photoelectron Spectroscopy data, we here discuss and compare the analysis of MES data using both Phase Sensitive Detection (PSD) and Fourier analysis. We discuss that PSD determines the component magnitude at a user-defined phase value while Fourier analysis provides the maximum oscillation amplitude and respective phase value of oscillating spectral features. We discuss advantages and disadvantages of the different analysis schemes and explore how the full time-evolution can be obtained.

An integrated In-Silico-In-Chemico-In-Vitro (iSiCiV) Approach to identify biomarkers to predict the skin sensitisation potential of phytochemicals

BackgroundSkin sensitisation is one of the important regulatory endpoints used to determine whether a given test chemical can elicit an allergic response in susceptible individuals. The in-vitro approaches for predicting skin sensitisation potential for chemicals have been well-developed and widely accepted. Continuous efforts are being made to identify novel solutions to overcome the limitations of the existing approaches. PurposeThe herbal preparations used in dermal therapeutics are frequently found to elicit skin sensitisation, requiring caution. The herbal preparations tend to contain more than one phytochemical. The expected active ingredient may not possess skin sensitisation. However, the other phytochemical traces could pose synergistic and potentiating effects towards enhanced/suppressed skin sensitisation. In this regard, isolation, purification, yield, and in-vitro / in-vivo evaluation of skin sensitisation for all the traces would be time, cost, and animal-consuming. Hence, the regulatory agencies appreciate using computational tools to substantiate in-vitro methods. The regulators have also endorsed using in-silico approaches like quantitative structure-activity relationships (QSAR) and read-across. These approaches are limited to structure-based predictions and in combination with system-level approaches, which comprehensively facilitate a better understanding of complex biological systems. Study designIn the present study, 603 phytochemicals were screened in-silico using OECD QSAR Toolbox. The limitations of the QSAR Toolbox in predicting skin sensitisers were identified. MethodThe systems biology-based approach to complement the QSAR-based prediction was developed, and 41 biomarkers were identified as a determinant of skin sensitisation. The molecules attributed to these biomarkers were predicted as skin sensitisers. ResultsAs a result, 31 phytochemicals were predicted as skin sensitisers. Acrolein, eugenol, formaldehyde, and glycerol were selected for experimental validation of the in-silico predictions using direct peptide reactivity assay (DPRA), KeratinoSens™, and h-CLAT assays representing each key event in skin sensitisation. Further, identified biomarkers were validated in THP-1 and KeratinoSens cell lines using qRT-PCR. Among all genes, IL-8 and CCL4 were upregulated by 6.4 and 5.6 folds, respectively, in THP-1, while AKR1C2 and AKR1C3 were upregulated by 7.8 and 11.1 folds, respectively, in KeratinoSens. IL-8 level was analysed by ELISA and found to be in line with qRT-PCR results. ConclusionThe study proposes a possible strategy based on the “iSiCiV” approach to enhance the prediction of the dermal sensitisation potential of a test compound. The approach offers a robust platform and highlights an opportunity to shift the paradigm of skin sensitisation assay with a better understanding of toxicology mechanisms.

Depletion forces beyond the diluted limit

The determination of the effective interactions in many-body systems still possesses a tremendous challenge in Condensed Matter Physics. The problem mainly resides in the fact that, on the one hand, there is not a unique route to obtain the effective forces between the ”observable” constituents and, on the other hand, one typically considers that the diluted limit of those components always corresponds to the effective forces at all particle concentrations. In the particular case of colloidal dispersions, it is very important to have experimental, theoretical, and computational tools that allow us to determine, accurately and without using significant approximations, the effective interactions between colloids. In this contribution, we report on a detailed study of depletion potentials in colloidal mixtures at finite concentration, namely, binary and ternary mixtures of disks (in two dimensions or 2D) and spheres (in three dimensions or 3D). To this end, the depletion forces between the large colloidal species are determined through a recently developed scheme based on the so-called contraction of the description, which has been extended and built at the level of the bare forces, i.e., we basically consider that all particles interact through the bare potentials and the net force acting on a given particle is determined by the second’s Newton law. This scheme can be easily adapted to Molecular Dynamics simulations. To verify the physical consistency of the formalism, we explicitly show that in the diluted limit of large particles, the resulting depletion potential reproduces correctly the AO-Vrij limit. As further proof of the accuracy of the results, a comparison of the structure of the large colloids in the whole mixture with the one that results using exclusively the depletion potential is carried out. In 3D, the results are explicitly compared with the potential of mean force and those obtained with the integral equations formalism. We also report a new colloidal stability mechanism based on the use of two different species of depletant agents at low and equal concentrations. Although we highlight the fact that the depletion potential depends on the concentration of the large species, we show that this dependence can be eliminated when the colloidal dispersion is open to a reservoir of small particles, i.e., when the chemical potential of small particles is fixed. Finally, we report the effects of polydispersity on the depletion interaction between large colloids.

Equation of state of the relativistic electron–positron–photon plasma at arbitrary temperature and degeneracy

We consider the plasma made of relativistic electrons and positrons in thermodynamic equilibrium with photons at arbitrary temperature and degeneracy. We establish various thermodynamic identities as a function of the electron and positron chemical potentials and temperature. The high-temperature regime in which the electrons and positrons are ultrarelativistic is recovered. The excess of electrons with respect to positrons or the excess of positrons with respect to electrons depends on the thermodynamic conditions. Doing so, we go beyond what is usually found in the literature where only the high temperature regime is usually tackled.

Water vapor corrosion behavior of SiC-Al40Y ceramics fabricated by reactive melt infiltration and thermal diffusion

The corrosion resistance of Y-Al diffused SiC ceramics (SiC-Al40Y) at 1100-1300 °C was investigated. The results show that the weight gain curves comply with the parabolic fitting formula, then the oxidation rate constant and the activation energy were calculated to be 1.653×10-5 (1100 °C), 3.704×10-5 (1200 °C), 9.306×10-5 (1300 °C) mg2/cm4s and 154.7 kJ/mol. Compared with reported SiC (41-147 kJ/mol), the higher activation energy indicates the better corrosion-resistant performance. And it is found that the Y-Al diffusion layers can be transformed to corrosion-resistant YAlSixOy layers under corrosive atmosphere. Eventually, based on experimental results, the corrosion-resistant mechanism is analyzed: chemical potential gradient caused by preferential oxidation of Y-Al prompts the immigration of Y-Al from matrix to surface, gradually forming a continuous Y/Al-silicate layer on the surface and thus can hinder the further corrosion of H2O, O2.

Theoretical investigation of graphdiyne-supported single-cluster catalysts for electroreduction of nitric oxide

The electrochemical NO reduction reaction (NORR) to NH3 offers an efficient, environmentally friendly strategy for NO removal and NH3 production, but developing effective catalysts to facilitate the conversion of NO into NH3 remains a challenge. Single-cluster catalysts (SCCs) with multi-metallic sites show promise due to the synergistic interactions among the active atoms. Herein, utilizing density functional theory (DFT) and grand-canonical DFT (GC-DFT), we systematically investigated the potential of late transition metal (TM = Fe, Co, Ni, Cu, Ru, Rh, Pd, Pt) clusters on graphdiyne (TMx/GDY, x = 1–5) for NORR. Ni3/GDY, Pd3/GDY, and Pt3/GDY emerged as the most promising candidates, demonstrating stability, excellent NORR activity, and HER suppression. Their outstanding performance is attributed to the moderate adsorption of NO, with the dxz/dyz orbitals playing a key role in NO activation. GC-DFT results highlight nonlinear variation of intermediate grand free energies with the applied potential. Detailed electronic property analyses were conducted to reveal the charge effects induced by the applied chemical potential. This study provides valuable insights into SCC-catalyzed NO reduction and highlights the significance of potential effects in theoretical simulations of electrochemical systems.

Strangeness-correlations on the pseudocritical line in ( 2+1 )-flavor QCD

We present some lattice QCD results on first (χ1i) and second (χ2i) cumulants of and correlations (χ11ij) among net baryon-number (B), strangeness (S) and electric charge (Q) along the pseudocritical line [Tpc(μB)] in the temperature (T)–baryon chemical potential (μB) phase diagram of (2+1)-flavor QCD. We point out that violations of sum rules among second order cumulants, which hold in the isospin symmetric limit of vanishing electric charge chemical potential, are small along the Tpc(μB) for the entire range of μB covered in the RHIC beam energy scan. For the strangeness neutral matter produced in heavy-ion collisions this leads to a close relation between χ11BS and χ11QS. We compare lattice QCD results for χ11BS/χ2S along the Tpc(μB) line with preliminary experimental measurements of χ11BS/χ2S for collision energies 7.7 GeV≤sNN≤62.4 GeV. While we find good agreements for sNN≥39 GeV, differences are sizeable at smaller values of sNN. Moreover, we compare lattice QCD results for the ratio of the strangeness (μS) to baryon (μB) chemical potentials, which define a strangeness neutral system with fixed electric charge to baryon number density, with experimental results obtained by the STAR collaboration for μS/μB using strange baryon yields on the freeze-out line. Finally, we determine the baryon chemical potential at the freeze-out (μBf) by comparing χ1B/χ2B along the Tpc(μB) with the experimentally measured net-proton cumulants χ1p/χ2p. We find that {μBf,Tpc(μBf)} are consistent with the freeze-out parameters of the statistical-model fits to experimentally measured hadron yields for sNN≥11.5 GeV. Published by the American Physical Society 2024

Charged AdS black holes with higher derivative corrections in the presence of string cloud

We have obtained charged asymptotically anti-de Sitter (AdS) black hole solutions in Einstein–Gauss–Bonnet gravity in the presence of string cloud. It turns out that there exist three black holes in certain range of parameters for small enough chemical potential. However, for large chemical potential, these black holes merge into a single one. The free energy of the black holes is computed from the on-shell Euclidean action by subtracting the contribution of an extremal black hole. We have studied the free energy and specific heat of the solutions, which shows that the medium-sized black hole is unstable. As an application, we have studied the quark–antiquark potential in the dual gauge theory. This study provides necessary ingredients for the study of the dual theories in the context of condensed matter systems.

A comprehensive review on chemical and pharmacological potential of Synsepalum dulcificum (Schumach. & Thonn.) Daniell

The fruit of plant Synsepalum dulcificum(Schumach. & Thonn.) Daniell, is found native to tropical regions of West Africa, and vernacularly recognized as the “Miracle Fruit” by Africans. The property of the plant has traditionally been employed in many food industries, besides its ethnopharmacological significance. The phytochemical analysis from literature reveals that various parts of plant contains many bioactive components including alkaloids, lignans, phenolic acids, glycoproteins and flavonoids. Recent studies exhibit its pharmacologicalpotential such as antidiabetic, antihyperlipidemic, anti-cancer, antimicrobial, antioxidant, anti-hyperuricemia and anti-convulsant properties. Therefore, this review aims to systematically summarizes scientific evidences with the therapeutic, ethnopharmacological and traditional claims found in literature. However, the data acquired is still very imperfect, thus future research is hopeful to discover the precise mechanism of action of its bioactive components to explore chemical constituents, and their nutraceutical and clinical uses of this multipurpose plant to employ its valuable effects on human beings.

Phytochemical investigation and spectral characterization of isolated compounds from Pyracantha crenulata (D. Don) M. Roem (syn. Crataegus crenulata Roxb) leaves: evaluation of antioxidant activity and molecular docking analysis

Pyracantha crenulata (D. Don) M. Roem (syn. Crataegus crenulata Roxb.) is an evergreen shrub in the Rosaceae family, notable for its chemical diversity and biological potential. This study isolates and characterises six compounds (Cc-1 to Cc-6), including four new ones, using repeated column chromatography. Structural elucidation employed IR, UV-vis, 1H and 13 C NMR, and mass spectrometry. The DPPH assay was used to test the antioxidant activity in vitro. Compounds Cc-4, Cc-2, Cc-1, and Cc-5 had IC50 values of 15.734 μg/ml, 51.422 μg/ml, 62.864 μg/ml, and 71.622 μg/ml, in that order. Quantitative phytochemical analysis revealed flavonoid content (22.81 mg/g), tannin content (385.15 mg/g), and total phenolic content (128.78 mg/g). Human cyclin-dependent kinase 2 (CDK2) (PDB ID: 1hck) docked with compound Cc-4, which demonstrated strong antioxidant activity and revealed significant non-bonding interactions. The pkCSM and SwissADME analyses suggested promising drug-like properties for Cc-4, supported by BOILED-Egg diagrams highlighting its therapeutic potential.

CSEL-BGC: A Bioinformatics Framework Integrating Machine Learning for Defining the Biosynthetic Evolutionary Landscape of Uncharacterized Antibacterial Natural Products.

The sluggish pace of new antibacterial drug development reflects a vulnerability in the face of the current severe threat posed by bacterial resistance. Microbial natural products (NPs), as a reservoir of immense chemical potential, have emerged as the most promising avenue for the discovery of next generation antibacterial agent. Directly accessing the antibacterial activity of potential products derived from biosynthetic gene clusters (BGCs) would significantly expedite the process. To tackle this issue, we propose a CSEL-BGC framework that integrates machine learning (ML) techniques. This framework involves the development of a novel cascade-stacking ensemble learning (CSEL) model and the establishment of a groundbreaking model evaluation system. Based on this framework, we predict 6,666 BGCs with antibacterial activity from 3,468 complete bacterial genomes and elucidate a biosynthetic evolutionary landscape to reveal their antibacterial potential. This provides crucial insights for interpretating the synthesis and secretion mechanisms of unknown NPs.