Density Functional Theory Research Articles

Synthesis, Crystal Structure, Spectroscopic Characterization, In Vitro and In Silico Molecular Docking Studies of Benzyl Tetrazole-N-Isobutyl Acetamide Hybrid

Background: Tetrazole-based compounds are of significant interest due to their potential pharmacological applications. The current study focuses on the synthesis and analysis of such a compound. Objective: This research aims to synthesize the title compound N-(3-methyl-1-phenyl-2-(1Htetrazol- 1-yl) butyl) acetamide, analyze its crystal structure, perform computational studies, and evaluate its potential pharmacological activities and it’s in silico and in vitro supports, specifically antidiabetic and anti-inflammatory properties. Methods: The title compound, C14H19N5O, was synthesized, and its crystal structure was confirmed using single-crystal X-ray diffraction analysis by default parameters. Density Functional Theory (DFT) calculations were performed using the Gaussian 09W software package with the B3LYP/6-311++G (d,p) method to optimize the compound's structure and calculate its HOMOLUMO energy gap, Molecular Electrostatic Potential (MEP), and Mulliken charge distribution. In vitro, antidiabetic and anti-inflammatory activities were assessed and compared with standard drugs by using reported protocols. Additionally, molecular docking studies were conducted with enzymes related to diabetes and inflammation with default parameters, and Auto-Dock 4.2 software was used. Results: The X-ray diffraction analysis confirmed the crystal structure, and the Density Functional Theory (DFT) calculations provided insights into the molecular properties of the compound. Molecular docking experiments with relevant enzymes further supported the significant antidiabetic and anti-inflammatory activities demonstrated in the in vitro tests. Conclusion: The synthesized tetrazole-based compound exhibits promising antidiabetic and antiinflammatory activities, supported by both experimental and theoretical studies, suggesting its potential for further pharmacological investigation.

Benchmark Investigation of SCC-DFTB Against Standard DFT to Model Phononic Properties in Two-Dimensional MOFs for Thermoelectric Applications.

Despite the importance of modeling lattice thermal conductivity in predicting thermoelectric (TE) properties, computational data on heat transport, especially from first-principles, in 2D metal-organic frameworks (MOFs) remain limited due to the high computational cost. To address this, we provide a benchmark of the performance of semiempirical self-consistent-charge density functional tight-binding (SCC-DFTB) methods against density functional theory (DFT) for monolayer, serrated, AA-stacked and/or AB-stacked Zn3C6O6, Cd3C6O6, Zn-NH-MOF, and Ni3(HITP)2 MOFs. Harmonic lattice dynamics calculations, including partial atomic contributions to phonon dispersions, are evaluated with both SCC-DFTB and DFT, whereas anharmonic transport (i.e., thermal conductivity) is evaluated with SCC-DFTB only. Our findings further suggest that unlike the other stacking geometries modeled, serrated Zn3C6O6, serrated Zn-NH-MOF, and wavy serrated Ni3(HITP)2 represent stable geometries. While Zn3C6O6 and Zn-NH-MOF exhibit a higher power factor than Ni3(HITP)2 (as found in our previous work), Zn-NH-MOF shows lower thermal conductivity, resulting in the highest thermoelectric figure of merit (ZT) among the studied MOFs.

Extending GPU-accelerated Gaussian integrals in the TeraChem software package to f type orbitals: Implementation and applications.

The increasing availability of graphics processing units (GPUs) for scientific computing has prompted interest in accelerating quantum chemical calculations through their use. However, the complexity of integral kernels for high angular momentum basis functions often limits the utility of GPU implementations with large basis sets or for metal containing systems. In this work, we report the implementation of f function support in the GPU-accelerated TeraChem software package through the development of efficient kernels for the evaluation of Hamiltonian integrals. The high efficiency of the resulting code is demonstrated through density functional theory (DFT) calculations on increasingly large organic molecules and transition metal complexes, as well as coupled cluster singles and doubles calculations on water clusters. Preliminary investigations into Ni(I) catalysis with DFT and the photochemistry of MnH(CH3) with complete active space self-consistent field are also carried out. Overall, our GPU-accelerated software appears to be well-suited for fast simulation of large transition metal containing systems, as well as organic molecules.

A Case Study of an Energy Barrier in Li-Ion Battery Cathode Material Using DFT and Post-HF Approaches.

With the ever-increasing interest toward energy storage materials, an accurate understanding of the underlying physicochemical processes becomes mandatory for enabling accurate and predictive simulations. In this study, we apply multilevel quantum chemical calculations on a benchmark material commonly adopted as a cathode in Lithium batteries, Li0.5Co0.5+3Ni0.5+4O2. We estimate the Lithium hopping barrier, a key quantity for the estimate of Li diffusion coefficient, at different levels: Hartree-Fock (HF), density functional theory (DFT), periodic local Møller-Plesset perturbation theory of second order, complemented with a coupled cluster correction evaluated using an embedded-fragment approach. The post-HF methods were used here not only for benchmarking the key quantities themselves but also for assessing the accuracy of different functionals and probing the influence of the long-range and static correlation. For the given system and quantity in question, we observe that obtained results do not significantly vary across different DFT functionals or post-HF methods, which is rather uncommon. Such an agreement between the employed methods suggests that static correlation, even if prominent in this system, cancels out in the studied energy differences. In fact, the values of the T1 diagnostics, which test the reliability of the single-reference description, do vary from one fragment to another. But for certain fragments they are fairly small and of similar magnitude, indicating the applicability of such fragments for the correction. Our best estimate of the reaction barrier is about 0.85 eV.

Transfer learning for accurate description of atomic transport in Al-Cu melts.

Machine learning interatomic potentials (MLIPs) provide an optimal balance between accuracy and computational efficiency and allow studying problems that are hardly solvable by traditional methods. For metallic alloys, MLIPs are typically developed based on density functional theory with generalized gradient approximation (GGA) for the exchange-correlation functional. However, recent studies have shown that this standard protocol can be inaccurate for calculating the transport properties or phase diagrams of some metallic alloys. Thus, optimization of the choice of exchange-correlation functional and specific calculation parameters is needed. In this study, we address this issue for Al-Cu alloys, in which standard Perdew-Burke-Ernzerhof (PBE)-based MLIPs cannot accurately calculate the viscosity and melting temperatures at Cu-rich compositions. We have built MLIPs based on different exchange-correlation functionals, including meta-GGA, using a transfer learning strategy, which allows us to reduce the amount of training data by an order of magnitude compared to a standard approach. We show that r2SCAN- and PBEsol-based MLIPs provide much better accuracy in describing thermodynamic and transport properties of Al-Cu alloys. In particular, r2SCAN-based deep machine learning potential allows us to quantitatively reproduce the concentration dependence of dynamic viscosity. Our findings contribute to the development of MLIPs that provide quantum chemical accuracy, which is one of the most challenging problems in modern computational materials science.

The molecular structure, electronic properties, and decomposition mechanism of FOX-7 under external electric field were calculated based on density functional theory

The molecular structure, electronic properties, and decomposition mechanism of FOX-7 under external electric field were calculated based on density functional theory

Tailoring d‐Band Center of Single‐Atom Nickel Sites for Boosted Photocatalytic Reduction of Diluted CO2 from Flue Gas

AbstractPhotocatalytic reduction of diluted CO2 from anthropogenic sources holds tremendous potential for achieving carbon neutrality, while the huge barrier to forming *COOH key intermediate considerably limits catalytic effectiveness. Herein, via coordination engineering of atomically scattered Ni sites in conductive metal–organic frameworks (CMOFs), we propose a facile strategy for tailoring the d‐band center of metal active sites towards high‐efficiency photoreduction of diluted CO2. Under visible‐light irradiation in pure CO2, CMOFs with Ni‐O4 sites (Ni‐O4 CMOFs) exhibits an outstanding rate for CO generation of 13.3 μmol h−1 with a selectivity of 94.5 %, which is almost double that of its isostructural counterpart with traditional Ni‐N4 sites (Ni‐N4 CMOFs), outperforming most reported systems under comparable conditions. Interestingly, in simulated flue gas, the CO selectivity of Ni‐N4 CMOFs decreases significantly while that of Ni‐O4 CMOFs is mostly unchanged, signifying the supremacy for Ni‐O4 CMOFs in leveraging anthropogenic diluted CO2. In situ spectroscopy and density functional theory (DFT) investigations demonstrate that O coordination can move the center of the Ni sites′ d‐band closer to the Fermi level, benefiting the generation of *COOH key intermediate as well as the desorption of *CO and hence leading to significantly boosted activity and selectivity for CO2‐to‐CO photoreduction.

Complexation by γ-cyclodextrin as a way of improving anticancer potential of sumanene

Biological applications of sumanene buckybowl molecule have been widely discussed over the years yet remain still unexplored experimentally. On the other hand, creating cyclodextrin-containing supramolecular assemblies was demonstrated to be a powerful tool in terms of designing effective systems for medicinal chemistry purposes. Here, we show that sumanene molecule exclusively forms 1:1 host-guest complexes with γ-cyclodextrin (γCD) or (2-hydroxypropyl)-γ-cyclodextrin (HP-γCD), as revealed by extensive spectroscopic studies supported with density functional theory (DFT) computations. Based on our preliminary biological studies, we discovered that the formation of such complexes resulted in the improvement of anticancer properties of sumanene, expressed by high cell viabilities in vitro of healthy human mammary fibroblasts (HMF) together with low viabilities of human breast adenocarcinoma cells (MDA-MB-231). Improved pharmacokinetic (ADME-Tox) properties for sumanene@γCD and sumanene@HP-γCD complexes in comparison to native sumanene were also supported by in sillico modeling studies. This work provides the method how to focus the cytotoxic action of sumanene toward cancer cells using supramolecular assembly strategy, paving the way to the further exploration of biological properties of sumanene-containing supramolecular systems with bioactive features and applications of this buckybowl in general.

Tailoring d-Band Center of Single-Atom Nickel Sites for Boosted Photocatalytic Reduction of Diluted CO2 from Flue Gas.

Photocatalytic reduction of diluted CO2 from anthropogenic sources holds tremendous potential for achieving carbon neutrality, while the huge barrier to forming *COOH key intermediate considerably limits catalytic effectiveness. Herein, via coordination engineering of atomically scattered Ni sites in conductive metal-organic frameworks (CMOFs), we propose a facile strategy for tailoring the d-band center of metal active sites towards high-efficiency photoreduction of diluted CO2. Under visible-light irradiation in pure CO2, CMOFs with Ni-O4 sites (Ni-O4 CMOFs) exhibits an outstanding rate for CO generation of 13.3 μmol h-1 with a selectivity of 94.5 %, which is almost double that of its isostructural counterpart with traditional Ni-N4 sites (Ni-N4 CMOFs), outperforming most reported systems under comparable conditions. Interestingly, in simulated flue gas, the CO selectivity of Ni-N4 CMOFs decreases significantly while that of Ni-O4 CMOFs is mostly unchanged, signifying the supremacy for Ni-O4 CMOFs in leveraging anthropogenic diluted CO2. In situ spectroscopy and density functional theory (DFT) investigations demonstrate that O coordination can move the center of the Ni sites' d-band closer to the Fermi level, benefiting the generation of *COOH key intermediate as well as the desorption of *CO and hence leading to significantly boosted activity and selectivity for CO2-to-CO photoreduction.

Selective Coupling of β-(Borylvinyl)silanes by a Gold-Catalyzed Hiyama Reaction-An Easy Way to Diaryl-Substituted Vinyl Boronates.

The use of diaryl-substituted vinyl boronates, a class of chemical building blocks with well-known synthetic utility, is principally limited by the difficulty faced in their preparation. Herein, we present a convenient synthetic strategy based on a gold-catalyzed Hiyama arylation of (Z)-β-(borylvinyl)silanes, which are easily accessible by hydroboration of silylalkynes. By exploiting the highly electronegative nature of the gold(III) intermediate (which is accessed by light-assisted oxidation using aryl diazonium salts), a selective activation of the silyl group in the presence of the boron moiety is achieved. This opens a route to selectively synthesize diaryl-substituted vinyl boronates. The reaction shows a broad substrate range, excellent functional group tolerance, and perfect chemoselectivity. Experimental studies and density functional theory (DFT) calculations allowed us to elucidate the mechanism of the reaction. The synthetic potential was demonstrated by downstream transformations providing a facile route to bifunctional phenanthrenes and triaryl-substituted olefins.

NiIr Nanowire Assembles as an Efficient Electrocatalyst Towards Oxygen Evolution Reaction in Both Acid and Alkaline Media.

Oxygen evolution reaction (OER) is the rate-limiting step in water electrolysis due to its sluggish kinetic, and it is challenging to develop an OER catalyst that could work efficiently in both acid and alkaline environment. Herein, NiIr nanowire assembles (NAs) with unique nanoflower morphology were prepared by a facile hydrothermal method. As a result, the NiIr NAs exhibited superior OER activity in both acid and alkaline media. Specifically, in 0.1 M HClO4, NiIr NAs presented a superior electrocatalytic performance with a low overpotential of merely 242 mV at 10 mA cm-2 and a Tafel slope of only 58.1 mV dec-1, surpassing that of commercial IrO2 and pure Ir NAs. And it achieved a significantly higher mass activity of 148.40 A/g at -1.5 V versus RHE. In 1.0 M KOH, NiIr NAs has an overpotential of 291 mV at 10 mA cm-2 and a Tafel slope of 42.1 mV dec-1. Such remarkable activity makes the NiIr NAs among the best of recently reported representative Ir-based OER electrocatalysts. Density functional theory (DFT) calculations confirmed alloying effect promotes surface bonding of NiIr with oxygen-containing reactants, resulting in excellent catalytic properties.

Photovoltaic response promoted via intramolecular charge transfer in triphenylpyridine core with small acceptors: A DFT/TD-DFT study

Currently, A−π−A configured molecules (TTP1-TTP6) were designed from the reference compound (TPPR) by modifying the terminal acceptors for photovoltaic materials. Density functional theory (DFT) and time-dependent density functional theory (TD-DFT) using the M06/6-311G(d,p) functional were employed to analyze the photonic and electronic properties of the newly designed derivatives. Various analyses; frontier molecular orbitals (FMOs), density of states (DOS), absorption spectra (λmax), transition density matrix (TDM), binding energy (Eb), hole-electron and open circuit voltage (Voc) were performed to explore the photovoltaic properties of triphenylpyridine based compounds. The structural modulation with acceptor moieties significantly tuned their HOMO and LUMO levels, resulting in reduced band gaps (2.833–3.037 eV). They also exhibited broader absorption spectra (λmax) ranging from 482.560 to 514.756 nm as compared to the reference compound (486.289 nm). Notably, TPP3 showed the good photovoltaic response as it displayed the least energy gap (2.833 eV) with lower binding energy (0.415 eV) and bathochromic shift (512.798 nm) in absorption spectra as compared to all other derivatives. Beside this, a comparative study with spiro-OMeTAD and P3HT standard hole transport materials illustrated that these materials can also be utilized as effective photovoltaic materials.

Unexpected band structure changes within the higher-temperature antiferromagnetic state of CeBi

The interest in the rare-earth monopnictides was boosted after the discovery of unconventional surface-state pairs in antiferromagnetically ordered NdBi. In contrast to other materials in which such states were reported, CeBi is known to have multiple antiferromagnetic phases. In this study, we perform angle-resolved photoemission spectroscopy (ARPES) measurements in conjunction with density functional theory (DFT) calculations to investigate the evolution of the electronic structure of CeBi upon a series of antiferromagnetic (AFM) transitions. We find evidence for a new AFM transition in addition to two previously known from transport studies. We demonstrate the development of an additional Dirac state in the ( + − + − ) ordered phase and a transformation of unconventional surface-state pairs in the ( + + − − ) ordered phase. This revises the phase diagram of this intriguing material, where there are now three distinct AFM states below TN in zero magnetic field instead of two as it was previously thought.

Challenges in Mathematics Arising from Theoretical and Computational Chemistry

The combination of theoretical chemistry and mathematics represents a significant advancement in science since it has yielded insights into the enigmas surrounding atoms and molecules. The advancement of technology has greatly benefited drug development, leading to significant advancements in both medicine and materials research. This summary discusses innovative methodologies and computational challenges in the expansive domain of theoretical and computational chemistry. Despite the computational challenges associated with the Schrodinger equation and Density Functional Theory (DFT), quantum mechanics offers a basic understanding of the behaviour of molecules and atoms. While MD simulations may not handle long-range interactions and complex configuration spaces, they nonetheless excel at capturing various time scales of molecular behaviour. Nevertheless, the process of transforming abstract notions into computer models for the purpose of solving MD simulations continues to be difficult; statistical mechanics offers a theoretical framework for understanding MD simulations. Data-driven methodologies and machine learning have significantly transformed the perspective of computational chemistry by enabling the observation and comprehension of very complex chemical interactions. We must also address concerns about interpretability, reliability in limited data streams, and system transferability. These challenges expedite the advancement of novel materials, product designs, and pharmaceuticals by leveraging machine learning and integrating it with specialised domain expertise. We used available data from many reputable databases, spanning the time period from 2010 to 2024. It is imperative to prioritise the advancement of multiscale modelling techniques and hybrid quantum-classical tools in order to achieve sufficient mastery over chemical phenomena. Another potential benefit is the use of novel mathematical models to uncover previously unknown patterns and connections in genetic data. The most effective way to tackle mathematical problems is by employing a straightforward approach and engaging in collaboration with experts from other fields. By adopting this approach, we can effectively address significant societal issues and propel advancements in chemistry. Keywords: mathematics, computational, chemistry, theoretical, challenges, quantum mechanics

Organic BODIPY based gels: Optical, electrochemical and self‐assembly properties

Two novel BODIPY dyes, BOC3 and BC12, were synthesized with variable alkyl chains at terminal amide functional units. BC12, featuring a longer alkyl chain (‐C12H25), formed a gel compared to BOC3, which has a shorter alkyl chain (‐CH2OCH3), due to supra molecular self‐assembly in film. Both dyes exhibited absorption peaks around 530 nm in the visible region, with a red shift of about 30 nm in the film state, essential for organic electronic applications. Concentration variation studies revealed π‐π stacking/aggregates in the solid state causing red shifts in absorption and emission. BC12 exhibited more significant red shifts in film compared to its solution state due to supra molecular self‐assembly. Electronic structure analysis using density functional theories (BMK and O3LYP) showed better correlation with absorption using the O3LYP method. Both dyes displayed quasi‐irreversible oxidation and reduction couples with suitable HOMO (5.46 eV) and LUMO (3.32 eV) energy levels for organic electronic applications. Transient photoluminescence studies indicated a longer lifetime for BC12 (5.28 ns) than BOC3 (4.50 ns), suggesting π‐π aggregation and supra molecular self‐assembly. BC12's gelation, attributed to its long alkyl chain and two‐dimensional motifs of the BODIPY core, forms spherical‐shaped nano networks.

Exploring the structural and electronic properties of N-doped Ti2C MXenes for novel applications in advanced materials and devices: A DFT study

MXenes, a category of two-dimensional transition metal carbides and nitrides, have attracted significant interest owing to their distinctive characteristics. This study utilizes Density Functional Theory (DFT) to examine the effects of nitrogen doping on the structural and electrical properties of Ti2C MXenes. N-doping induces significant alterations in the lattice structure and electronic properties, culminating in an elevated density of states at the Fermi level, indicating improved conductivity. Furthermore, optical characteristics such as reflectivity and loss function are affected by N-doping, resulting in a shift in the intensity of the reflectivity peak. The alterations provide N-doped Ti2C MXenes viable candidates for advanced applications in energy storage, catalysis, and electronic devices, facilitating future empirical and theoretical investigations in MXene-based materials.

Raman activities of nitrogen reduction and ammonia oxidation intermediates on the high-entropy alloy CoCuFeMoNi catalytic surface.

We developed a computational framework to extract the Raman spectra of nitrogen reduction and ammonia oxidation intermediates on high-entropy alloy (HEA) surfaces, integrating density functional theory with microstructural representations to account for the inherent lattice randomness in these materials. As a case study, we computed the Raman activities of intermediates (N2*, NNH*, N*, NH*, and NH3*) and H* adsorption on CoCuFeMoNi HEA surfaces. A comprehensive map of Raman peaks was generated and assigned to specific vibrational modes. The method highlighted the effects of lattice randomness on the Raman spectra compared to those of adsorbates on single-element catalysts. For instance, our results showed that the adsorbed N2 exhibits Raman modes that are dependent on whether the adsorption is vertical or horizontal. These peak differences could serve as unique fingerprints to identify nitrogen reduction reaction pathways. Moreover, it is also possible to detect surface poisoning by hydrogen, a common issue in reductive environments, due to the high-frequency peaks of H* compared to the typical N-metal stretching and bending frequencies. These results provide valuable references for identifying intermediates in nitrogen reduction and ammonia oxidation reactions, offering insights into reaction mechanisms and potential surface poisoning. This approach is generalizable to other reactions and surfaces in catalysis, provided that the relevant intermediates can be identified.

Understanding melting behavior of aluminum clusters using machine learned deep neural network potential energy surfaces.

Deep neural network-based deep potentials (DP), developed by Tuo et al., have been used to compute the thermodynamic properties of free aluminum clusters with accuracy close to that of density functional theory. Although Jarrold and collaborators have reported extensive experimental measurements on the melting temperatures and heat capacities of free aluminum clusters, no reports exist for finite-temperature abinitio simulations on larger clusters (N > 55 atoms). We report the heat capacities and melting temperatures for 32 clusters in the size range of 48-342 atoms, computed using the multiple histogram technique. Extensive molecular dynamics (MD) simulations at twenty four temperatures have been performed for all the clusters. Our results are in very good agreement with the experimental melting temperatures for 19 clusters. Except for a few sizes, the interesting features in the heat capacities have been reproduced. To gain insight into the striking features reported in the experiments, we used structural and dynamical descriptors such as temperature-dependent mean squared displacements and the Lindemann index. Bimodal features observed in Al116 and the weak shoulder seen in Al52 are attributed to solid-solid structural transitions. In confirmation of the earlier reports, we observe that the behavior of the heat capacities is significantly influenced by the nature of the ground state geometries. Our findings show that the sharp drop in the melting temperature of the 56-atom cluster is a consequence of the change in the geometry of Al55. Mulliken population analysis of Al55 reveals that the charge-induced local electric field is responsible for the strong bonding between core and surface atoms, leading to the higher melting temperature. Our calculations do not support the lower melting temperature observed in experimental studies of Al69. Our results indicate that Al48 is in a liquid state above 600K and does not support the high melting temperature reported in the experiment. It turns out that the accuracy of the DP model by Tuo et al. is not reliable for MD simulations beyond 750K. We also report low-lying equilibrium geometries and thermodynamics of 11 larger clusters (N = 147-342) that have not been previously reported, and the melting temperatures of these clusters are in good agreement with the experimental ones.

Heterogeneous Carbonylation of Alcohols on Charge‐Density‐Distinct Mo−Ni Dual Sites Localized at Edge Sulfur Vacancies

AbstractAlcohols carbonylation is of great importance in industry but remains a challenge to abandon the usage of the halide additives and noble metals. Here we report the realization of direct alcohols heterogeneous carbonylation to carbonyl‐containing chemicals, especially in methanol carbonylation, with a remarkable space‐time‐yield (STY) of 4.74 molacetyl/kgcat./h and a durable stability as long as 100 h on Ni@MoS2 catalyst. Mechanistic analysis reveals that the Mo−Ni dual sites localized at edge sulfur vacancies of Ni@MoS2 exhibit distinct charge density, which strongly activate CH3OH to break its C−O bond and non‐dissociatively activate CO. Density functional theory calculations further suggest that the low charge density in Mo−Ni, the Ni site, could significantly lower the barrier for CO migration and nucleophilic attack of methoxy species, and finally leads to the rapid formation of acetyl products. Ni@MoS2 catalyst could also effectively realize the carbonylation of ethanol, n‐propanol and n‐butanol to their acyl products, which may demonstrate its universal application for alcohols carbonylation.

Achieving Color‐Tunable Solid‐State Fluorescence by Adjusting the Molecular‐State Chromophores on Carbonized Polymer Dots

Carbon dots (CDs) have attracted great interest in recent years due to their excellent fluorescent properties, convenient synthetic methods, and wide availability of source materials. However, although most CDs exhibit excellent luminescent properties in solution, achieving solid‐state fluorescence (SSF) CDs is still difficult due to aggregation‐caused quenching, and realizing color‐tunable SSF‐CDs remains a serious challenge. Herein, the SSF‐carbonized polymer dots (CPDs) are successfully obtained by one‐step hydrothermal of polyethyleneimine (PEI) and citric acid. The photoluminescence centers of these CPDs are molecular‐state chromophores, which are proved as imidazo [1,2‐a] pyridine‐7‐carboxylic acid, 1,2,3,5‐tetrahydro‐5‐oxo‐ (IPCA) derivatives by NMR. Further investigation reveals that the formation and distribution of IPCA derivatives would affect the bandgaps when CPDs particles aggregate, which is also verified by density functional theory calculations. Based on the above conclusion, the blue, green, yellow, and orange SSF CPDs are successfully obtained, and the multicolor and white emission light emitting diodes are effectively fabricated by these CPDs.