Pair Interactions Research Articles

Mode entanglement and isospin pairing in two-nucleon systems

Abstract In this study, we explore the entanglement and correlation in two-nucleon systems using isospin formalism. With the help of Slater decomposition, we derive analytical expressions for various entanglement measures. Specifically, we analyse the one- and two-mode entropies, mutual informations, and a basis-independent characteristic known as the one-body entanglement entropy.

To understand the impact of pairing, we consider interactions involving isovector and isoscalar L=0 pairing terms. Our findings show that certain pairing interactions can maximize one-body entanglement entropy of ground states when both total angular momentum and total isospin have zero projections.

We provide numerical examples for the sd shell and explore the mutual informations in LS coupled and jj coupled single-particle bases. We find that the shell structure and angular momentum coupling significantly impact the measures of entanglement. We outline the implications of conserving angular momentum and isospin on one-mode entropies, irrespective of particle number.

Cation-lone pair interaction in Alkali/alkaline earth metal ion-heavier borazine analogue complexes.

The present study is the first report on the formation of alkali/alkaline earth metal ion-heavier borazine analogue complexes via cation-lone pair interaction. Density functional calculations are performed in scrutinizing the complex formation between alkali (Li+, Na+, K+)/alkaline earth (Be2+, Mg2+, Ca2+) metal ions and heavier borazine analogues (HBA) viz. B3P3H6, Al3N3H6, Al3P3H6, Al3As3H6, and Ga3P3-H6. The complexes are found to be stable in gas phase with stabilization energies within the range 26.40 to 324.74 kcalmol-1. The stability can be attributed to the polarizing power of the involved metal ions. Presence of solvent phase exerted notable impact on the stability of the complexes; stability is reduced significantly with the increase in solvent polarity. The process of complexation is exothermic and spontaneous. QTAIM analysis indicated the presence of both ionic and covalent interaction between HBAs and metal ions. HOMO energy, Wiberg bond index, NCI-isosurface and RDG plot analysis revealed the major role of cation-lone pair interaction in the complexation process.

Pairing phase favored by magnetic frustration.

The interplay between magnetic frustration and pairing is investigated by adopting a BCS-like pairing mechanism on the frustrated $J_1-J_2$ Ising model on the square lattice. The ground-state and thermal phase transitions of the model are analyzed using a fermionic formulation within a cluster mean-field method. In this approach, the lattice system is divided into identical clusters, where the intracluster dynamic is exactly solved, and the intercluster interactions are replaced by self-consistent mean fields. We introduce a framework with two pairing couplings: an intracluster local coupling, $g$, which controls the electron pairing and its mobility within the clusters, and an intercluster coupling, $g'$, which adjusts the pairing mechanism between clusters. Tuning $g'/g$ allows evaluating how the pairing phase evolves from a weak pairing coupling between clusters (clustered system) to a strong one ($g' \rightarrow g$, homogeneous system). In the range $0 \le g'/g \le 1$, we find that a gradual increase in $g'/g$ favors the pairing phase and induces a change in criticality. In particular, our results reveal the presence of tricriticality for a certain range of $g'/g$. In addition, an increase in competing magnetic interactions weakens the magnetic orders, causing the pairing phase to occur at lower strengths of pairing interactions, especially when $g' = g$. Therefore, our findings support that magnetic frustration favors the pairing phase, contributing to the onset of a superconducting state.

Self-Generated Ions Modify the Pair Interaction and the Phase Separation of Chemically Active Colloids.

Chemically active colloids that release/consume ions are an important class of active matter, and exhibit interesting collective behaviors such as phase separation, swarming, and waves. Key to these behaviors is the pair-wise interactions mediated by the concentration gradient of self-generated ions. This interaction is often simplified as a pair-wise force decaying at 1/r2, where r is the interparticle distance. Here, we show that this simplification fails for isotropic and immotile active colloids with net ion production, such as Ag colloids in H2O2. Specifically, the production of ions on the surface of the Ag colloids increases the local ion concentration, c, and attenuates the pair-wise interaction force that scales with ∇c/c. As a result, the attractive force between an Ag colloid and its neighbor (active or passive) decays at 1/r or 1/r2 for small or large r, respectively. In a population, the attraction of a colloid by a growing cluster also scales with ∇c/c, so that medium-sized clusters grow fastest, and that the cluster coarsening slows with time. These results, supported by finite element and Brownian dynamic simulations, highlight the important role of self-generated ions in shaping the collective behavior of chemically active colloids.

Fluids with power-law repulsion: Hyperuniformity and energy fluctuations.

We revisit the equilibrium statistical mechanics of a classical fluid of point-like particles with repulsive power-law pair interactions, focusing on density and energy fluctuations at finite temperature. Such long-range interactions, decaying with inter-particle distance $r$ as $1/r^s$ in $d$ dimensions, are known to fall into two qualitatively different categories. For $s<d$ (``strongly" long-range interactions) there are screening of correlations and suppression of large-wavelength density fluctuations (hyperuniformity). These effects eliminate density modes with arbitrarily large energy. For $s>d$ (``weakly" long-range interactions) screening and hyperuniformity do not occur. Using scaling arguments, variational analysis, and Monte Carlo simulations, we find another qualitative distinction. For $s\geq d/2$ the strong repulsion at short distances leads to enhanced small-wavelength density fluctuations, decorrelating particle positions. This prevents indefinitely negative entropy and large energy fluctuations. The distinct behaviors for $s\geq d/2$ and $s<d/2$ give rise to qualitatively different dependencies of the entropy, heat capacity, and energy fluctuations on temperature and density. We investigate the effect of introducing an upper cutoff distance in the pair-potential. The effect of the cutoff on energy fluctuations is strong for $s<d/2$ and negligible for $s \geq d/2$.

Infinitely rugged intra-cage potential energy landscape in metallic glasses caused by many-body interaction

The absence of translational symmetry in glassy materials poses a significant challenge in establishing effective structure-property relationships in real space. Consequently, the potential energy landscape (PEL) in phase space is widely utilized to comprehend the complex phenomena in glasses. The classical PEL features a two-scale profile comprising mega-basins and sub-basins, corresponding to α-relaxations (e.g. glass transition) and β-relaxations (e.g. local cage-breaking atomic rearrangements), respectively. Recent studies, however, reveal that sub-basins are not smooth and contain finer structures, the origins of which remain elusive. Here we probe the smoothness of sub-basin bottoms in glasses' PEL by introducing small intra-cage cyclic loading and then measuring the net changes in atomic-level stresses. Compared to glasses with pair interaction, glasses with many-body interaction exhibit orders-of-magnitude larger and loading-dependent stress changes even before the first cage-breaking event takes place, which reflect much more feature-rich sub-basins. We further demonstrate this stark contrast stems from the spatial distribution of individual atom's constraining force field. Specifically, at vanishing perturbations, many-body interactions disrupt the positive-definite synchrony in energy variations of the perturbed atom and the whole system, causing inherently less confined atomic responses and infinitely rugged sub-basins. The implications of these findings for the selective addition or removal of fine structures in the PEL and the subsequent tuning of glassy materials' responses to external stimuli are also explored.

NFSA-DTI: A Novel Drug-Target Interaction Prediction Model Using Neural Fingerprint and Self-Attention Mechanism.

Existing deep learning methods have shown outstanding performance in predicting drug-target interactions. However, they still have limitations: (1) the over-reliance on locally extracted features by some single encoders, with insufficient consideration of global features, and (2) the inadequate modeling and learning of local crucial interaction sites in drug-target interaction pairs. In this study, we propose a novel drug-target interaction prediction model called the Neural Fingerprint and Self-Attention Mechanism (NFSA-DTI), which effectively integrates the local information of drug molecules and target sequences with their respective global features. The neural fingerprint method is used in this model to extract global features of drug molecules, while the self-attention mechanism is utilized to enhance CNN's capability in capturing the long-distance dependencies between the subsequences in the target amino acid sequence. In the feature fusion module, we improve the bilinear attention network by incorporating attention pooling, which enhances the model's ability to learn local crucial interaction sites in the drug-target pair. The experimental results on three benchmark datasets demonstrated that NFSA-DTI outperformed all baseline models in predictive performance. Furthermore, case studies illustrated that our model could provide valuable insights for drug discovery. Moreover, our model offers molecular-level interpretations.

Characterization of the regulatory network and pathways in duodenum affecting chicken abdominal fat deposition

The excessive accumulation of abdominal fat in chickens has resulted in a reduction in both the feed conversion efficiency and the slaughter yield. To elucidate the regulatory mechanisms and metabolic pathways affecting abdominal fat deposition in the context of broiler breeding, a cohort of 400 Qingyuan partridge chickens with varying abdominal fat deposition was established. Whole transcriptome sequencing analyses were conducted on the duodenum of 20 representative chickens to ascertain the regulatory networks at this vital digestive and absorptive organ. Consequently, 116 differentially expressed genes were identified, exhibiting a trend of increasing or decreasing expression in correlation with the accumulation of abdominal fat. A total of 36 DEmRNAs, 170 DElncRNAs, 92 DEcircRNAs and 88 DEmiRNAs were identified as differentially expressed between chickens with extremely high and low abdominal fat deposition. The functional enrichment analyses demonstrated that the differentially expressed RNA in the duodenum were involved in the regulation of chicken abdominal fat deposition by mediating a series of metabolic pathways, including the Wnt signaling pathway, the PPAR signaling pathway, the Hippo signaling pathway, the FoxO signaling pathway, the MAPK signaling pathway and other signaling pathways that are involved in fatty acid metabolism and degradation. The construction of putative interaction pairs led to the suggestion of two lncRNA-miRNA-mRNA ceRNA networks comprising two mRNAs, two miRNAs, and 29 lncRNAs, as well as two circRNA-lncRNA-miRNA-mRNA ceRNA networks comprising 26 mRNAs, 12 miRNAs, 17 lncRNAs, and nine circRNAs, as core regulatory networks in the duodenum affecting chicken abdominal fat deposition. The aforementioned genes including TMEM150C, REXO1, PIK3C2G, ppp1cb, PARP12, SERPINE2, LRAT, CYP1A1, INSR and APOA4, were proposed as candidate genes, while the miRNAs, including miR-107-y, miR-22-y, miR-25-y, miR-2404-x and miR-16-x, as well as lncRNAs such as ENSGALT00000100291, TCONS_00063508, TCONS_00061201 and TCONS_00079402 were the candidate regulators associated with chicken abdominal fat deposition. The findings of this study provide a theoretical foundation for the molecular mechanisms of mRNAs and non-coding RNAs in duodenal tissues on abdominal fat deposition in chickens.

Targeted Analysis of Mitochondrial Protein Conformations and Interactions by Endogenous ROS-Triggered Cross-Linker Release.

The study of in situ conformations and interactions of mitochondrial proteins plays a crucial role in understanding their biological functions. Current chemical cross-linking mass spectrometry (CX-MS) has difficulty in achieving in-depth analysis of mitochondrial proteins for cells without genetic modification. Herein, this work develops the reactive oxygen species (ROS)-responsive cross-linker delivery nanoparticles (R-CDNP) targeting mitochondria. R-CDNP contains mitochondria-targeting module triphenylphosphine, ROS-responsive module thioketal, loading module poly(lactic-co-glycolic acid) (PLGA), and polyethylene glycol (PEG), and cross-linker module disuccinimidyl suberate (DSS). After targeting mitochondria, ROS-triggered cross-linker release improves the cross-linking coverage of mitochondria in situ. In total, this work identifies 2103 cross-linked sites of 572 mitochondrial proteins in HepG2 cells. 1718 intra-links reveal dynamic conformations involving chaperones with ATP-dependent conformation cycles, and 385 inter-links reveal dynamic interactions involving OXPHOS complexes and 27 pairs of possible potential interactions. These results signify that R-CDNP can achieve dynamic conformation and interaction analysis of mitochondrial proteins in living cells, thereby contributing to a better understanding of their biological functions.

Bounds on the superconducting transition temperature

I summarize recent progress on obtaining rigorous upper bounds on superconducting transition temperature [Formula: see text] in two dimensions independent of pairing mechanism or interaction strength. These results are derived by finding a general upper bound for the superfluid stiffness for a multi-band system with arbitrary interactions, with the only assumption that the external vector potential couples to the kinetic energy and not to the interactions. This bound is then combined with the universal relation between the superfluid stiffness and the Berezinskii–Kosterlitz–Thouless [Formula: see text] in 2D. For parabolic dispersion, one obtains the simple result that [Formula: see text], which has been tested in recent experiments. More generally, the bounds are expressed in terms of the optical spectral weight and lead to stringent constraints for the [Formula: see text] of low-density, strongly correlated superconductors. Results for [Formula: see text] bounds for models of flat-band superconductors, where the kinetic energy vanishes and the vector potential must couple to interactions, are briefly summarized. Upper bounds on [Formula: see text] in 3D remains an open problem, and I describe how questions of universality underlie the challenges in 3D.

Quantum chemical calculation dataset for representative protein folds by the fragment molecular orbital method

The function of a biomacromolecule is not only determined by its three-dimensional structure but also by its electronic state. Quantum chemical calculations are promising non-empirical methods available for determining the electronic state of a given structure. In this study, we used the fragment molecular orbital (FMO) method, which applies to biopolymers such as proteins, to provide physicochemical property values on representative structures in the SCOP2 database of protein families, a subset of the Protein Data Bank. Our dataset was constructed by over 5,000 protein structures, including over 200 million inter-fragment interaction energies (IFIEs) and their energy components obtained by pair interaction energy decomposition analysis (PIEDA) using FMO-MP2/6-31 G*. Moreover, three basis sets, 6-31 G*, 6-31 G**, and cc-pVDZ, were used for the FMO calculations of each structure, making it possible to compare the energies obtained with different basis functions for the same fragment pair. The total data size is approximately 6.7 GB. Our dataset will be useful for functional analyses and machine learning based on the physicochemical property values of proteins.

Thermodynamics and kinetics of long-range ordering in FCC Ni–33at.%Cr alloys: Insights from atomic scale modeling

This study investigates the thermodynamics and kinetics of the NiCr system, focusing specifically on the kinetics of the order–disorder phase transformation in the Ni–33at.%Cr alloy. Combining density functional theory, CALPHAD-type models, and experimental diffusion data, we introduce and validate an efficient pair interaction model (PIM) and use it in Monte Carlo simulations. Our results include a detailed phase diagram of NiCr in face-centered cubic structure and kinetic models that delineate the behavior of solid solutions at high temperatures and ordered structures at low temperatures. The simulations shed light on tracer diffusion and ordering kinetics within Ni–33at.%Cr, demonstrating good agreement with existing experimental data. Furthermore, our simulation-driven insights prompt a reevaluation of certain aspects of related experimental studies concerning the apparent ordering activation enthalpies and growth kinetics. We also provide a thorough discussion on the strengths of our models and features for future improvement.

Construction of competitive endogenous RNA network and identification of potential regulatory axis in vascular calcification.

Competitive endogenous RNAs (ceRNA) theory has been proved in numerous biological processes. Nevertheless, there is a lack of research applying the ceRNA theory to the study of vascular calcification (VC) in chronic kidney diseases (CKD). In the present study, a ceRNA network was constructed after conducting transcriptome sequencing of differentially expressed genes, followed by experimental validation to identify a new target for the diagnosis and treatment of vascular calcification. Total RNA was extracted from β-glycerophosphate (β-GP) cultured vascular smooth muscle cells (VSMCs) on Day 7. Illumina HiSeq platform was utilized to build sequencing libraries. GO and KEGG analysis was conducted to identify the function of the differentially expressed genes. Protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. A ceRNA network was established based on TargetScan, miRDB, miRWALK, and miRanda database. Western blot and qRT-PCR were used to explore the expression level of protein and RNA, respectively. The direct binding sites were confirmed by dual-luciferase reporter assay. In total, 647 differentially expressed lncRNAs and 289 differentially expressed mRNAs were identified (|log2FC| ≥ 1, p < .05). The function of differentially expressed mRNAs was mainly enriched in negative regulation of osteoblast differentiation, regulation of RNA metabolic process, and other typical pathways. The ceRNA network was generated with a total of 107 interaction pairs. The lncRNA Prrc2c/miR-145-5p/Smad3 axis was considered a potential regulatory pathway within the ceRNA network. The regulatory relationship and targets of this ceRNA axis were validated via invitro experiments. For the first time, we found that lncRNA Prrc2c was highly expressed and promoted calcification of VSMCs. Luciferase reporter assay showed that lncRNA Prrc2c could bind miR-145-5p at site 1755-1761. Similarly, luciferase reporter assay showed that miR-145-5p inhibited Smad3 expression by binding to its 3'UTR. Our findings provide a comprehensive examination of the ceRNA networks in vascular smooth muscle cells (VSMCs) treated with high phosphorate. Specifically, we have identified the role of lncRNA Prrc2c in promoting VSMC calcification through the miR-145-5p/Smad3 axis.

Simplify to the Limit! Embedding-less Graph Collaborative Filtering for Recommender Systems

The tremendous positive driving effect of Graph Convolutional Network (GCN) and Graph Contrastive Learning (GCL) for recommender systems has become a consensus. GCN encoders are extensively used in recommendation models for capturing high-order connectivities between users and items, whereas GCL accelerates the training of recommendation tasks by adding extra supervision signals from contrastive objectives. However, little attention has been paid on corresponding theories that are truly tailored to recommendation tasks. From the technical perspective, Collaborative Filtering (CF) is seen as an important factor in recommender systems. It is applied to measure user-user, item-item, and user-item similarities rather than to achieve better clustering or node classification results. Besides, heuristic-based data augmentation may not be hold true in the field of recommender systems as it requires additional training costs and introduces noises that will corrupt the interaction graph structure and the semantic information of nodes. To tackle these limitations, we propose a novel Embedding-less Graph Collaborative Filtering (EGCF) for recommendation, which is tailor-made for the problem mentioned for CF and further simplifies existing solutions. Structurally, it consists of two parts: embedding-less GCN and embedding-less GCL. The former improves user-item affinity by streamlining user-type embeddings and carrying out iterative graph convolution. And the latter utilizes three-type contrastive objectives to directly measure the alignment and the uniformity of users, items, and interaction pairs, respectively, avoiding any type of data augmentation or multi-view construction. Even though EGCF has been extremely streamlined, extensive experimental results on three classical datasets demonstrate the effectiveness of EGCF in terms of recommendation accuracy and training efficiency. The code and used datasets are released at https://github.com/BlueGhostYi/ID-GRec.

Cation-Specific interfacial behavior in organic electrolytes for enhanced energy storage

Energy storage systems such as electrical double-layer capacitors have achieved significant attention due to their high power density and cyclability, attained through charge accumulation at the electrode interfaces. Organic electrolytes are widely investigated for energy storage applications owing to their broad potential windows and high specific energy. In this study, we employed constant potential molecular dynamics simulations at various applied potential differences from 0.0 V to 4.0 V to investigate the interfacial structure between organic electrolytes and graphene electrodes. The electrolytes consisted of propylene carbonate (PC) as the solvent, various cations (Li+, Na+, and K+), and bis(trifluoromethanesulfonyl)imide (TFSI−) as the anion. We observed significant structural reorientation of the PC solvent near the electrode surface under high applied potentials, which altered the K+ layer position near the cathode surface and influenced the capacitive behavior of the system. Additionally, K+ ions exhibited a high desolvation rate, lower ion pair interactions, and faster diffusion capabilities compared to Li+ and Na+ ions. These insights are crucial for advancing the understanding and development of organic electrolyte-based metal ion energy storage systems.

Topological features of trajectories of virtual photons and their effective interaction under multiple scattering in a system of conductive nanoparticles

It is shown that in conditions of strong light localization in a system of Rayleigh's resonance scatterers, effective photon–photon interaction appears. This interaction is associated with neither nonlinearity of medium nor nonlocal interaction of polarization-entangled photon pairs. It is related to complex topology of photon trajectories due to multiple scattering. Because of this interaction, acts of simultaneous elastic scattering of pair of photons in the considered system cease to be independent processes. The differential cross section of this cooperative process contains only an extra degree of small Rayleigh's factor in comparison with the classical scattering cross section of a single photon. This opens up the possibility of control of light fluxes by means of alternative low-intensity light fluxes without using slow optoelectronic converters. Light localization that provides the effective photon–photon interaction is considered in the framework of a new formalism different from traditional one. Equation of the Bethe–Salpeter for two-photon propagator is resolved directly in coordinate representation without traditional reducing of this equation to some transport equation. This allows in a new light to look on reason of weak light localization and to show that weak localization is one of consequences of strong localization.

Synergistic effect of ceramic filler in polymer salt complex for improved ion dissociation and migration mechanism

Abstract Use of Ceramic filler is one of the most common approaches to improve the conductivity and stability properties of a solid polymer electrolyte (SPE) cum separator. Among them, active fillers like Garnet have been extensively used to enhance the stability and conductivity of SPE. However, SPE suffers from limited ion migration at room temperature acting as a bottleneck for their application in all solid-state batteries. An extensive study on these fillers' role in ion dissociation and migration can be a stepping stone for advanced SPE. In the present work, an FTIR analysis has primarily been used to identify and evaluate cation coordinate site-cation, and ion pair interactions in a Li6.5La3Zr1.75Te0.25O12 loaded polyethylene oxide-LiCF3SO3 matrix with varying ceramic concentrations. Further, the Trukhan model has been used to calculate diffusion coefficient, mobility, and charge carrier density to interpret relaxation parameters, conductivity, and FTIR results in the SPE samples. Finally, an ion migration model has been proposed based on the results obtained in experimental studies.&amp;#xD;

Exposure to Lead (Pb) influences the outcomes of male-male competition during precopulatory intrasexual selection

Male-male competition is a component of Darwin’s theory of precopulatory intrasexual selection, where males compete for access to resources important for reproduction and successful males pass on traits that endow greater competitive ability to their offspring, thereby exaggerating the trait(s) over evolutionary time. Metals, such as lead (Pb) often occur in urban mangrove forests, where shore crabs reside, and being neurotoxic may cause sub-lethal effects on behaviour. In this study, we asked whether exposure to Pb influences the outcomes of male-male competition in the Semaphore crab, Heloecius cordiformis, thereby altering outcomes of intrasexual selection. Crabs were exposed to an environmentally relevant, and a behaviourally relevant, concentration of lead (i.e. Pb, 10 µg/L and 100 µg/L respectively) under laboratory conditions for 96 h and subsequently allowed to compete for burrow ownership in experimental arenas. Exposed crabs (100 µg/L) were less successful than control crabs in chela size-matched paired competitive interactions, spent less time in burrows and predominantly lost burrow ownership. Further, exposure to Pb contamination (both 10 µg/L and 100 µg/L) negated the chela size advantage in size-asymmetric competitive interactions. This contaminant-induced loss of size-related competitive advantage may result in relaxation in selection pressure on body size and smaller male carapace widths and especially male chela lengths in contaminated locations. Assessment of a range of locations in the wild found a consistent pattern of metal-associated size declines in more contaminated locations for males, but not for females.

Unconventional pairing in Ising superconductors: application to monolayer NbSe2

Abstract The presence of a non-centrosymmetric crystal structure and in-plane mirror symmetry allows an Ising spin–orbit coupling to form in some two-dimensional materials. Examples include transition metal dichalcogenide superconductors like monolayer NbSe2, MoS2, TaS2, and PbTe2, where a nontrivial nature of the superconducting state is currently being explored. In this study, we develop a microscopic formalism for Ising superconductors that captures the superconducting instability arising from a momentum-dependent spin- and charge-fluctuation-mediated pairing interaction. We apply our pairing model to the electronic structure of monolayer NbSe2, where first-principles calculations reveal the presence of strong paramagnetic fluctuations. Our calculations provide a quantitative measure of the mixing between the even- and odd-parity superconducting states and its variation with Coulomb interaction. Further, numerical analysis in the presence of an external Zeeman field reveals the role of Ising spin–orbit coupling and mixing of odd-parity superconducting state in influencing the low-temperature enhancement of the critical magnetic field.

Interface Synergy of Exposed Oxygen Vacancy and Pd Lewis Acid Sites Enabling Superior Cooperative Photoredox Synthesis.

Photo-driven cross-coupling of o-arylenediamines and alcohols has emerged as an alternative for the synthesis of bio-active benzimidazoles. However, tackling the key problem related to efficient adsorption and activation of both coupling partners over photocatalysts towards activity enhancement remains a challenge. Here, we demonstrate an efficient interface synergy strategy by coupling exposed oxygen vacancies (VO) and Pd Lewis acid sites for benzimidazole and hydrogen (H2) coproduction over Pd-loaded TiO2 nanospheres with the highest photoredox activity compared to previous works so far. The results show that the introduction of VO optimizes the energy band structure and supplies coordinatively unsaturated sites for adsorbing and activating ethanol molecules, affording acetaldehyde active intermediates. Pd acts as a Lewis acid site, enhancing the adsorption of alkaline amine molecules via Lewis acid-base pair interactions and driving the condensation process. Furthermore, VO and Pd synergistically promote interfacial charge transfer and separation. This work offers new insightful guidance for the rational design of semiconductor-based photocatalysts with interface synergy at the molecular level towards the high-performance coproduction of renewable fuels and value-added feedstocks.