High Stability Research Articles

ZIF‐67 Derived Cobalt Catalysts for the Hydroformylation of Liquid Olefins

AbstractIn this work, we described a general monometallic cobalt heterogeneous catalyst for the hydroformylation of olefins, achieving good yields and recyclability up to five times with no loss in catalytic activity. These catalysts were prepared through the pyrolysis of the well‐defined metal–organic framework ZIF‐67. The addition of steam during the pyrolysis did not affect the final phase composition of the cobalt particles; nonetheless, it resulted in an increase of the cobalt particle size and the partial removal of the carbonaceous matrix. The materials were extensively characterized by several techniques, and it was observed that the N‐doped carbon matrix played a crucial role in terms of activity and stability. Different liquid olefins, including internal, terminal, and cyclic were successfully tested in our hydroformylation protocol. Aldehydes yields of 48%–77% for different liquid olefins were achieved with the optimal catalyst. No leaching of the active sites was observed over five catalytic cycles. The high stability of the catalyst is attributed to the presence of stabilizing nitrogen atoms bearing the cobalt sites.

Subphenotypes of adult-onset diabetes: Data-driven clustering in the population-based KORA cohort.

A data-driven cluster analysis in a cohort of European individuals with type 2 diabetes (T2D) has previously identified four subgroups based on clinical characteristics. In the current study, we performed a comprehensive statistical assessment to (1) replicate the above-mentioned original clusters; (2) derive de novo T2D subphenotypes in the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) cohort and (3) describe underlying genetic risk and diabetes complications. We used data from n = 301 individuals with T2D from KORA FF4 study (Southern Germany). Original cluster replication was assessed forcing k = 4 clusters using three different hyperparameter combinations. De novo clusters were derived by open k-means analysis. Stability of de novo clusters was assessed by assignment congruence over different variable sets and Jaccard indices. Distribution of polygenic risk scores and diabetes complications in the respective clusters were described as an indication of underlying heterogeneity. Original clusters did not replicate well, indicated by substantially different assignment frequencies and cluster characteristics between the original and current sample. De novo clustering using k = 3 clusters and including high sensitivity C-reactive protein in the variable set showed high stability (all Jaccard indices >0.75). The three de novo clusters (n = 96, n = 172, n = 33, respectively) adequately captured heterogeneity within the sample and showed different distributions of polygenic risk scores and diabetes complications, that is, cluster 1 was characterized by insulin resistance with high neuropathy prevalence, cluster 2 was defined as age-related diabetes and cluster 3 showed highest risk of genetic and obesity-related diabetes. T2D subphenotyping based on its sample's own clinical characteristics leads to stable categorization and adequately reflects T2D heterogeneity.

The Role of Exogenous microRNAs on Human Health: The Plant–Human Trans-Kingdom Hypothesis

MicroRNAs (miRNAs) are small, endogenous, single-stranded RNAs that act on gene silencing at the post-transcriptional level by binding to a target messenger RNA (mRNA), leading to its degradation or inhibiting translation into functional proteins. The key role of miRNAs in development, proliferation, differentiation andapoptosis has been deeply investigated, revealing that deregulation in their expression is critical in various diseases, such as metabolic disorders and cancer. Since these small molecules initially evolved as a mechanism of protection against viruses and transposable elements, the fascinating hypothesis that they can move between organisms both of the same or different species has been postulated. Trans-kingdom is the term used to define the migration that occurs between species. This mechanism has been well analyzed between plants and their pests, in order to boost defense and increase pathogenicity, respectively. Intriguingly, in the last decades, the plant–human trans-kingdom migration via food intake hypothesis arose. In particular, various studies highlighted the ability of exogenous miRNAs, abundant in the mainly consumed plant-derived food, to enter the human body affecting gene expression. Notably, plant miRNAs can resist the strict conditions of the gastrointestinal tract through a methylation step that occurs during miRNA maturation, conferring high stability to these small molecules. Recent studies observed the anti-tumoral, immune modulator and anti-inflammatory abilities of trans-kingdom interaction between plant and human. Here, we depict the existing knowledge and discuss the fascinating plant–human trans-kingdom interaction, highlighting first the eventual role of plant miRNAs from foods on our somatic gene identity card and then the potential impact of using plant miRNAs as novel therapeutic avenues.

Heterogeneous Asymmetric Hydrogenation of C=C and C=O Double Bonds

Nowadays, heterogeneous catalysts play a crucial role in the field of asymmetric catalysis to produce enantiopure compounds for various applications. The unique properties of heterogeneous systems, such as high stability, reusability, or ease of separation, allow effective catalysis of asymmetric transformations and their further implementation in industrial processes. In this mini review, we address the recent trend in the synthesis of chiral heterogeneous catalysts and their subsequent application in asymmetric hydrogenation reactions. We focus on current advances in asymmetric hydrogenation reactions of C=O and C=C bonds due to their high relevance in the fine chemicals industry. Our main aim is to provide a short overview of this expanding field, its current challenges, and future perspectives.

Ultrahigh Energy Storage of Twisted Structures in Supramolecular Polymers.

Polymer dielectrics possess outstanding advantages for high-power energy storage applications such as high breakdown strength (Eb) and efficiency (η), while both of them decrease rapidly at elevated temperatures. Although several strategies have been evaluated to enhance Eb and heat resistance, the discharged energy density (Ud) is still limited by the planar conjugated structure. In this study, a novel approach to manipulate polymer morphology is introduced, thereby influencing dielectric properties. A range of polyurea (PU)-based polymers are predicted from different structural unit combinations by machine learning and synthesized two representative polymers with high dielectric constants (K) and thermal stability. These polymers are combined with PI to form a twisted polymer via hydrogen bonding interactions (HNP). Both experimental results and computational simulations demonstrate the twisted structure disrupts the conjugated structure to widen the bandgap and increase dipole moment through the twisting of polar groups, leading to simultaneous improvements in both K and Eb. Consequently, HNP-20% achieves an ultrahigh Ud of 6.42 Jcm-3 with an efficiency exceeding 90% at 200 °C. This work opens a new avenue to scalable high Ud all-polymer dielectric for high-temperature applications.

Performance analysis of DC-DC Buck converter with innovative multi-stage PIDn(1+PD) controller using GEO algorithm

Power electronic converters are widely used in various fields of electrical equipment. Due to their fast dynamics and non-linear nature, controlling them requires dealing with various complexities. Therefore, having a well-designed, high-speed, and robust controller is critical to ensure the effective operation of these devices. In a DC-DC converter, steady-state performance with minimum error and fast dynamic response relies on controller design. This paper presents the design of a multi-stage PID controller with an N-filter combined with a one plus proportional derivative (1+PD) controller. This controller illustrates fast tracking reference voltage; additionally, it shows incredible results when the DC-DC converter operates in different modes. The parameters of the proposed controller are effectively determined using the golden eagle optimization (GEO) algorithm. Furthermore, a comprehensive comparison between the proposed controller, proportional–integral–derivative (PID), and fractional order PID (FOPID) controllers, as well as different metaheuristic optimization methods in various conditions, has been conducted to demonstrate the effectiveness of the proposed controller. The behavior of the closed-loop system under different conditions has been thoroughly investigated. The superior time and frequency domain characteristics of the closed-loop system with the PIDn(1+PD) controller highlight its superiority over other controllers. The demonstrated enhancements in settling time, voltage regulation accuracy, and transient response emphasize the potential applicability of the proposed control strategy in real-world power electronics systems, particularly in scenarios requiring high efficiency, stability, and dynamic performance.

Facile Approach for the Fabrication of Vapor Sensitive Spin Transition Composite Nanofibers

In this work polymer nanofibers were functionalized by incorporation of the spin transition (ST) compound [Fe(H2btm)2(H2O)2]Cl2 (FeH2btm) (H2btm = di(1H‐tetrazol‐5‐yl)methane). FeH2btm is an interesting compound due to its ability to reversibly and sensitively switch between high spin (HS) and low spin (LS) state when exposed to common volatile compounds (VOC) like ammonia and methanol. By using polyvinylidene fluoride (PVDF) as the main compound, inhibiting interactions between the complex and polymer were minimized. By using UV‐Vis spectroscopy, the visible and reversible switching between HS and LS state when exposed to an ammonia or hydrochloric acid atmosphere was confirmed. Powder X‐Ray diffraction (PXRD), scanning electron microscopy (SEM) and energy dispersive X‐Ray spectroscopy (EDX) show a homogenous distribution of FeH2btm with no major crystalline accumulations and a mean fiber diameter of 106 ± 20 nm. The composite fiber has a similarly high thermal stability as the pure FeH2btm, as shown by thermogravimetric analysis (TGA). Mössbauer spectroscopy indicates an incomplete spin transition after exposition to ammonia. This could be due to low permeability of the VOC into the composite fiber.

Study on Evaluation and Prediction Model of Long-term Mechanical Properties of Fine-grained Saline Soil Subgrade

In this thorough examination, we dive deep into the long-lasting mechanical characteristics of fine-grained saline soil subgrades, aspiring to establish a precise and reliable collection of predictive models. Our objective is to provide a solid scientific footing for the design and ongoing upkeep of road networks within saline soil environments. Analyzing prolonged monitoring data across diverse highway subgrades within a prototypical saline soil locale, we unveil the intricate temporal fluctuations and environmental sensitivities of the soil’s mechanical properties under continuous load. Precisely, the subgrade’s compressive modulus dwindled by 15%, while shear strength declined by 8% over a five-year period. These trends intensify during rainy and scorching seasons, with drops surpassing 20% and 12% respectively. Leveraging this intricate data, we deploy nonlinear regression analysis and sophisticated machine learning algorithms to construct a predictive model tailored for the long-term mechanical properties of fine-grained saline soil roadbeds. This model integrates a multitude of factors, including load duration, temperature, humidity, and more, delivering accurate forecasts of key subgrade indicators like compressive modulus, shear strength, and beyond. In the verification stage, compared with the measured data, the error rate of the model prediction results is controlled within 5%, showing high prediction accuracy and stability. In addition, we also carried on the sensitivity analysis to the model, found that the load size and the duration of the impact on the mechanical properties of the roadbed is the most significant. Therefore, in the design of road engineering in saline soil areas, the influence of these factors should be fully considered, and reasonable engineering measures should be taken to ensure the safety and durability of roads. This study not only provides effective data support for the long-term mechanical performance evaluation of fine-grained saline soil roadbed, but also provides an important theoretical reference for engineering practice in related fields.

Enhanced Structural VS4 Grown onto Hollow Carbon Mesoporous Spheres via Surficial Bonding for High Cycling Stability in Sodium-Ion Batteries.

Transition metal sulfides are recognized as an excellent alternative to sodium ion anodes ascribed to the outstanding theoretical capacity. The unique crystal arrangement of VS4 gives it exceptional theoretical capacity, despite challenges like insufficient electrical conductivity and undesirable volume expansion. Herein, a novel stabilized anode featuring a distinctive 3D hollow spherical structure is proposed, providing a simple strategy to synthesize such anodes for VS4-HCMSs bonded via C-O-S and V-O-C interfaces. The kinetic investigations and density functional theory reveal that the unique structure connected by interfacial bonds enhances Na+ transport rate and charge transfer efficiency, while carbon greatly mitigates the volume expansion. Unsurprisingly, the VS4-HCMSs exhibit an impressive first-cycle Coulombic efficiency of 91.31% and an ultrahigh reversible capacity of 612 mAh g-1 after 300 cycles at 0.5 A g-1, even exhibit the reversible capacity of 498.8 mAh g-1 after 1000 cycles at 5 A g-1. Additionally, the NaFePO4//VS4-HCMSs full cell is cycled for 200 cycles at 0.2 C and powered the light-emitting diodes for up to 30 minutes afterward. Overall, this work enhances the conductivity and stability of the material by combining VS4 with hollow carbon mesoporous spheres through interfacial bonding, offering an efficient strategy to anode materials in sodium-ion batteries.

Imaging in-operando LiCoO2 nanocrystallites with Bragg coherent X-ray diffraction

Although the LiCoO2 (LCO) cathode material has been widely used in commercial lithium ion batteries (LIB) and shows high stability, LIB’s improvements have several challenges that still need to be overcome. In this paper, we have studied the in-operando structural properties of LCO within battery cells using Bragg Coherent X-ray Diffraction Imaging to identify ways to optimise the LCO batteries’ cycling. We have successfully reconstructed the X-ray scattering phase variation (a fingerprint of atomic displacement) within a ≈ (1.6 × 1.4 × 1.3) μm3 LCO nanocrystal across a charge/discharge cycle. Reconstructions indicate strained domains forming, expanding, and fragmenting near the surface of the nanocrystal during charging, with a determined maximum relative lattice displacements of 0.467 Å. While discharging, all domains replicate in reverse the effects observed from the charging states, but with a lower maximum relative lattice displacements of 0.226 Å. These findings show the inefficiency-increasing domain dynamics within LCO lattices during cycling.

Late-stage Functionalization using a Popular Titrating Agent: Aryl-Chlorides and -Fluorides Activation by the Diphenylacetic Acid Dianion.

Aryl-chlorides and -fluorides are common building blocks, but their use in synthesis is limited by the high stability of their Ar-X bonds. The generation of aryl radicals via activation of strong Ar-X bonds is possible through the irradiation of tailor-made organic anions, which become reductants stronger than lithium metal. We report that the combination of visible light with the cheap diphenylacetic acid dianion is an even better tool, showing excellent activity across a variety of complex substrates and providing opportunities for late-stage drug modification. Ar-X bonds are chemoselectively activated in the presence of more easily reducible functions, such as Alk-Cl ones and carbonyl groups. These results pave the way to original synthetic strategies that would be otherwise considered impossible.

A Long‐Range Disordering RuO2 Catalyst for Highly Efficient Acidic Oxygen Evolution Electrocatalysis

AbstractNon‐iridium acid‐stabilized electrocatalysts for oxygen evolution reaction (OER) are crucial to reducing the cost of proton exchange membrane water electrolyzers (PEMWEs). Here, we report a strategy to modulate the stability of RuO2 by doping boron (B) atoms, leading to the preparation of a RuO2 catalyst with long‐range disorder (LD‐B/RuO2). The structure of long‐range disorder endowed LD‐B/RuO2 with a low overpotential of 175 mV and an ultra‐long stability, which can maintain OER for about 1.6 months at 10 mA cm−2 current density in 0.5 M H2SO4 with almost invariable performance. More importantly, a PEM electrolyzer using LD‐B/RuO2 as the anode demonstrated excellent performance, reaching 1000 mA cm−2 at 1.63 V with durability exceeding 300 h at 250 mA cm−2 current density. The introduction of B atoms induced the formation of a long‐range disordered structure and symmetry‐breaking B−Ru−O motifs, which enabled the catalyst structure to a certain toughness while simultaneously inducing the redistribution of electrons on the active center Ru, which jointly promoted and guaranteed the activity and long‐term stability of LD‐B/RuO2. This study provides a strategy to prepare long‐range disordered RuO2 acidic OER catalysts with high stability using B‐doping to perturb crystallinity, which opens potential possibilities for non‐iridium‐based PEMWE applications.

A New Algorithm for Predicting Dam Deformation Using Grey Wolf-Optimized Variational Mode Long Short-Term Neural Network

To solve the problems of difficult-to-model parameter selections, useful-signal extraction and improper-signal decomposition in nonlinear, non-stationary dam displacement time series prediction methods, we propose a new predictive model for grey wolf optimization and variational mode decomposition and long short-term memory (GVLSTM). Firstly, we used the grey wolf optimization (GWO) algorithm to optimize the parameters of variable mode decomposition (VMD), obtaining the optimal parameter combination. Secondly, we used multiscale permutation entropy (MPE) as a standard to select signal screening, determining and recon-structing the effective modal components. Finally, the long short-term memory neural network (LSTM) was used to learn the dam deformation characteristics. The result shows that the GVLSTM model can effectively reduce the estimation deviation of the prediction model. Compared with VMDGRU and VMDANN, the average RMSE and MAE value of each station is increased by 19.11%~28.58% and 27.66%~29.63%, respectively. We used determination (R2) coefficient to judge the performance of the prediction model, and the value of R2 was 0.95~0.97, indicating that our method has good performance in predicting dam deformation. The proposed method has outstanding advantages of high accuracy, reliability, and stability for dam deformation prediction.

Reusable SERS Platform of Femtosecond Laser Processed Substrate for Detection of Malachite Green

This study presents the development of highly efficient Surface-Enhanced Raman Scattering (SERS) substrates through femtosecond (fs) laser processing of crystalline silicon (Si), resulting in mountain-like microstructures. These microstructures, when decorated with gold nanoparticles (Au NPs), exhibit remarkable SERS performance due to the creation of concentrated hotspots. The enhanced Raman signals originate from the excitation of localized surface plasmon resonance (LSPR) of the Au NPs and the multi-scale rough morphology of the Si substrates. Finite-element method simulations confirm the electromagnetic field enhancement in narrow gaps, supporting the experimental observations. The fabricated substrates show high uniformity, oxidation resistance, long-term stability, and exceptional reproducibility, making them ideal for molecular detection, especially in food safety applications. A remarkable enhancement factor (EF) of 1010 is attained in the detection of Malachite Green (MG), boasting a limit of detection (LoD) as low as 10−14 M. This underscores the immense potential of this technique for achieving highly sensitive and dependable SERS-based sensing capabilities.

Anion regulation for surface passivation enables ultrahigh-stability perovskite nanocrystals.

All-inorganic perovskite CsPbBr3 nanocrystals (NCs) display high photoluminescence quantum yield and narrow emission, which show great potential application in optoelectronic devices. However, the poor environment stability of NCs will hinder their practical application. Herein, a series of ionic liquids with different anions (BF4-, Br-, and NO3-) were used as a sole capping ligand to synthesize NCs. Among the three samples, 1-hexadecyl-3-methylimidazolium tetrafluoroborate ([C16MIM]BF4) capped NCs have the highest stability in light, thermal, and water, possibly attributing to the in situ passivation of bromine vacancy via pseudohalogen BF4- and tight binding of ionic liquid ligands and lead atoms. In addition, green-emission [C16MIM]BF4 NCs were used to assemble a white light-emitting diode device, and it possessed a wide National Television System Committee color gamut of 124.5% and a stable emission peak at high driving currents of 380 mA. This work paves the way for resurfacing perovskite NCs with ultrahigh stability, thereby driving the perovskite NC display industry closer to real-world application.

Influence of Subvalent Twin-Rattler for High n-Type Thermoelectric Performance in Bi13S18Br2 Chalcohalide.

Metal chalcohalides, owing to their higher stability over halides and greater tunability of electronic features over chalcogenides, open new avenues for investigating properties of materials. Complex metal chalcohalides can be a good choice for thermoelectric studies for their halide-like low thermal conductivity and chalcogenide-like high electrical conductivity. Here, we have investigated the thermoelectric properties of n-type Bi13S18Br2 and utilized the concept of Fajans' polarization to describe the formation of a dimer and explained how it can help achieve high thermoelectric figure of merit (zT) of ∼1.0 at 748 K. This zT value is so far the highest-reported value for pristine metal chalcohalides. The existence of subunit in Bi13S18Br2 is experimentally verified by synchrotron X-ray pair distribution function (X-PDF) analysis. The complex structure of Bi13S18Br2 having a large unit cell exhibits simultaneous dimer-cation rattler (i.e., "twin-rattler"), which decreases the lattice thermal conductivity drastically. We observed evidence of such low-energy rattling vibrations from DFT-calculated eigen mode visualizations of the phonon dispersion. The subvalent nature of accommodates an extra electron in Bi(6pz) orbital, which helps form a weakly dispersed donor band just below the Fermi energy (EF), leading to a significant reduction in band gap (0.77 eV), which is favorable for high thermoelectric performance. Consequently, we obtained a semiconducting nature of n-type Bi13S18Br2 with moderate electrical conductivity, as well as a high Seebeck coefficient. Our investigation presents the importance of fundamental chemistry in thermoelectrics and demonstrates the influence of subvalent twin-rattler in triggering high thermoelectric performance in metal chalcohalides.

Aptamer-Encapsulated Cellular Nanoparticles for Neurotoxin Neutralization.

Aptamers are single-stranded oligonucleotides that fold into defined architectures for specific target binding. In this study, aptamers are selected that specifically bind to small-molecule neurotoxins and encapsulate them into cell membrane-coated nanoparticles (referred to as 'cellular nanoparticles' or 'CNPs') for effective neutralization of neurotoxins. Specifically, six different aptamers are selected that bind to saxitoxin (STX) or tetrodotoxin (TTX) and encapsulate them into metal-organic framework cores, which are then coated with neuronal cell membrane. The resulting CNPs exhibit high colloidal stability, minimal aptamer leakage, and effective protection of aptamer payloads against enzyme degradation. This detoxification platform combines membrane-enabled broad-spectrum neutralization with aptamer-based specific toxin binding, offering dual-modal neutralization mechanisms for efficient neurotoxin neutralization. The in vitro neutralization efficacy is demonstrated using a neuron osmotic swelling assay, a Na+ flux fluorescence assay, and a cytotoxicity assay. The in vivo neutralization efficacy is further validated using mouse models of STX and TTX intoxication in both therapeutic and preventative regimens. Overall, integrating aptamers with CNPs combines the strengths of both technologies, resulting in a robust solution for broad-spectrum toxin-neutralization applications.

Novel metal–organic framework biosensing platform for detection of COVID-19 RNA

The latest pandemic resulting from the novel SARS-CoV-2 coronavirus has significantly affected public health, the worldwide economy, and social life. Metal organic frameworks (MOFs) are currently being implemented in biosensors for rapid and accurate detection of viruses thanks to their exceptional properties. This research aims to develop a Zeolitic Imidazolate Framework-8 (ZIF-8) based fluorescent biosensor for facile and rapid COVID-19 RNA sequence detection. ZIF-8 was characterized using several tests, such as FT-IR, TGA, and PXRD, to examine the MOF’s crystalline structure and thermal stability. The results demonstrated high crystallinity and thermal stability up to a temperature of 550 °C. The experimental study showed that ZIF-8 is an excellent fluorescence quencher, with 78.39% quenching efficiency. Analyzing the adsorption mechanism of probe DNA into ZIF-8 revealed that they can form electrostatic and π–π stacking interactions, forming a P-DNA@ZIF-8 complex and that PET is more dominant than FRET in the quenching mechanism. This ZIF-8 biosensing platform showed high sensitivity towards COVID-19 RNA with an ultra-low limit of detection of 6.24 pM, a rapid detection time of 8 min, and high selectivity to COVID-19 RNA. Indeed, ZIF-8 experienced much lower fluorescence recovery when tested on two mismatched RNAs. The experimental results show the potential use of ZIF-8 as a novel biosensor for a rapid and sensitive COVID-19 diagnosis.

Synthesis and Characterization of Self-Dispersion Monodisperse Silica-Based Functional Nanoparticles for Enhanced Oil Recovery (EOR) in Low-Permeability Reservoirs

A controllable particle size mono-dispersing nanofluid system has been developed to address the challenges of low porosity and low-permeability in low to ultra-low-permeability reservoirs. This system combines high dispersion stability with enhanced oil recovery performance, and its effectiveness in improving recovery rates in low-permeability reservoirs, where conventional chemical flooding is ineffective, has been well demonstrated. Using the in situ method to prepare monodispersed nano-silica particles, the effects of the water concentration, ammonia concentration, and silica precursor concentration on the morphology, particle size, and formation time of the silica spherical particles were analyzed. Building on this foundation, a partially hydrophobic modified nano-silica oil displacement fluid was synthesized in situ. The system’s dispersion stability, ability to reduce oil-water interfacial tension, and capacity to alter rock wettability were evaluated. Core physical models were used to evaluate the oil displacement efficiency and the permeability applicability limits of the self-dispersing nano-silica oil displacement system. The experiments confirmed that the particle size distribution of the self-dispersing nano-silica oil displacement system can be controlled within a range of 10 nm to 300 nm. The nanofluids exhibited excellent stability, effectively altering the rock wettability from oil-wet to water-wet and reducing the oil-water interfacial tension to approximately 10−1 mN/m. The nano-displacement system increased the recovery rate of the low permeability reservoirs by more than 17%. The in situ modification method used to prepare these self-dispersing nanoparticles provides valuable insights for synergistic enhancement of recovery when combined with other systems, such as surfactants and CO2. This approach also opens up new possibilities and drives further development in the field of nano-enhanced oil recovery chemistry.

Biochar Regulates the Humification of Kitchen Waste and the Effects of the Humic Acid Structure of Products on Black Soil

Kitchen waste is a misplaced resource that is characterized by a high organic matter content, high water content, and a tendency to rot easily. Biochar is a black solid substance produced under high-temperature, anaerobic conditions using agricultural organic wastes as the raw material. It possesses a large specific surface area, a loose and porous structure, and functional groups, which confer high thermal stability and strong adsorption capabilities. However, little is known about how humic products made from biochar affect the composition and structure of soil humus. To solve the above problems, this study carried out a two-year outdoor field experiment by means of element analysis, infrared spectroscopy, and differential thermal analysis (0.4 kg/m2 (W4), 0.8 kg/m2 (W8), 1.2 kg/m2 (W12), 1.6 kg/m2 (W16), and 2.0 kg/m2 (W20)); CK was the blank control (no application). The samples were collected one year and two years after they returned to the field. The results showed that the application of organic materials facilitated the accumulation of soil organic carbon (SOC) and increased the total nitrogen (TN) content. The highest SOC content in the W20 treatment was 12.39 g/kg and 14.67 g/kg in one and two years, respectively. The maximum relative HA content in the W20 treatment was 22.99% one year after returning to the field. The PQ value (the ratio of HA/(fulvic acid (FA) + HA)) for the W20 treatment was 88.21%. The W20 treatment greatly increased the SOC and humus carbon contents. Compared with the CK treatment, all the organic materials applied for one year improved the structure of the humic acid to varying degrees, increased the degree of oxidation, reduced the degree of condensation and thermal stability of the HA in the soil, and gradually simplified the structure of the humic acid; among all the treatments, the W20 treatment had the greatest effect.