Local application of silver nitrate as an adjuvant treatment before deep lamellar keratoplasty for fungal keratitis poorly responsive to medical treatment

ObjectiveThe purpose of this study is to evaluate the efficacy and safety of the local application of silver nitrate (LASN) as an adjuvant treatment before deep lamellar keratoplasty (DLKP) for fungal keratitis responding poorly to medical treatment.MethodsA total of 12 patients (12 eyes) with fungal keratitis responding poorly to medical treatment (for at least 2 weeks) were included. LASN was performed using 2% silver nitrate, the ulcer was cleaned and debrided, and then, the silver nitrate cotton stick was applied to the surface of the ulcer for a few seconds. The effect of LASN was recorded. The number of hyphae before and after treatment was determined by confocal microscope. After the condition of the ulcer improved, DLKP was performed. Fungal recurrence, best-corrected visual acuity (BCVA), loose sutures, and endothelial cell density (ECD) were recorded in detail.ResultsClinical resolution of corneal infiltration and edema was observed, and the ulcer boundary became clear in all 12 patients after 7–9 days of LASN. Confocal microscopy showed that the number of hyphae was significantly reduced. Ocular pain peaked on days 1 and 2 after treatment, and 9 patients (75%, day 1) and 1 patient (8.3%, day 2) required oral pain medication. During the follow-up period after DLKP, no fungal recurrence and loose sutures were observed. After the operation, the BCVA of all patients improved. The mean corneal ECD was 2,166.83 ± 119.75 cells/mm2.ConclusionThe LASN was safe and effective and can be well tolerated by patients. Eye pain can be relieved quickly. LASN as an adjuvant treatment before DLKP might be a promising therapeutic strategy

Gas protection of two-dimensional nanomaterials from high-energy impacts

Two-dimensional (2D) materials can be produced using ball milling with the help of liquid surfactants or solid exfoliation agents, as ball milling of bulk precursor materials usually produces nanosized particles because of high-energy impacts. Post-milling treatment is thus needed to purify the nanosheets. We show here that nanosheets of graphene, BN, and MoS2 can be produced by ball milling of their bulk crystals in the presence of ammonia or a hydrocarbon ethylene gas and the obtained nanosheets remain flat and maintain their single-crystalline structure with low defects density even after a long period of time; post-milling treatment is not needed. This study does not just demonstrate production of nanosheets using ball milling, but reveals surprising indestructible behaviour of 2D nanomaterials in ammonia or hydrocarbon gas under the high-energy impacts; in other milling atmospheres such as air, nitrogen or argon the same milling treatment produces nanosized particles. A systematic study reveals chemisorption of ammonia and hydrocarbon gases and chemical reactions occurring at defect sites, which heal the defects by saturating the dangling bonds. Density functional theory was used to understand the mechanism of mechanochemical reactions. Ball milling in ammonia or hydrocarbon is promising for mass-production of pure nanosheets

Controllable CO2 Electrocatalytic Reduction via Ferroelectric Switching on Single Atom Anchored In2Se3 Monolayer

Efficient and selective CO2 electroreduction into chemical fuels promises to alleviate environmental pollution and energy crisis, but it relies on catalysts with controllable product selectivity and reaction path. Here, by means of first-principles calculations, we identify six ferroelectric catalysts comprising transition-metal atoms anchored on In2Se3 monolayer, whose catalytic performance can be controlled by ferroelectric switching based on adjusted d-band center and occupation of supported metal atoms. The polarization dependent activation allows effective control of the limiting potential of CO2 reduction on TM@In2Se3 (TM = Ni, Pd, Rh, Nb, and Re) as well as the reaction paths and final products on Nb@In2Se3 and Re@In2Se3. Interestingly, the ferroelectric switching can even reactivate the stuck catalytic CO2 reduction on Zr@In2Se3. The fairly low limiting potential and the unique ferroelectric controllable CO2 catalytic performance on atomically dispersed transition-metals on In2Se3 clearly distinguish them from traditional single atom catalysts, and open an avenue toward improving catalytic activity and selectivity for efficient and controllable electrochemical CO2 reduction reaction

Enzymatic interesterification of palm stearin and palm olein blend catalyzed by sn-1,3-specific lipase: interesterification degree, acyl migration, and physical properties

Acyl migration of fatty acid at sn-2 is often observed alongside enzymatic interesterification (EIE), causing the loss of lipase selectivity toward the acyl group at sn-1,3. In this study, an oil blend consisting of palm stearin (PST) and palm olein (POL) was interesterified via a chemical interesterification (CIE) and enzymatic method using a packed bed reactor. Characterization in terms of the triacylglycerol (TAG) compositions, sn-2 fatty acid distributions, and solid fat content profiles was performed. In comparison to that of CIE fats, EIE fats showed different modification effects on the solid fat content. Under similar reaction conditions, different interesterification degrees (IDs) were obtained according to the various blend ratios. Using the same mass ratio of substrates (POL/PST of 9:1), the EIE reaction time and temperature affected the ID and the change in the fatty acyl group at the sn-2 position. Under the reaction time of 46 min, an ID of 94.41% was acquired, while at 80 °C, the degree of acyl migration at sn-2 was 92.87%. EIE with high acyl migration exhibited a lower crystallization rate than that of EIE with low acyl migration. However, the effect of acyl migration on crystal polymorphism and oxidative stability was insignificant. Outcomes from this study are meaningful for the establishment of a theoretical basis for a controlled positional-specific EIE that is catalyzed by sn-1,3-specific lipase

Life Prediction of Battery Using a Neural Gaussian Process with Early Discharge Characteristics

The state of health (SOH) prediction of lithium-ion batteries (LIBs) is of crucial importance for the normal operation of the battery system. In this paper, a new method for cycle life and full life cycle capacity prediction is proposed, which combines the early discharge characteristics with the neural Gaussian process (NGP) model. The cycle data sets of commercial LiFePO4(LFP)/graphite cells generated under different operating conditions are analyzed, and the power characteristic P is extracted from the voltage and current curves of the early cycles. A Pearson correlation analysis shows that there is a strong correlation between P and cycle life. Our model achieves 8.8% test error for predicting cycle life using degradation data for the 20th to 110th cycles. Based on the predicted cycle life, capacity degradation curves for the whole life cycle of the cells are predicted. In addition, the NGP method, combined with power characteristics, is compared with other classical methods for predicting the remaining useful life (RUL) of LIBs. The results demonstrate that the proposed prediction method of cycle life and capacity has better battery life and capacity prediction. This work highlights the use of early discharge characteristics to predict battery performance, and shows the application prospect in accelerating the development of electrode materials and optimizing battery management systems (BMS)

Life Prediction of Battery Using a Neural Gaussian Process with Early Discharge Characteristics

The state of health (SOH) prediction of lithium-ion batteries (LIBs) is of crucial importance for the normal operation of the battery system. In this paper, a new method for cycle life and full life cycle capacity prediction is proposed, which combines the early discharge characteristics with the neural Gaussian process (NGP) model. The cycle data sets of commercial LiFePO4(LFP)/graphite cells generated under different operating conditions are analyzed, and the power characteristic P is extracted from the voltage and current curves of the early cycles. A Pearson correlation analysis shows that there is a strong correlation between P and cycle life. Our model achieves 8.8% test error for predicting cycle life using degradation data for the 20th to 110th cycles. Based on the predicted cycle life, capacity degradation curves for the whole life cycle of the cells are predicted. In addition, the NGP method, combined with power characteristics, is compared with other classical methods for predicting the remaining useful life (RUL) of LIBs. The results demonstrate that the proposed prediction method of cycle life and capacity has better battery life and capacity prediction. This work highlights the use of early discharge characteristics to predict battery performance, and shows the application prospect in accelerating the development of electrode materials and optimizing battery management systems (BMS)

Structural and electronic properties of layered arsenic and antimony arsenide

Layered materials exhibit intriguing electronic characteristics and the search for new types of two-dimensional (2D) structures is of importance for future device fabrication. Using state-of-art first principle calculations, we identify and characterize the structural and electronic properties of two 2D layered arsenic materials, namely, arsenic and its alloy AsSb. The stable 2D structural configuration of arsenic is confirmed to be the low-buckled two-dimensional hexagonal structure by phonon and binding energy calculations. The monolayer exhibits indirect semiconducting properties with gap around 1.5 eV (corrected to 2.2 eV by hybrid function), which can be modulated into a direct semiconductor within a small amount of tensile strain. These semiconducting properties are preserved when cutting into 1D nanoribbons, but the band gap is edge dependent. It is interesting to find that an indirect to direct gap transition can be achieved under strain modulation of the armchair ribbon. Essentially the same phenomena can be found in layered AsSb, except a weak Rashba induced band splitting is present in AsSb due to the nonsymmetric structure and spin orbit coupling. When an additional layer is added on the top, a semiconductor–metal transition will occur. The findings here broaden the family of 2D materials beyond graphene and transition metal dichalcogenides and provide useful information for experimental fabrication of new layered materials with possible application in optoelectronics