Zeolites are essential crystalline materials for catalysis and molecular separations, yet their targeted synthesis remains challenging because framework selection is governed by coupled solution chemistry, organic structure-directing agents, solvent environments, and crystallization conditions. Here we develop a data-driven framework that integrates state-of-the-art synthesis parameters with solution physical properties derived from molecular simulations to predict zeolite crystallization outcomes. Across 366 literature syntheses, the model achieves 96.4% accuracy in classifying 20 zeolite frameworks and 87.7% accuracy in distinguishing four structural aperture classes, outperforming composition-only baselines. Model interpretation reveals that solution density and dielectric constant provide independent information, with opposite effects on the formation of small- and large-aperture zeolites. These findings show that framework selection is encoded not only in chemical composition but also in emergent solution properties, offering a physically informed strategy for predictive zeolite synthesis.
Directly resolving the atomic-scale dynamics of phase transitions in alkali halide crystals after nucleation from saturated solutions remains challenging but is essential for understanding crystal growth. Here, in situ liquid-phase transmission electron microscopy (LP-TEM) was used to visualize the early stage structural evolution of KCl in aqueous solution. We observe the dissolution of [110]-oriented KCl domains followed by reprecipitation into [100]-oriented domains. Time-resolved radial distribution function (RDF) analysis derived from sequential fast Fourier transform (FFT) diffractograms quantitatively maps the kinetic pathway of this transformation. A previously unreported metastable hexagonal phase (h-KCl) is identified as a transient intermediate connecting two cubic domains. These results provide direct evidence for a cubic-hexagonal-cubic transformation pathway in a prototypical ionic crystal and reveal how nonequilibrium intermediates govern solution-mediated solid-state phase transitions.
Organic solar cells (OSCs) continue to show rapid performance improvements. The interest in OSCs is nurtured by the prospects of a sustainable technology that allows for low-cost, large-area solution processability. In reality, most OSCs still rely on thermally evaporated metal electrodes, such as silver or gold. Here, we demonstrate the first OSCs utilizing a fully solution-processed, doctor-bladed carbon top electrode as a low-cost and recyclable alternative to established metal contacts. A robust electron transport layer (ETL) architecture comprising a thin film of solution-processed aluminum-doped zinc oxide nanoparticles (AZO-NPs) and a 20 nm-thick tin oxide (SnOx) layer, grown by atomic layer deposition (ALD) at 80 °C, is introduced to protect the underlying organic layers against the otherwise detrimental solvent from the carbon paste. The AZO-NP layer is of critical importance to improve the nucleation of the ALD-SnOx layer and afford the necessary solvent barrier properties. To improve the electronic interface between the carbon top electrode and the ETL, we inserted an ultrathin indium oxide (InOx) layer (1.5 nm), grown in the same ALD process. The metallic properties of the ALD-InOx improved reproducibility, and we also confirmed that the 2 orders of magnitude lower sheet resistance of ALD-InOx (5 × 106 Ω/sq) vs ALD-SnOx (5 × 108 Ω/sq) enabled sufficient lateral transport of photogenerated electrons to be extracted by the carbon top electrode, that is found to only make pointlike contact to the adjacent ETL. The resulting OSCs with the doctor-bladed carbon top electrode achieved an encouraging power conversion efficiency of 11%, which provides a very promising direction toward sustainable, scalable, and resource-efficient OSC manufacturing.
Branch water release and radial exchange influence drought responses. Although mechanistic models describe radial hydraulic and storage dynamics, experimental quantification of hydraulic capacitance (C) and radial resistance (Rr) across broad ranges of xylem water-potential (Ψx), particularly under severe dehydration, remains limited. We quantified how C and Rr vary with Ψx in Populus alba, assessed the value of coupling controlled osmotic dehydration with high-resolution dendrometry, and evaluated cellular damage and bud viability across increasing dehydration levels. Branch segments were subjected to stepwise, experimentally induced dehydration by perfusion with D-sorbitol solutions (-1 to -4 MPa) to impose stable and controlled Ψx. Branch diameter dynamics and equilibration plateaus were used to estimate C and Rr, and diameter-derived pressure-volume curves were fitted using the Sureau model. Electrolyte leakage (EL) and bud development were monitored to assess injury and recovery capacity at the organ level. D-sorbitol equilibrated rapidly along the xylem with limited bark infiltration, and stepwise decreases in Ψx induced characteristic diameter contractions enabling robust extraction of C and Rr. Both traits varied with Ψx: C peaked at intermediate Ψx (-1 to -2 MPa) and declined under severe dehydration, while Rr increased steadily as Ψx decreased. EL increased and buds failed to resume growth below -2 MPa. Controlled osmotic dehydration combined with high-resolution dendrometry enables precise quantification of C(Ψx) and Rr(Ψx) and reveals physiologically meaningful thresholds associated with cellular injury and loss of recovery capacity at the organ level, providing a useful framework for dehydration-tolerance phenotyping.
This is a protocol for a Cochrane Review (intervention). The objectives are as follows: To evaluate the benefits and harms of different tumescent solutions for adults with lower limb varicose veins undergoing thermal ablation (laser, radiofrequency, microwave, or steam ablation), compared with other tumescent formulations or no tumescent anaesthesia.
Substance use disorders (SUDs) are a persistent health issue in the United States that demand interdisciplinary strategies. A major obstacle has been turning scientific innovations into successful commercial products. Our aim was to teach technology commercialization to a national group of SUD researchers, boosting their ability to develop and implement effective SUD solutions. With the Office of Translational Initiatives and Program Innovations at the National Institute on Drug Abuse (NIDA), we created a 7-week program at Johns Hopkins Carey Business School called Innovations for SUD (I4SUD). Participants visited Baltimore for 3.5 days of in-person lectures, workshops, networking, and a visit to local SUD treatment centers. Online were 7 asynchronous modules (3-4 hours each), 3 1.5-hour synchronous sessions, and office hours. Each year, I4SUD ended with a 3-hour, 2-round "pitch" competition where one innovation received a $10,000 award. We report the evaluation of the first 3 cohorts. Out of 265 applicants, we enrolled 100 participants from 45 academic institutions from 2023 to 2025. Most had limited experience with basic technology commercialization concepts but improved significantly across 5 core learning objectives in pre- and post-assessments. Over 75% were motivated to seek additional funding at the program's conclusion. Participants rated highest the clinic site visits, workshops on defining unmet needs, office hours with NIDA and I4SUD experts, and pitch sessions. I4SUD provides a successful model of entrepreneurship education for SUD scientists that can be adapted to other settings, helping innovations reach the market and potentially impact people with SUDs.
This study addresses the critical challenge associated with the removal of reactive yellow dyes from aqueous media and industrial wastewater streams. Owing to their pronounced chemical stability and resistance to conventional degradation techniques, such dyes constitute a substantial environmental concern. In this context, the present work investigates the efficacy of unmodified magnetite nanoparticles (plate-like rounded structures 6-23 nm in size), synthesised under rigorously controlled conditions and well characterised, as high-performance adsorbents for the sequestration of persistent dye species exhibiting limited susceptibility to rapid degradation. The effects of key operational parameters on dye removal efficiency were systematically evaluated to establish optimal treatment conditions. Complete removal of reactive yellow dye (100%) was achieved within 30 min at low initial dye concentrations (20 mg/L) under mildly acidic conditions and continuous agitation. Adsorption equilibrium studies, interpreted using the Langmuir isotherm model, revealed a maximum adsorption capacity of 33 mg/g under optimised conditions. Thermodynamic analysis indicated that the adsorption process is spontaneous (-ΔG° ≈ 46-54 kJ/mol) and endothermic (ΔH° = 21.12 kJ/mol), accompanied by an increase in system disorder (ΔS° = 0.2 kJ/mol × K). Importantly, experiments conducted using real wastewater matrices demonstrated performance comparable to that obtained in deionised water, thereby underscoring the practical applicability of the proposed system. Furthermore, the nanoparticles retained more than 90% removal efficiency after five consecutive adsorption-desorption cycles, employing a basic eluent for dye desorption and surface regeneration. The intrinsic magnetic properties of the adsorbent additionally enable facile recovery and potential reutilisation in secondary applications, including asphalt production. Collectively, these findings highlight the considerable potential of magnetite nanoparticles as effective and reusable adsorbents for wastewater remediation and support further investigation toward pilot-scale implementation.
Scalable manufacturing of graphene-based solid-contact ion-selective electrodes (SC-ISEs) is constrained by reliance on mined graphite and on patterning methods that are costly, energy-intensive, or poorly suited to high-throughput production. Here, we present a sustainable, manufacturing-ready approach in which graphene derived from hardwood biochar is formulated into printable inks and patterned by high-throughput screen printing to produce bioderived graphene solid-contact ion-selective electrodes (BioG-SC-ISEs). Unlike prior biomass-derived electrodes based on amorphous or activated carbons, this work demonstrates the conversion of biochar into graphene-like nanosheets compatible with scalable printing. By functionalizing the screen-printed electrodes with poly(vinyl chloride) (PVC)-based ion-selective membranes doped with distinct ionophores, we produced sensors capable of selectively monitoring six plant nutrients (K+, Na+, NH4+, Ca2+, Mg2+, and NO3-). The resulting sensors exhibited near-Nernstian sensitivities with detection limits between 0.064 and 0.526 mg·L-1 with wide sensing ranges (10-6 to 10-1 M for monovalent ions, 10-5 to 10-1 M for Mg2+, and 10-5 to 10-2 M for Ca2+). As an application-relevant demonstration, K+ BioG-SC-ISEs tracked progressive potassium depletion across modified Hoagland formulations (100%, 50%, and 25% K+), achieving a sensitivity of 57.4 ± 0.7 mV·dec-1 and a detection limit nearly three orders of magnitude below typical hydroponic potassium levels, with measurements in close agreement with inductively coupled plasma optical emission spectrometry (ICP-OES). Overall, this work establishes a sustainable strategy for scalable SC-ISE manufacturing and provides a versatile platform for high-performance ion sensing with direct implications for hydroponic agriculture, environmental monitoring, and other electrochemical sensing applications requiring selective ion detection.
Integrating high elasticity, high-fidelity electromechanical transduction, and long-term operational stability under dynamic mechanical deformation has become a fundamental scientific challenge to develop ultrathin conductive rubber films for the field of flexible electronics. In this work, hydrogenated nitrile butadiene rubber/single-walled carbon nanotube (HNBR/SWCNT) based rubber films with precisely controlled thickness were prepared with a wet coating process in N-methyl-2-pyrrolidone (NMP) and cyclohexanone (CYC). Results have demonstrated that NMP-derived rubber films exhibit exceptional tensile strength (22.4 MPa), outstanding cyclic durability (modulus retention >92% after 5000 cycles), and ultralow volume resistivity (0.75 kΩ·cm). Conversely, CYC-derived rubber films achieve extraordinary extensibility (EAB > 400%) but display significantly elevated resistivity (77 kΩ·cm), directly resulting from discontinuous and defect-rich SWCNT networks with poor intertube connectivity. Critically, both HNBR/SWCNT rubber films display strain-rate-independent stress-strain response over the broad range of 50-500 mm/min and retain >94% of elongation at break and >94% of electrical conductivity after 168 h thermal aging. Collectively, owing to the wide detection range (1-100% strain), high gauge factor (GF = 455), and exceptional fatigue resistance (ΔR/R0 < 5% after 5000 bending cycles), NMP-derived HNBR/SWCNT films can be integrated as the active transducing layer for the next-generation flexible strain sensors, real-time physiological monitoring patches, and intelligent wearable electronic systems.
This study aimed to establish a thorough proof of concept for an innovative, fully automated, non-destructive, and label-free approach for the identification of bacterial colonies directly on agar plates, integrating digital holography with artificial intelligence, and to evaluate its performance. High-resolution holographic images of individual bacterial colonies grown on translucent brain-heart agar plates were captured every 30 min over an 18-h incubation period (530 MPx per full plate). Imaging was performed using a large field 1× magnification system, a partially coherent LED light source, and a high-resolution complementary metal-oxide-semiconductor (CMOS) sensor. A database containing 49,490 digital holograms of individual colonies from 276 clinical strains belonging to 10 of the most prevalent pathogenic bacterial species was used to train the convolutional neural network (CNN). Prediction accuracy was further enhanced by incorporating information across different phylogenetic levels. The performance of the BAIO-DX system was evaluated on 232 strains from the 10 species included in the training data set, as well as 64 strains from 8 species not included in the training data set. For the species included in the training data set, this new method identified 86.6% of the strains at the species level, with a positive-percent agreement of 96.5%. An additional 48% of the strains not identified at the species level could be correctly classified at the genus level through phylogenetic interpretation. These results validate this innovative approach as a candidate for a fully automated, non-destructive, and label-free solution for bacterial identification in clinical microbiology laboratories. Identification of pathogenic bacteria in clinical laboratories is traditionally performed using culture-based methods, such as matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) mass spectrometry or biochemical assays. Although recent advances in automation and artificial intelligence (AI) applied to agar plate imaging have reduced manual workload, bacterial identification remains time-consuming and labor-intensive. Here, we present a fully automated, non-destructive, and label-free identification method of bacterial colonies directly on agar plates, combining digital holography and convolutional neural network (CNN) algorithms. After training the system with 276 strains belonging to 10 of the most frequent pathogenic species, the BAIO-DX solution was able to identify 86.6% of new strains at the species level, on a 232-sample test set, achieving a positive-percent agreement of 96.5%. These thorough proof of concept shows that advanced imaging methods with AI-driven analysis can enable reliable, fully automated identification of a substantial proportion of clinically relevant bacteria, offering significant potential to streamline and enhance diagnostic workflows in clinical microbiology.
This study investigates the preparation and characterization of tin micro- and nanoparticles with an emphasis on phase-transformation-induced particle formation and chemical purity. Microparticles were generated through repeated phase transformations between β-Sn (white tin) and α-Sn (gray tin), exploiting the associated volumetric changes to induce fragmentation and particle size reduction. The evolution of particle size distribution was systematically analyzed as a function of transformation cycles. The data were analyzed using the modified Johnson-Mehl-Avrami-Kolmogorov equation, and the saturation particle size corresponds to the grain size of the original tin sheet. The phase transformation was induced homogeneously by α-Sn particles and heterogeneously by InSb, and the results were comparable. The influence of the surrounding atmosphere was studied. The increase in oxygen content during repeated phase transformation was measured. In parallel, tin nanoparticles were synthesized via a solution-based route using ammonium hexachlorostannate as a precursor. The nanoparticles precipitated from this solution at mild temperatures during the β-Sn to α-Sn transformation at 13.2 °C. Both micro- and nanoparticles were characterized in terms of morphology and size distribution. The results provide insight into the relationship between phase transformation and particle size reduction mechanisms, and offer a controllable pathway for the preparation of tin particles across micro- and nanoscale regimes.
Swift heavy ion irradiation provides an effective method for defect-mediated regulation of magnetic functionality in oxide materials. In this work, 100 MeV Ag ions were used to systematically modify the structural and magnetic properties of Co1.5Fe1.5O4, prepared via the solution combustion method, at different fluences: 0, 1 × 1013, and 1 × 1014 ions per cm2. Ion irradiation improves the orbital magnetic contribution and ferrimagnetic ordering by altering the defect chemistry, causing cation redistribution, and strengthening superexchange interactions. These results show the potential of irradiated Co1.5Fe1.5O4 for enhanced magnetic recording, spintronic, and environmental applications, and offer essential insight into ion-beam-controlled magnetic tuning. We described the structural, morphological, magnetic, and electronic properties of the irradiated Co1.5Fe1.5O4 using angle-dispersive X-ray diffraction (ADXRD), high-resolution transmission electron microscopy (HRTEM), vibrating sample magnetometry (VSM), X-ray absorption spectroscopy (XAS), and X-ray magnetic circular dichroism (XMCD). ADXRD confirmed the inverse cubic spinel structure of these ferrites before and after the heavy ion impact. VSM analysis revealed enhanced magnetic saturation and coercivity with higher Ag ion fluences. The overall magnetic moment per Co1.5Fe1.5O4 unit cell increases from 1.38 to 2.56µB, indicating stronger ferrimagnetic alignment. Ion-induced anisotropic strain enhances orbital angular momentum, resulting in an increase in the orbital magnetic moment of the Fe ions at higher fluences. Ion impact tunes the magnetic properties of Co1.5Fe1.5O4 by creating defects, making it suitable for applications in magnetic recording media, magnetic storage devices, wastewater treatment, and spintronics.
Al-Cu-Fe quasicrystalline coatings were deposited on AISI 321 stainless steel substrates by high-velocity oxy-fuel (HVOF) spraying at oxygen pressures of 3.0, 3.5, and 4.0 bar. The influence of oxygen pressure on the phase composition, microstructure, porosity, corrosion behavior, thermal stability, and microhardness of the coatings was investigated using X-ray diffraction (XRD), scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM/EDS), ImageJ porosity analysis, electrochemical corrosion testing in 3.5 wt.% NaCl solution, simultaneous thermal analysis (TGA/DSC), and microhardness measurements. XRD analysis revealed the formation of quasicrystalline-related intermetallic phases together with Al, Fe3Al13, FeAl, Fe3O4, CuFe2O4, Cu2O, and CuO phases. The coating deposited at 3.5 bar exhibited the lowest porosity (5.37%), the most homogeneous microstructure, and the largest residual coating thickness after corrosion testing. SEM and EDS analyses indicated that corrosion preferentially initiated at pores, splat boundaries, and phase interfaces, while the coating produced at 3.5 bar demonstrated the most stable surface condition after exposure to a 3.5 wt.% NaCl solution. Thermal analysis showed that all coatings remained stable up to 900 °C. Sample (a) exhibited the lowest mass loss and the highest thermal stability, whereas sample (b) demonstrated the most favorable combination of structural integrity, phase ordering, coating density, corrosion-related performance, and thermal stability. Microhardness values of the coatings ranged from 754 to 778 HV, significantly exceeding that of the AISI 321 substrate. The results demonstrate that oxygen pressure is a critical parameter controlling the microstructure and functional properties of HVOF-sprayed Al-Cu-Fe coatings, with 3.5 bar providing the most balanced set of properties.
Over the last forty years, monoclonal antibodies have become increasingly important therapeutic agents, with most manufactured as preformulated solutions. However, bioformulation of complex proteins is a difficult engineering challenge; formulations must be tailored to individual therapies, necessitating time- and material-intensive campaigns to select combinations of excipients to simultaneously optimize various design criteria. These additives complicate formulation design with unintuitive and non-linear relationships, creating a vast multidimensional design space that is intrinsically difficult to optimize using traditional techniques. To address this challenge, we investigated a high-throughput discovery pipeline using machine learning to model and predict the effects of GRAS excipients on formulation behavior of a model antibody. This was supported by automation-assisted "on-demand" formulation to produce dozens of uniquely formulated antibody solutions for downstream evaluation and biophysical characterization. This pipeline was then integrated into an iterative closed-loop cycle of automated Design-Build-Test-Learn (DBTL), where new rounds of experiments are designed by the model. The process yielded both improved formulations and accurate predictive models of formulation behavior across multiple target objectives (melting temperature, diffusivity, and high-concentration viscosity). This validates the utility of this technique to both map the underlying property-function landscape and effectively guide formulation development while balancing multiple competing design requirements.
Sesame meal protein isolate (SPI) derived from sesame meal was utilized as an upcycled plant protein source to develop N-halamine structure-based antimicrobial coating system to prevent cross-contamination for fresh food produce. The coating matrix was formulated using SPI, tannic acid (TA), cellulose nanocrystal (CNC), and sodium hypochlorite (NaOCl). The N-halamine structure maintained a stable active chlorine content of approximately 5 µmol/cm2 and enabled repeated recharging to the initial level on the coated model food-contact surface, stainless steel (SS). The stability of the coated surface was evaluated under various harsh conditions, including different pH levels (2, 4, 7, and 9), temperatures (4°C, 23°C, and 35°C), chemical oxygen demand (COD) levels (0-20,000 mg/L), and physical damage. Antimicrobial test against Escherichia coli O6 and Listeria innocua showed a 5 log CFU/mL reduction within 5 min under at 22 ± 2°C and 45 ± 5% relative humidity. Furthermore, the SPI-based coating inhibited the transfer of bacteria to leafy fresh food produce about 4 log CFU/mL reduction in simulated cross-contamination tests. These findings suggest that the developed coating system in this study offers a stable and effective solution for cross-contamination of fresh food produce, addressing limitations of conventional biopolymer-based coatings.
Cowpea (Vigna unguiculata L.) is an underutilized protein-rich pulse with strong potential to diversify the alternative protein market, particularly through sustainable fractionation strategies. However, comparative insights into how dry and hybrid routes influence protein structure, functionality, and nutritional quality within the same processing stream remain limited. This study evaluated the nutritional, morphological, and techno-functional properties of ingredients recovered via dry and hybrid (dry-wet) processes. Dry fractionation (milling and air classification) yielded a cowpea protein concentrate (CPC) with 47.5% yield and 54.6 g·100 g-1 protein (d.b.). CPC served as feedstock for wet extraction, producing a cowpea protein isolate (CPI) with a 45.0% process yield and 87.5 g·100 g-1 protein (d.b.). The hybrid route increased protein purity compared to dry processing while reducing solvent demand (water and pH-adjusting solutions) per unit of protein relative to conventional wet extraction of whole flour. Both ingredients mainly consisted of glutamic acid, aspartic acid, leucine, and lysine. The amino acid score (AAS) met FAO/WHO requirements, except for sulfur-containing amino acids, with in vitro protein digestibility-corrected AAS of 66% (CPC) and 70% (CPI). Soaking (CPC-S) markedly reduced tannins, phytates, and ash content through leaching. CPI exhibited higher solubility at alkaline pH and improved emulsifying, foaming, and water-/oil-holding capacities than CPC. Structural analyses indicated that the hybrid process produced a more homogeneous protein-rich matrix with signs of aggregation and molecular rearrangement. In contrast, dry-fractionated ingredients retained heterogeneous structures associated with protein-carbohydrate interactions. Overall, the hybrid route efficiently produced a high-purity CPI, with improved functionality, and provided a promising route for developing high-value cowpea-derived ingredients for plant-based food applications. PRACTICAL APPLICATIONS: This study demonstrates an efficient strategy for converting cowpeas into high-value protein ingredients using a combined dry and wet fractionation approach. By removing starch- and fiber-rich components during the initial dry fractionation step, the process generates a protein-enriched fraction that facilitates downstream extraction and can reduce the intensity of aqueous processing compared to conventional wet extraction from whole flour. The resulting ingredients exhibit enhanced nutritional quality and improved techno-functional performance, including higher solubility, emulsifying capacity, and foaming properties. These attributes support their use across diverse food applications, including plant-based beverages, meat analogs, bakery products, and nutritional formulations. Overall, this approach expands the use of cowpea as a versatile, sustainable, and competitive alternative protein source for contemporary food systems.
Melam and ammeline are simple, s-triazine-based compounds first described by Liebig nearly 200 years ago. Outgoing from these two compounds, synthetic strategies for asymmetrically substituted s-triazines were developed. As the initial key step, Clauson-Kaas pyrrolation of the compounds' primary amino groups was carried out, significantly improving their solubility in organic solvents and thereby facilitating further conversions. These include functionalization of the s-triazine bridging amino group of pyrrolated melam by reaction with electrophiles, while pyrrolated ammeline was deoxychlorinated and subsequently reacted with nucleophiles to displace the resulting Cl substituent. Moreover, a reaction protocol for reversion of pyrrolyl into amino groups was developed, which involved ozonolysis, followed by treatment with aqueous NaOCl of the resulting formamide derivatives. Thereby, melam derivatives with essentially the same coordination site but enhanced solubilities were obtained. This enabled the preparation of a Cu(II) coordination complex from aqueous solution, which is unheard of for melam itself. Finally, the thus accessible s-triazines were structurally characterized to gain deeper insights on how the different conducted transformations influence the physicochemical properties relevant for future applications.
SUMMARYPeptidoglycan (PG) is a dynamic, load-bearing polymer whose crosslinking chemistry governs envelope mechanics, growth modes, and stress tolerance. For decades, PG crosslinking was viewed primarily through the lens of penicillin-binding proteins (PBPs). However, accumulating evidence over the past 2 decades has established LD-transpeptidases (LDTs) as important contributors to PG remodeling. Here, we organize the expanding LDT field into macro-domains bridging biochemistry, evolution, and ecology. We initially describe the reaction mechanisms, structural diversification, and convergent solutions and then explore the evolution across species. We highlight non-canonical LD-crosslinking chemistries, including L-Ala-meso-DAP (1-3) linkages, that broaden the design space of the sacculus. We then map functional repertoires across lineages-from reinforcement during envelope stress to outer membrane tethering, predation, specialized secretion, dormancy, and biofilms. In pathogens where LD-crosslinking is dominant or essential, carbapenems and penems remain particularly effective inhibitors of LDTs, yet family-wide diversity calls for structure-guided selectivity and ecological awareness. We also chart underexplored connections to microbiome ecology and propose LDT-derived biomarkers that report growth modes and dormancy. We integrate dispersed evidence into a complete landscape in which two-component systems and environmental cues coordinate LD pathways. Building on these threads, we propose a unifying model of LDTs as adaptive architects of PG whose acyl-enzyme intermediate and modular substrate gating endow reversibility, partner choice, and context-dependent outcomes-reinforcement, remodeling, anchoring, or controlled self-breach. Finally, we outline methods that enabled the discovery of LDTs and explore future directions. Together, these perspectives reframe LDTs from auxiliary enzymes to central designers of envelope architecture and bacterial fitness.
This work examines the impact of initial stress on the spread of coupled thermo-mechanical waves in a semiconductor thermo-elastic medium using a β-order fractional derivative model. The study is undertaken utilizing three generalized thermo-elastic theories: Dual-Phase-Lag (DPL) model, Lord-Shulman (L-S) theory, and Refined Dual-Phase-Lag (RDPL) model. To accurately reflect the underlying physical processes, the governing equations for heat conduction, elastic deformation, and semiconductor carrier dynamics are fully coupled, taking into account both finite-speed thermal transport and carrier density effects. To simplify the mathematical treatment, a suitable nondimensionalization strategy is adopted, lowering the number of governing parameters and clarifying the structure of the problem. A transform technique is then utilized to transform the resulting system of coupled partial differential equations (PDEs) into an analogous system of ordinary differential equations (ODEs) that can be solved analytically. This approach produces solution for displacement, temperature, carrier density, and stress tensor components, allowing for a complete investigation of wave propagation properties inside the medium. Numerical simulations using graphical representations are used to investigate the physical significance of the theoretical concept. These computations provide a comparative examination of physical quantities with and without initial stress across the three thermo-elastic theories. The β-fractional derivative and initial stress significantly impact wave behavior, including propagation velocity, amplitude evolution, and attenuation characteristics. Furthermore, the analysis sheds further light on the interplay between thermal processes and carrier density effects in thermo-elastic materials, emphasizing the significance of these elements in precisely forecasting the dynamic response of modern semiconductor media.
Vacuum-deposited organic solar cells (v-OSCs) are alternative candidates for photovoltaics technologies. Their advantages include well-defined molecular structures, high purity of materials, excellent batch-to-batch reproducibility, and solution-free fabrication process that enables good compatibility with underlying perovskite layer for tandem devices. Triarylamine-based small-molecule donors are commonly used in v-OSCs, however, their power conversion efficiencies (PCEs) are constrained by low short-circuit current density (Jsc). Moreover, to match with the photocurrent of perovskite subcell, enhancing Jsc of v-OSCs is highly demanded. Herein, four small-molecule donors (named PT, PF, BT, and BF) based on triarylamine electron-donating moieties are designed. Compared with linear analogues PT and PF, BT and BF with fused-ring building blocks including benzothiophene and benzofuran exhibit smaller bandgaps, lower highest occupied molecular orbital (HOMO) energy levels, and higher hole mobilities. Consequently, v-OSCs based on BT and BF exhibit surprisingly high Jsc values (17.91 and 18.13 mA cm-2, respectively), representing the highest reported Jsc for v-OSCs. Moreover, the Jsc enhancement leads to improved PCEs of devices based on BT and BF (10.53% and 10.11%, respectively). Remarkably, the PCE of 10.53% for the BT-based device represents the best PCE reported for v-OSCs. This work opens a promising avenue to develop high-performance small-molecule donors for v-OSCs.