Tianjin University of Science and Technology

Hydrogen evolution reaction (HER) in alkaline medium is currently a point of focus for sustainable development of hydrogen as an alternative clean fuel for various energy systems, but suffers from sluggish reaction kinetics due to additional water dissociation step. So, the state-of-the-art catalysts performing well in acidic media lose considerable catalytic performance in alkaline media. This review summarizes the recent developments to overcome the kinetics issues of alkaline HER, synthesis of materials with modified morphologies, and electronic structures to tune the active sites and their applications as efficient catalysts for HER. It first explains the fundamentals and electrochemistry of HER and then outlines the requirements for an efficient and stable catalyst in alkaline medium. The challenges with alkaline HER and limitation with the electrocatalysts along with prospective solutions are then highlighted. It further describes the synthesis methods of advanced nanostructures based on carbon, noble, and inexpensive metals and their heterogeneous structures. These heterogeneous structures provide some ideal systems for analyzing the role of structure and synergy on alkaline HER catalysis. At the end, it provides the concluding remarks and future perspectives that can be helpful for tuning the catalysts active-sites with improved electrochemical efficiencies in future.

Abstract Starch retrogradation is a process in which disaggregated amylose and amylopectin chains in a gelatinized starch paste reassociate to form more ordered structures. Starch retrogradation has been the subject of intensive research over the last 50 years, mainly due to its detrimental effect on the sensory and storage qualities of many starchy foods. However, starch retrogadation is desirable for some starchy food products in terms of textural and nutritional properties. To better understand the effect of starch retrogradation on the quality of starchy foods, measurement methods of starch retrogradation and factors that influence starch retrogradation have been studied extensively. This article provides a comprehensive review of starch retrogradation including the definition of the process, molecular mechanisms of how it occurs, and measurement methods and factors that influence starch retrogradation. The review also discusses the effect of retrogradation on the in vitro enzyme digestibility of starch. Spectroscopic methods such as FTIR and Raman are considered to be very promising in characterizing starch retrogradation at a molecular level, although more studies are needed in the future.

Lactic acid bacteria are a kind of microorganisms that can ferment carbohydrates to produce lactic acid, and are currently widely used in the fermented food industry. In recent years, with the excellent role of lactic acid bacteria in the food industry and probiotic functions, their microbial metabolic characteristics have also attracted more attention. Lactic acid bacteria can decompose macromolecular substances in food, including degradation of indigestible polysaccharides and transformation of undesirable flavor substances. Meanwhile, they can also produce a variety of products including short-chain fatty acids, amines, bacteriocins, vitamins and exopolysaccharides during metabolism. Based on the above-mentioned metabolic characteristics, lactic acid bacteria have shown a variety of expanded applications in the food industry. On the one hand, they are used to improve the flavor of fermented foods, increase the nutrition of foods, reduce harmful substances, increase shelf life, and so on. On the other hand, they can be used as probiotics to promote health in the body. This article reviews and prospects the important metabolites in the expanded application of lactic acid bacteria from the perspective of bioengineering and biotechnology.

Abstract Lithium–sulfur (Li–S) battery has emerged as one of the most promising next‐generation energy‐storage systems. However, the shuttle effect greatly reduces the battery cycle life and sulfur utilization, which is great deterrent to its practical use. This paper reviews the tremendous efforts that are made to find a remedy for this problem, mostly through physical or chemical confinement of the lithium polysulfides (LiPSs). Intrinsically, this “confinement” has a relatively limited effect on improving the battery performance because in most cases, the LiPSs are “passively” blocked and cannot be reused. Thus, this strategy becomes less effective with a high sulfur loading and ultralong cycling. A more “positive” method that not only traps but also increases the subsequent conversion of LiPSs back to lithium sulfides is urgently needed to fundamentally solve the shuttle effect. Here, recent advances on catalytic effects in increasing the rate of conversion of soluble long‐chain LiPSs to insoluble short‐chain Li 2 S 2 /Li 2 S, and vice versa, are reviewed, and the roles of noble metals, metal oxides, metal sulfides, metal nitrides, and some metal‐free materials in this process are highlighted. Challenges and potential solutions for the design of catalytic cathodes and interlayers in Li–S battery are discussed in detail.

With the increasing demand for wearable electronics (such as smartwatch equipment, wearable health monitoring systems, and human-robot interface units), flexible energy storage systems with eco-friendly, low-cost, multifunctional characteristics, and high electrochemical performances are imperative to be constructed. Nanocellulose with sustainable natural abundance, superb properties, and unique structures has emerged as a promising nanomaterial, which shows significant potential for fabricating functional energy storage systems. This review is intended to provide novel perspectives on the combination of nanocellulose with other electrochemical materials to design and fabricate nanocellulose-based flexible composites for advanced energy storage devices. First, the unique structural characteristics and properties of nanocellulose are briefly introduced. Second, the structure-property-application relationships of these composites are addressed to optimize their performances from the perspective of processing technologies and micro/nano-interface structure. Next, the recent specific applications of nanocellulose-based composites, ranging from flexible lithium-ion batteries and electrochemical supercapacitors to emerging electrochemical energy storage devices, such as lithium-sulfur batteries, sodium-ion batteries, and zinc-ion batteries, are comprehensively discussed. Finally, the current challenges and future developments in nanocellulose-based composites for the next generation of flexible energy storage systems are proposed.

Starch is the most important glycemic carbohydrate in foods. The relationship between the rate and extent of starch digestion to produce glucose for absorption into the bloodstream and risk factors for diet-related diseases is of considerable nutritional interest. Native starch is attacked slowly by enzymes, but after hydrothermal processing its susceptibility to enzymatic breakdown is greatly increased. Most starch consumed by humans has undergone some form of processing or cooking, which causes native starch granules to gelatinize, followed by retrogradation on cooling. The extent of gelatinization and retrogradation are major determinants of the susceptibility of starch to enzymatic digestion and its functional properties for food processing. The type and extent of changes that occur in starch as a result of gelatinization, pasting and retrogradation are determined by the type of the starch, processing and storage conditions. A mechanistic understanding of the molecular disassembly of starch granules during gelatinization is critical to explaining the effects of processing or cooking on starch digestibility. This review focuses on the molecular disassembly of starch granules during starch gelatinization over a wide range of water levels, and its consequential effect on in vitro starch digestibility and in vivo glycemic index.

Abstract The detrimental shuttle effect in lithium–sulfur batteries mainly results from the mobility of soluble polysulfide intermediates and their sluggish conversion kinetics. Herein, presented is a multifunctional catalyst with the merits of strong polysulfides adsorption ability, superior polysulfides conversion activity, high specific surface area, and electron conductivity by in situ crafting of the TiO 2 ‐MXene (Ti 3 C 2 T x ) heterostructures. The uniformly distributed TiO 2 on MXene sheets act as capturing centers to immobilize polysulfides, the hetero‐interface ensures rapid diffusion of anchored polysulfides from TiO 2 to MXene, and the oxygen‐terminated MXene surface is endowed with high catalytic activity toward polysulfide conversion. The improved lithium–sulfur batteries deliver 800 mAh g −1 at 2 C and an ultralow capacity decay of 0.028% per cycle over 1000 cycles at 2 C. Even with a high sulfur loading of 5.1 mg cm −2 , the capacity retention of 93% after 200 cycles is still maintained. This work sheds new insights into the design of high‐performance catalysts with manipulated chemical components and tailored surface chemistry to regulate polysulfides in Li–S batteries.

In this paper, we explore the problem of multiview subspace clustering. We introduce a low-rank tensor constraint to explore the complementary information from multiple views and, accordingly, establish a novel method called Low-rank Tensor constrained Multiview Subspace Clustering (LT-MSC). Our method regards the subspace representation matrices of different views as a tensor, which captures dexterously the high order correlations underlying multiview data. Then the tensor is equipped with a low-rank constraint, which models elegantly the cross information among different views, reduces effectually the redundancy of the learned subspace representations, and improves the accuracy of clustering as well. The inference process of the affinity matrix for clustering is formulated as a tensor nuclear norm minimization problem, constrained with an additional L2,1-norm regularizer and some linear equalities. The minimization problem is convex and thus can be solved efficiently by an Augmented Lagrangian Alternating Direction Minimization (AL-ADM) method. Extensive experimental results on four benchmark datasets show the effectiveness of our proposed LT-MSC method.

Physical interactions often occur between major food components during food processing. These interactions may involve starch, lipids, and proteins forming V-type starch-lipid complexes or ternary starch-lipid-protein complexes of larger molecular size and greater structural order. Complexes between starch and lipids have been the subject of intensive research for over half a century, whereas the study of starch-lipid-protein complexes is a relatively new field with only a limited amount of knowledge being gained so far. The formation of these complexes can significantly affect the functional and nutritional properties of finished food products in terms of flavor, texture, shelf life, and digestibility. This article provides a comprehensive review of starch-lipid and starch-lipid-protein complexes, including their classification, factors affecting their formation and structure, and preparative and analytical methods. The review also considers how complexes affect the physicochemical and functional properties of starch, including digestibility, and potential applications in the food industry.

Abstract Developing superelastic and superhydrophilic carbon aerogels with intriguing mechanical properties is urgently desired for achieving promising performances in highly compressive supercapacitors and strain sensors. Herein, based on synergistic hydrogen bonding, electrostatic interaction, and π–π interaction within regularly arranged layered porous structures, conductive carbon aerogels with cellulose nanofibrils (CNF), carbon nanotubes (CNT) and reduced graphene oxide (RGO) are developed via bidirectional freezing and subsequent annealing. Benefiting from the porous architecture and high surface roughness, CNF/CNT/RGO carbon aerogels exhibit ultralow density (2.64 mg cm –3 ) and superhydrophilicity (water contact angle ≈0° at 106 ms). The honeycomb‐like ordered porous structure can efficiently transfer stress in the entire microstructure, thereby endowing carbon aerogels with high compressibility and extraordinary fatigue resistance (10,000 cycles at 50% strain). These aerogels can be assembled into compressive solid‐state symmetric supercapacitors showing excellent area capacitance (109.4 mF cm –2 at 0.4 mA cm –2 ) and superior long cycle compression performance (88% after 5000 cycles at compressive strain of 50%). Furthermore, the aerogels reveal good linear sensitivity ( S = 5.61 kPa –1 ) and accurately capture human bio‐signals as strain sensors. It is expected that such CNF/CNT/RGO carbon aerogels will provide a novel multifunctional platform for wearable electronics, electronic skin, and human motion monitoring.

In this paper, we propose a novel Latent Multi-view Subspace Clustering (LMSC) method, which clusters data points with latent representation and simultaneously explores underlying complementary information from multiple views. Unlike most existing single view subspace clustering methods that reconstruct data points using original features, our method seeks the underlying latent representation and simultaneously performs data reconstruction based on the learned latent representation. With the complementarity of multiple views, the latent representation could depict data themselves more comprehensively than each single view individually, accordingly makes subspace representation more accurate and robust as well. The proposed method is intuitive and can be optimized efficiently by using the Augmented Lagrangian Multiplier with Alternating Direction Minimization (ALM-ADM) algorithm. Extensive experiments on benchmark datasets have validated the effectiveness of our proposed method.

N 6 -Methyladenosine (m 6 A) refers to methylation modification of the adenosine nucleotide acid at the nitrogen-6 position. Many conventional computational methods for identifying N 6 -methyladenosine sites are limited by the small amount of data available. Taking advantage of the thousands of m 6 A sites detected by high-throughput sequencing, it is now possible to discover the characteristics of m 6 A sequences using deep learning techniques. To the best of our knowledge, our work is the first attempt to use word embedding and deep neural networks for m 6 A prediction from mRNA sequences. Using four deep neural networks, we developed a model inferred from a larger sequence shifting window that can predict m 6 A accurately and robustly. Four prediction schemes were built with various RNA sequence representations and optimized convolutional neural networks. The soft voting results from the four deep networks were shown to outperform all of the state-of-the-art methods. We evaluated these predictors mentioned above on a rigorous independent test data set and proved that our proposed method outperforms the state-of-the-art predictors. The training, independent, and cross-species testing data sets are much larger than in previous studies, which could help to avoid the problem of overfitting. Furthermore, an online prediction web server implementing the four proposed predictors has been built and is available at http://server.malab.cn/Gene2vec/ .

Abstract In recent decades, flexible and wearable devices have been extensively investigated due to their promising applications in portable mobile electronics and human motion monitoring. MXene, a novel growing family of 2D nanomaterials, demonstrates superiorities such as outstanding electrical conductivity, abundant terminal groups, unique layered‐structure, large surface area, and hydrophilicity, making it to be a potential candidate material for flexible and wearable devices. Numerous pioneering works are devoted to develop flexible MXene‐based composites with various functions and designed structures. Therefore, the latest progress of the flexible MXene‐based composites for wearable devices is summarized in this review, focusing on the preparation strategies, working mechanisms, performances, and applications in sensors, supercapacitors, and electromagnetic interference shielding materials. Moreover, the current challenges and future outlooks are also discussed.

Due to its clear inherited backgrounds as well as simple and diverse genetic manipulation systems, Bacillus subtilis is the key Gram-positive model bacterium for studies on physiology and metabolism. Furthermore, due to its highly efficient protein secretion system and adaptable metabolism, it has been widely used as a cell factory for microbial production of chemicals, enzymes, and antimicrobial materials for industry, agriculture, and medicine. In this mini-review, we first summarize the basic genetic manipulation tools and expression systems for this bacterium, including traditional methods and novel engineering systems. Secondly, we briefly introduce its applications in the production of chemicals and enzymes, and summarize its advantages, mainly focusing on some noteworthy products and recent progress in the engineering of B. subtilis. Finally, this review also covers applications such as microbial additives and antimicrobials, as well as biofilm systems and spore formation. We hope to provide an overview for novice researchers in this area, offering them a better understanding of B. subtilis and its applications.

Abstract Oxygen evolution reaction (OER) plays a vital role in many energy conversion and storage processes including electrochemical water splitting for the production of hydrogen and carbon dioxide reduction to value‐added chemicals. IrO 2 and RuO 2 , known as the state‐of‐the‐art OER electrocatalysts, are severely limited by the high cost and low earth abundance of these noble metals. Developing noble‐metal‐free OER electrocatalysts with high performance has been in great demand. In this review, recent advances in the design and synthesis of noble‐metal‐free OER electrocatalysts including Ni, Co, Fe, Mn‐based hydroxides/oxyhydroxides, oxides, chalcogenides, nitrides, phosphides, and metal‐free compounds in alkaline, neutral as well as acidic electrolytes are summarized. Perspectives are also provided on the fabrication, evaluation of OER electrocatalysts and correlations between the structures of the electrocatalysts and their OER activities.

Abstract Photocatalysis has been regarded as a promising strategy for hydrogen production and high-value-added chemicals synthesis, in which the activity of photocatalyst depends significantly on their electronic structures, however the effect of electron spin polarization has been rarely considered. Here we report a controllable method to manipulate its electron spin polarization by tuning the concentration of Ti vacancies. The characterizations confirm the emergence of spatial spin polarization among Ti-defected TiO 2 , which promotes the efficiency of charge separation and surface reaction via the parallel alignment of electron spin orientation. Specifically, Ti 0.936 O 2 , possessing intensive spin polarization, performs 20-fold increased photocatalytic hydrogen evolution and 8-fold increased phenol photodegradation rates, compared with stoichiometric TiO 2 . Notably, we further observed the positive effect of external magnetic fields on photocatalytic activity of spin-polarized TiO 2 , attributed to the enhanced electron-spin parallel alignment. This work may create the opportunity for tailoring the spin-dependent electronic structures in metal oxides.

Abstract Covalent organic frameworks (COFs) hold great promise in molecular separations owing to their robust, ordered and tunable porous network structures. Currently, the pore size of COFs is usually much larger than most small molecules. Meanwhile, the weak interlamellar interaction between COF nanosheets impedes the preparation of defect-free membranes. Herein, we report a series of COF membranes through a mixed-dimensional assembly of 2D COF nanosheets and 1D cellulose nanofibers (CNFs). The pore size of 0.45–1.0 nm is acquired from the sheltering effect of CNFs, rendering membranes precise molecular sieving ability, besides the multiple interactions between COFs and CNFs elevate membrane stability. Accordingly, the membranes exhibit a flux of 8.53 kg m −2 h −1 with a separation factor of 3876 for n-butanol dehydration, and high permeance of 42.8 L m −2 h −1 bar −1 with a rejection of 96.8% for Na 2 SO 4 removal. Our mixed-dimensional design may inspire the fabrication and application of COF membranes.

Intensive research efforts have been pursued to remove arsenic (As) contamination from water with an intention to provide potable water to millions of people living in different countries. Recent studies have revealed that iron-based adsorbents, which are non-toxic, low cost, and easily accessible in large quantities, offer promising results for arsenic removal from water. This review is focused on the removal of arsenic from water using iron-based materials such as iron-based nanoparticles, iron-based layered double hydroxides (LDHs), zero-valent iron (ZVI), iron-doped activated carbon, iron-doped polymer/biomass materials, iron-doped inorganic minerals, and iron-containing combined metal oxides. This review also discusses readily available low-cost adsorbents such as natural cellulose materials, bio-wastes, and soils enriched with iron. Details on mathematical models dealing with adsorption, including thermodynamics, kinetics, and mass transfer process, are also discussed. For elucidating the adsorption mechanisms of specific adsorption of arsenic on the iron-based adsorbent, X-ray photoelectron spectroscopy (XPS) and X-ray absorption spectroscopy (XAS) are frequently used. Overall, iron-based adsorbents offer significant potential towards developing adsorbents for arsenic removal from water.

Acid hydrolysis is an important chemical modification that can significantly change the structural and functional properties of starch without disrupting its granular morphology. A deep understanding of the effect of acid hydrolysis on starch structure and functionality is of great importance for starch scientific research and its industrial applications. During acid hydrolysis, amorphous regions are hydrolyzed preferentially, which enhances the crystallinity and double helical content of acid hydrolyzed starch. This review discusses current understanding of the effect of acid hydrolysis on starch structure and functionality. The effects of acid hydrolysis on amylose content, chain length distribution of amylopectin molecules, molecular and crystalline organization (including lamellar structure) and granular morphology are considered. Functional properties discussed include swelling power, gelatinization, retrogradation, pasting, gel texture, and in vitro enzyme digestibility. The paper also highlights some promising applications of acid hydrolyzed starch (starch nanocrystals) in the preparation of biodegradable nanocomposites, bio-hydrogen, and slowly digestible starch-based healthy foods.

Solar energy provides an alternative, sustainable, and clean source of energy to meet the global energy demands without extra carbon emissions. However, the utilization efficiency of sunlight via most traditional photocatalytic processes remains relatively low. Photothermal catalysis, combining the advantages of photocatalysis and thermocatalysis, has emerged as a new fast-growing research area. In this review, we first discuss three different mechanisms of photothermal effects and then describe the functioning principles of photothermal catalysis. We categorize the photothermal catalysts into three types based on their specific coupling modes of thermochemical and photochemical pathways. We also illustrate the catalyst design strategies and characterization methods for photothermal catalysis. As specific examples of applications, we summarize the recent research progress on the photothermal catalytic reactions for CO2 conversion, CH4 activation, NH3 synthesis, and water splitting. Last, we present the challenges and perspectives in this field, as a guide for future development in photothermal catalysis.