Increase In Entropy Research Articles

Determination of Propagation Rate Coefficients of 2‐Hydroxyethyl Methacrylate in Aqueous Solution

AbstractMechanistic understanding of free radical polymerization (FRP) in aqueous solution is hindered by the lack of kinetic coefficient data. Here, we investigated the propagation rate coefficient (kp) for FRP of HEMA in aqueous solution. The kp at 80 °C increased by 6 times as the monomer weight fraction in aqueous system decreases from 100 wt.% to 6 wt.%, that is., from 6.0 × 103 to 3.3 × 104 L·moL−1·s−1. This increase in kp is associated with the increase in pre‐exponential factor (A), which suggests an increase in entropy with increasing water molecules in the polymerization system. To investigate the effect of solvent on kp, pulse‐laser polymerization in solvents of different hydrogen bonding affinity, that is, 50 wt.% butyl propionate (BP) and dimethyl formamide (DMF), are conducted. The kp obtained are in order of kp,bulk∼kp,BP > kp,DMF, suggesting that the intermolecular hydrogen bonding at carbonyl moieties critically affects the geometry of transition state quasi‐equilibrium in propagation. We underpinned this observation by analyzing the carbonyl and alkene moieties of HEMA in different solvents using infrared (IR) spectroscopy. The mechanistic analyses and insights relating to hydrogen bonding and functional moieties can be relevant for future studies involving non‐aqueous solvents promoting hydrogen bonds.

First-principles Calculation of Cumene: Molecular Structure, Electronic Structures, Spectroscopic Analysis, and Thermodynamic Properties

This study uses the DFT method for the investigation of optimized structure, electronic structures, charge analysis, FT-IR, FT-Raman spectroscopic analysis and thermodynamic properties. The optimized energy and dipole moment are 9531.775 eV and 0.3818 Debye. The bond lengths of C1-C2 and C1-H7 molecules inside the benzene ring are observed to be 1.39 Å and 1.08 Å respectively. The bond angle of C1-C2-C3 and C2-C1-C6 are found to be 120.10 Å and 119.36 Å. The HOMO-LUMO energy gap is 6.331 eV which corresponds very close to the energy gap of 6.321 eV obtained from density of states. The global parameters with ionization energy value 6.747 eV, electron affinity with 0.4152 eV, chemical potential with -3.5811 eV, electronegativity with 3.5811 eV, global hardness with 3.1659 eV, softness with 0.3148 eV-1 and electrophilicity index with 2.0253 eV are obtained. The Mulliken charges analysis indicate that most of the carbon atoms except C4 and C12 are found to carry negative charges where all of the H-atoms are found having positive charge. The molecular electrostatic potential, electrostatic potential and electron density identify different electrophilic and nucleophilic region and its reactive natures. The FT-IR spectroscopy shows strong C-H vibrations at 3186-3093 cm-1, methyl group vibration at 3091-3078 cm-1 and the ring vibrations at 1641-1482 cm-1. The heat capacity at constant volume and at constant pressure, internal energy, enthalpy, entropy increase with increasing temperature. However, Gibb’s free energy shows opposite nature providing very important insights according to the change in temperature.

SL: Stable Learning in Source-Free Domain Adaptation for Medical Image Segmentation

Deep learning techniques for medical image analysis often encounter domain shifts between source and target data. Most existing approaches focus on unsupervised domain adaptation (UDA). However, in practical applications, many source domain data are often inaccessible due to issues such as privacy concerns. For instance, data from different hospitals exhibit domain shifts due to equipment discrepancies, and data from both domains cannot be accessed simultaneously because of privacy issues. This challenge, known as source-free UDA, limits the effectiveness of previous UDA medical methods. Despite the introduction of various medical source-free unsupervised domain adaptation (MSFUDA) methods, they tend to suffer from an over-fitting problem described as “longer training, worse performance”. To address this issue, we proposed the Stable Learning (SL) strategy. SL is a method that can be integrated with other approaches and consists of weight consolidation and entropy increase. Weight consolidation helps retain domain-invariant knowledge, while entropy increase prevents over-learning. We validated our strategy through experiments on three MSFUDA methods and two public datasets. For the abdominal dataset, the application of the SL strategy enables the MSFUDA method to effectively address the domain shift issue. This results in an improvement in the Dice coefficient from 0.5167 to 0.7006 for the adaptation from CT to MRI, and from 0.6474 to 0.7188 for the adaptation from MRI to CT. The same improvement is observed with the cardiac dataset. Additionally, we conducted ablation studies on the two involved modules, and the results demonstrated the effectiveness of the SL strategy.

Impact of Quantum Non-Locality and Electronic Non-Ideality on the Shannon Entropy for Atomic States in Dense Plasma.

The influence of the collective and quantum effects on the Shannon information entropy for atomic states in dense nonideal plasma was investigated. The interaction potential, which takes into account the effect of quantum non-locality as well as electronic correlations, was used to solve the Schrödinger equation for the hydrogen atom. It is shown that taking into account ionic screening leads to an increase in entropy, while taking into account only electronic screening does not lead to significant changes.

Different Effects of Strong-Bonded Water with Different Degrees of Substitution of Sodium Sulfobutylether-β-cyclodextrin on Encapsulation.

The encapsulation of sodium sulfobutylether-β-cyclodextrin (SBE-β-CD) is influenced not only by the degree of substitution (DS) but also by the presence of strong-bonded water (SBW). Guests compete with SBW for positions within the cavity of SBE-β-CD. However, the correlation between DS and SBW was not clear. This study revealed a positive correlation between DS and SBW utilizing Karl Fischer titration. The mechanism may be attributed to molecular polarizability. To explore the impact of SBW inside SBE-β-CD with different DS on encapsulation, density functional theory was employed. Throughout the release process, an increase in enthalpy is unfavorable, while an increase in entropy favors spontaneous reaction occurrence. For SBE-β-CD (DS = 2, 3), enthalpy increase is the primary factor, leading to the retention of SBW within the cavities and consequently hindering guest entry. In contrast, for SBE-β-CD (DS = 4, 7), the situation differs. For SBE10-β-CD, the influence of SBW is minimal. This study aims to elucidate the relationship between DS and SBW, as well as the effect of SBW inside SBE-β-CD with different DS on encapsulation. It is crucial for a comprehensive understanding of the factors affecting the encapsulation of SBE-β-CD, thereby promoting quality control and functional development of SBE-β-CD.

Exploring enhanced heat transfer in wavy porous enclosures: Optimization and analysis of ternary nanofluid integration under varied boundary conditions with MHD mixed convection

This study explores the application of Al2O3-ZnO-Fe3O4/Water ternary nanofluids for enhanced thermal management in engineering applications, addressing the MHD Darcy–Forchheimer problem with an emphasis on optimizing cooling processes in a 2D-wavy cavity under various moving boundary conditions. Aimed at surpassing the limitations of conventional cooling fluids, the research employs the finite volume method within the OpenFOAM® framework to investigate the impact of nanofluid integration on heat transfer efficiency and entropy generation, utilizing partial heating and eight distinct boundary scenarios. By comparing the performance of ternary nanofluids against that of hybrid and mono nanofluids, we identify optimal conditions that significantly enhance cooling effectiveness, as evidenced by a 37% improvement in heat exchange efficiency over water. The findings demonstrate the superior performance of Al2O3-ZnO-Fe3O4/Water nanofluids in achieving higher average Nusselt numbers at low Darcy numbers, despite an increase in entropy. Optimal conditions were identified for the most favorable scenario involving the movement of cavity lids, based on the Nusselt number, specifically in Case 7 (ul1+ and ul2−). Decreasing the number of waves in the cavity enhances heat transfer and reduces irreversibility. Finally, the study shows that the influence of lid motion on skin friction significantly varies with Richardson numbers, and the use of nanofluids over pure water notably reduces skin friction.

The growth evolution of SnSe-doped SnTe alloy by in-situ selenization substitution method

In the era of increasing environmental pollution and energy crisis, the development of thermoelectric materials to achieve the reuse of waste heat energy is of great significance. SnTe, as an environmentally friendly thermoelectric material, its high electronic-thermal conductivity and coupled high electrical conductivity originated from intrinsic high carrier hole concentration leads to the unsatisfactory thermoelectric properties. With a lot of research going on to optimize thermoelectric performance by decoupling the thermo-electrical contradiction, the entropy engineering strategy, which can independently modulate lattice thermal conductivity is proved to be feasible by increasing the internal configurational entropy through doping. However, due to the uncontrollable growth microscopic process and the perturbation of film quality, the desired precise phase doping remains a challenge. In this work, we report an instantiation of the entropy increase of SnSe-doped SnTe alloy thin films prepared by two-step magnetron sputtering and selenization method. The microstructure and physical properties of thin films were investigated for replaying and controlling the growth evolution of in-situ selenization substitution. When the reaction temperature and duration were adjusted to 300℃ and 30 mins respectively, the desired pure phase doping was obtained. This work provides a new method of doping modification of SnTe materials, and the product as a new functional material expands the thermoelectric material library. In particular, it has positive reference significance for the development of synthesis controllability and structure establishment of complex polycrystalline materials.

Numerical investigation of discharge pressure effect on steam ejector performance in renewable refrigeration cycle by considering wet steam model and dry gas model

Abstract In recent times, steam ejectors have garnered significant interest among researchers due to their environmental friendliness and the utilization of low-grade energy sources. However, a key drawback of the ejector refrigeration cycle (ERC) is its relatively low coefficient of performance (COP). Understanding the behavior of ejectors under various operating conditions is crucial for addressing this concern. This study specifically focuses on investigating the flow characteristics of ejectors in the single-choking mode. Both dry steam model (DSM) and wet steam model (WSM) are employed to analyze and evaluate the performance in this study. Based on the findings, it is evident that the discharge pressure (DP) significantly influences the flow characteristics. With increasing DP, there is a decrease in the Mach number and liquid mass fraction (LMF) within the ejector, while the temperature distribution shows an upward trend. Additionally, as the DP increases, there is a notable decline in the entrainment ratio (ER) and production entropy. With an increase in the DP, both the DSM and WSM exhibit similar trends. However, in the DSM, the ER reaches zero at an earlier stage compared to the WSM. Specifically, when the DP rises from 5000 Pa to 5600 Pa, there is a 12.6 % increase in the production entropy in the WSM, while the DSM experiences a slightly higher increase of 12.9 %.

Quantitative Electroencephalography in Term Neonates During the Early Postnatal Period Across Various Sleep States.

Neonatal sleep is pivotal for their growth and development, yet manual interpretation of raw images is time-consuming and labor-intensive. Quantitative Electroencephalography (QEEG) presents significant advantages in terms of objectivity and convenience for investigating neonatal sleep patterns. However, research on the sleep patterns of healthy neonates remains scarce. This study aims to identify QEEG markers that distinguish between different neonatal sleep cycles and analyze QEEG alterations across various sleep stages in relation to postmenstrual age. From September 2023 to February 2024, full-term neonates admitted to the neonatology department at the Obstetrics and Gynecology Hospital of Fudan University were enrolled in this study. Electroencephalographic (EEG) recordings were obtained from neonates aged 37-42 weeks, within 1-7 days post-birth. The ROC curve was employed to evaluate QEEG features related to amplitude, range EEG (rEEG), spectral density, and connectivity across different sleep stages. Furthermore, regression analyses were performed to investigate the association between these QEEG characteristics and postmenstrual age. The alpha frequency band's spectral_diff_F3 emerged as the most potent discriminator between active sleep (AS) and quiet sleep (QS). In distinguishing AS from wakefulness (W), the theta frequency's spectral_diff_C4 was the most effective, whereas the delta frequency's spectral_diff_P4 excelled in differentiating QS from W. During AS and QS phases, there was a notable increase in entropy within the delta frequency band across all monitored brain regions and in the spectral relative power within the theta frequency band, correlating with postmenstrual age (PMA). Spectral difference showcases the highest discriminative capability across awake and various sleep states. The observed patterns of neonatal QEEG alterations in relation to PMA are consistent with the maturation of neonatal sleep, offering insights into the prediction and evaluation of brain development outcomes.

Hawking-Page transition on a spin chain

The accessibility of the Hawking-Page transition in AdS5 through a one-dimensional (1D) Heisenberg spin chain is demonstrated. We use the random matrix formulation of the Loschmidt echo for a set of spin chains, and randomize the ferromagnetic spin interaction. It is shown that the thermal Loschmidt echo, when averaged, detects the predicted increase in entropy across the Hawking-Page transition. This suggests that a 1D spin chain exhibits characteristics of black hole physics in 4+1 dimensions. We show that this approach is equally applicable to free fermion systems with a general dispersion relation. Published by the American Physical Society 2024

Perturbation-tuned triple spiral metamagnetism and tricritical point in kagome metal ErMn6Sn6

Kagome materials are of topical interest for their diverse quantum properties linked with correlated magnetism and topology. Here, we report anomalous hydrostatic pressure (p) effect on ErMn6Sn6 through isobaric and isothermal-isobaric magnetization measurements. Magnetic field (H) suppresses antiferromagnetic TN while simultaneously enhancing the ferrimagnetic TC by exhibiting dual metamagnetic transitions, arising from the triple-spiral-nature of Er and Mn spins. Counter-intuitively, pressure enhances both TC and TN with a growth rate of 74.4 K GPa−1 and 14.4 K GPa−1 respectively. Pressure unifies the dual metamagnetic transitions as illustrated through p-H phase diagrams at 140 and 200 K. Temperature-field-pressure (T-H, T-p) phase diagrams illustrate distinct field- and pressure-induced critical points at (Tcr = 246 K, Hcr = 23.3 kOe) and (Tcr = 435.8 K, pcr = 4.74 GPa) respectively. An unusual increase of magnetic entropy by pressure around Tcr and a putative pressure-induced tricritical point pave a unique way of tuning the magnetic properties of kagome magnets through simultaneous application of H and p.

Effects of different alkyl chain lengths on excess properties of CO2-1-Butyl-1-methyl-pyrrolidinebis(trifluoromethanesulfonyl)imide, CO2-1-hexyl-1-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide, CO2-1-octyl-1-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide systems

The study investigates the solubility of carbon dioxide (CO2) in three ionic liquids [BMP][Tf2N] (1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide), [HMP][Tf2N] (1-hexyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide) and [OMP][Tf2N] (1-octyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide). The research is conducted over a temperature range of 303.15 to 363.15 K. The phase equilibria of the binary systems are predicted using the Peng-Robinson (PR) equation of state, the Wilson (WS) mixing rule and the UNIFAC activity coefficient model. The interaction parameter kij is regressed from the vapor-liquid equilibrium (VLE) experimental data. The study also calculates the excess Gibbs free energy (GE), excess enthalpy (HE), and excess entropy (SE) for these systems. The research results indicate that the length of the alkyl chain in the cation has a significant effect on the excess properties of the CO2-ionic liquid systems. As the alkyl chain length increases, the excess Gibbs free energy and excess enthalpy decrease, while the excess entropy increases. The CO2-[OMP][Tf2N] system exhibits stronger interactions between CO2 and the ionic liquid, indicating a higher capacity for CO2 absorption. The study results are helpful for optimization of CO2 capture processes and the broader comprehension of fluid phase equilibria in complex systems.

Research on the Optimization of Digital Transformation of Social Assistance Based on Entropy Change Theory

With the development of digitalization in China, the social assistance environment has also undergone tremendous changes in the digital era, which requires social managers to achieve high-quality and efficient assistance through digital transformation. The research introduces the theory of entropy change, constructs a two-dimensional quadrant method, and demonstrates that the orderly digital transformation of social assistance is achieved by negative entropy reduction offsetting positive entropy increase. Based on the current situation and case study of the digital transformation of social assistance in China, the entropy change of social assistance system has the characteristics of variability, uncertainty and complexity. Based on these three characteristics, the optimization path of the digital transformation of the social assistance system is proposed from the perspectives of negative entropy increase and positive entropy flow.

Longitudinal detection of gait alterations associated with hypertension-induced cerebral microhemorrhages in mice: predictive role of stride length and stride time asymmetry and increased gait entropy

Cerebral microhemorrhages (CMHs) are of paramount importance as they not only signify underlying vascular pathology but also have profound implications for cognitive function and neurological health, serving as a critical indicator for the early detection and management of vascular cognitive impairment (VCI). This study aimed to investigate the effects of hypertension-induced CMHs on gait dynamics in a mouse model, focusing on the utility of advanced gait metrics as sensitive indicators of subclinical neurological alterations associated with CMHs. To induce CMHs, we employed a hypertensive mouse model, using a combination of Angiotensin II and L-NAME to elevate blood pressure, further supplemented with phenylephrine to mimic transient blood pressure fluctuations. Gait dynamics were analyzed using the CatWalk system, with emphasis on symmetry indices for Stride Length (SL), Stride Time (ST), and paw print area, as well as measures of gait entropy and regularity. The study spanned a 30-day experimental period, capturing day-to-day variations in gait parameters to assess the impact of CMHs. Temporary surges in gait asymmetry, detected as deviations from median gait metrics, suggested the occurrence of subclinical neurological signs associated with approximately 50% of all histologically verified CMHs. Our findings also demonstrated that increases in gait entropy correlated with periods of increased gait asymmetry, providing insights into the complexity of gait dynamics in response to CMHs. Significant correlations were found between SL and ST symmetry indices and between these indices and the paw print area symmetry index post-hypertension induction, indicating the interdependence of spatial and temporal aspects of gait affected by CMHs. Collectively, advanced gait metrics revealed sensitive, dynamic alterations in gait regulation associated with CMHs, resembling the temporal characteristics of transient ischemic attacks (TIAs). This underscores their potential as non-invasive indicators of subclinical neurological impacts. This study supports the use of detailed gait analysis as a valuable tool for detecting subtle neurological changes, with implications for the early diagnosis and monitoring of cerebral small vessel disease (CSVD) in clinical settings.

High-entropy perovskite quantum dots of rare earth synergy with excellent luminescence stability via high-energy ball milling

The problem of low stability and high lead content limit the commercial development of halide perovskite. In this paper, the high-energy ball milling is used to rapidly and efficiently synthesize high-entropy Cs(Pb1/5Mn1/5Ni1/5Zn1/5Yb1/5)Cl3 quantum dots (QDs), the introduction of high-entropy and rare earth ions reduces lead content, increases mixing entropy, and synergistically enhances the photoluminescence (PL) intensity and stability of QDs with other ions. Because the increase of entropy enhances the stability, the QDs still have 70 % PL intensity after 60 days of placement. After the QDs are exposed to the ultraviolet lamp for 8 hours, the PL intensity maintains at 67.1 % due to the loss of ligand. Ionic bonds are easily broken in water, so after soaking in water for 8 hours, the PL intensity of the QDs keeps at 32 %. The thermal stability of QDs is maintained well because of physical and chemical stability of rare earth ions. Since ethanol dissolves the ligands on the surface of the QDs, the non-radiative recombination is enhanced, so the PL intensity of QDs remains at 59 % after soaking for 8 hours. This paper provides a new way that further enhances the stability and solves high lead content of all-inorganic perovskite materials.

A total three-dimensional evaluation method to analyze the loss mechanism of film cooling on turbine guide vane

In view of the situation that the secondary flow in the passage deflects the coolant from film cooling holes and changes heat transfer, a total three-dimensional evaluation method is developed based on the HS1A high-pressure turbine guide vane to take a new insight into the loss mechanism. Film cooling holes are placed on the suction surface with compound angles to obtain different blade models. After satisfying the requirement of film cooling effectiveness, TTDM, a new total three-dimensional evaluation method where both mainstream and coolant are treated in three dimensions is established. Then, loss mechanism is analyzed by controlling the temperature ratio, changing the exit Mach number and blowing ratio. The entropy creation due to mixing is used as the evaluation basis to analyze different models within the high film cooling effectiveness range. It is believed that the mixing temperature and velocity need to be elaborated and distinguished in high subsonic environments. Compared with the original model within a certain range, the increase of the film cooling effectiveness can be found under the application of different compound angles in a short distance on suction surface. A slight increase of entropy is also noticed. By lessen the loss of secondary flow within a certain range of blowing ratio and exit Mach number conditions, the total loss can be reduced with reasonable setting of compound angle. Finally, the loss with film cooling is evaluated more accurately by the total three-dimensional evaluation method considering the effects of secondary flow.

Experimental study and process evaluation of coproduction graphene, acetylene and hydrogen from methane pyrolysis by thermal plasma

This paper developed a process for the coproduction of graphene, acetylene and hydrogen from methane pyrolysis by thermal plasma. Bench-scale tests under three specific energy input (SEI) were carried out to investigate the morphology of carbon nanomaterials and the product selectivity. The process was evaluated by exergy and exergoeconomic analyses. Results indicated that a higher SEI improved the selectivity of graphene nanoflakes (GNFs) and reduced their defects. The product selectivity of GNFs played a critical role in the decrease of total fuel exergy per unit of GNFs as the SEI increased. The plasma reactor exhibited the highest exergy loss ratio in the entire process due to heat dissipation. The quenching device exhibited the second-highest exergy loss ratio in the process, stemming from irreversible entropy increase causing exergy loss. Improving the design of the plasma reactor to enhance thermal efficiency and implementing a feasible waste heat recovery system were identified as effective strategies to enhance exergy efficiency. Excluding consideration of co-products, GNFs with high SEI had the lowest cost of 199.41 CNY/kg, when co-products were considered, the lowest cost decreases by 30%, and the low SEI had the lowest GNFs cost at 140.71 CNY/kg. This indicated that there was enough investment potential to tailor the properties of GNFs produced by such processes for application scenarios. The unit exergy cost of GNFs decreased from 0.89 CNY/MJ to 0.80 CNY/MJ as the SEI of the plasma reactor increased. Subsequently, it rose to 1.16 CNY/MJ. Prioritizing the increase in investment costs for the plasma reactor to reduce exergy loss costs should be considered first, and optimizing the waste heat recovery process was also a key direction to minimize exergy loss costs.

Relativistic energy spectra of diatomic molecules through the solutions of general conformable fractional (GCF) Klein-Gordon equation for Hulthen potential with position-dependent mass (PDM) and the thermodynamic properties

In this study, we investigate the thermodynamic properties of some diatomic molecules modelled by Hulthen potential with PDM. The GCF Klein-Gordon equation in the GCF cylindrical coordinate for the Hulthen potential and the PDM function is solved by using the GCF Laplace method to obtain the GCF energy equation and GCF wave function. The effect of the fractional order, quantum number, potential parameter, and PDM parameter on the energy eigenvalue of the H2, LiH, and HF diatomic molecules is discussed through the corresponding graphs computed using MATLAB software. The results show that the fractional order, quantum number, and potential parameter cause the energy spectrum to increase. In addition, the thermodynamic properties are examined by calculating the partition function. Based on the results, internal energy tends to be constant at lower temperatures, and the specific heat capacity decreases with increasing β . Whereas free energy and entropy increase monotonically with increasing β . To validate our findings, we compare our results with those obtained in the literature.

Evaluation of the effectiveness of methodological approaches to hierarchical intelligent control of ground-air Ad-Hoc communication network

The article shows the features of intelligent management processes of a new type of ground-air communication networks that are rapidly being implemented. The dynamic nature of the conditions of operation and behavior of communication nodes, both ground and air, causes a rapid increase in the volume of service information necessary to ensure continuous and adaptive management in real time. One of the ways to solve this problem is the redistribution of management tasks at different stages of the management cycle, which is classically divided into the stages of planning, deployment and operational management. On the one hand, the increase in entropy at the planning stage complicates this process, but this approach will increase the probability of making "correct" management decisions from the standpoint of quality management (network metrics). The work investigates a new architecture of a hierarchical intelligent ground-air communication network control system based on the model-free Reinforcement learning algorithm as a Q-learning network agent and FA-OSELM online sequential extreme machine learning algorithms as node-level agents. The IСS model is presented, its adequacy is checked, and the process of its learning at the planning stage on various mobility models is shown. An important feature of the IСS training process is the application of the developed mobility model, disclosed in the article, which describes the interaction processes of communication nodes at a deeper level. The work conducted a study of the representativeness of the training sample, obtained using the developed mobility model, that was carried out relative to the existing ones, and it was determined that despite the smaller volume of the population of the initial data, it was possible to ensure a better quality of resource management.

Structural, spectroscopic (FTIR, FT-Raman and UV–Vis) investigations, Fukui function analysis and thermodynamic properties of diethyl 3,3′-(ethane-1,2-diylbis(azanediyl))(2Z,2′Z)-bis(but-2-enoate)

Diethyl 3,3′-(ethane-1,2-diylbis(azanediyl))(2Z,2′Z)-bis(but‑2-enoate) (DBE) molecule is characterized by infrared, Raman and UV–visible spectroscopic techniques. The structural parameters obtained using density functional theory (DFT) with B3LYP/6-311++G(d,p) level of theory closely match the experimental data. The molecule's characteristic functional groups were identified through vibrational spectra analysis. The IR and Raman spectra vibrational peaks were assigned based on Potential Energy Distribution (PED) analysis. Excitation wavelengths, oscillator strengths and excitation energies were determined through time dependent density functional theory (TD-DFT) calculations and compared to experimental data. Nonlinear optical (NLO) properties were calculated to predict the electric dipole moment and first-order hyperpolarizability of the molecule. The significant nonlinear optical properties values indicated that these materials possess excellent nonlinear optical properties, making them suitable for applications in telecommunication and signal processing. The Mulliken atomic charge, chemical activity analysis and Fukui functions were utilized to investigate the electron-poor, rich and reactive sites in conjunction with the optimized structures using the DFT method with B3LYP function and 6-311++G(d,p) basis set. Thermodynamic investigations have shown that key molecular parameters such as entropy, heat capacity and enthalpy increase as temperature rises.