Theoretical Limit Research Articles

Estimation of the Chances to Find New Phenomena at the LHC in a Model-Agnostic Combinatorial Analysis

In this paper, we estimate the number of event topologies that have the potential to be produced in pp collisions at the Large Hadron Collider (LHC) without violating kinematic and other constraints. We use numerical calculations and combinatorics, guided by large-scale Monte Carlo simulations of Standard Model (SM) processes. Then, we set the upper limit on the probability that new physics may escape detection, assuming a model-agnostic approach. The calculated probability is unexpectedly large, and the fact that LHC has not found new physics until now is not entirely surprising. Theoretical limitations and experimental challenges in observing new physics within the studied exclusive event classes are examined.

Lateral Flow Assay for Preeclampsia Screening Using DNA Hairpins and Surface-Enhanced Raman-Active Nanoprobes Targeting hsa-miR-17-5p

Preeclampsia (PE) is a serious complication that poses risks to both mothers and their children. This condition is typically asymptomatic until the second or even third trimester, which can lead to poor outcomes and can be costly. Detection is particularly challenging in low- and middle-income countries, where a lack of centralized testing facilities coincides with high rates of PE-related maternal mortality. Variations in the levels of hsa-miR-17-5p have been identified as constituting a potential early indicator for distinguishing between individuals with PE and those without PE during the first trimester. Thus, developing a screening test to measure hsa-miR-17-5p levels would not only facilitate rapid detection in the early stages of pregnancy but also help democratize testing globally. Here, we present a proof-of-principle lateral-flow assay (LFA) designed to measure hsa-miR-17-5p levels using DNA-hairpin recognition elements for enhanced specificity and nanoprobes for sensitive surface-enhanced resonance Raman scattering (SERS) signal transduction. The theoretical limit of detection for hsa-miR-17-5p was 3.84 × 10−4 pg/µL using SERS.

Design and optimization of two-terminal InGaP/Si tandem solar cell through numerical simulation

Abstract The III-V/Si double junction solar cells demonstrate cost-effective performance comparable to III-V/III-V tandems, with an efficiency of 35.9%, below the 43% theoretical limit. Considering monolithic InGaP//Si based tandem solar cell, this work dealt with the optimization of its efficiency as a function of layer thicknesses and dopings. Considering ideal optoelectronic parameters of materials, numerical simulations were performed by using Silvaco/ATLAS TCAD software. They were conducted within the context of a multi-step optimization procedure that was proposed in this work. The obtained optimum tandem InGaP//Si structure reached an unprecedented power conversion efficiency of 40.74% under 1.5G spectrum.

CANCER. Is this Forever? Examining the Relationship Between Event Centrality and Fear of Cancer Recurrence from a Cognitive-Behavioral Standpoint

The purpose of this study was to test a moderated mediation model. We first looked into whether fear of a cancer recurrence mediated the effect of time since diagnosis on trauma centrality, a concept rendering the impact of cancer on one’s self-identity. Secondly, we looked into whether the indirect effect would depend on the stage of diagnosis. We expected a more pronounced indirect effect for early stages as opposed to late stages. We acquired data from 234 cancer survivors (78.02% female; Mage= 35.58), who received a cancer diagnosis, were undergoing cancer treatment or had finished their treatment. Together with demographics and basic medical information, participants completed the Fear of Cancer Recurrence Inventory Short Form (FCRI-SF) and the Centrality of Event Scale – the Short - Form (CED-SF). In line with our expectations, the results confirmed an indirect effect of fear of cancer recurrence which was stronger for survivors in the early stage of diagnosis (i.e., I, II) as compared to those in the late stage (i.e., III, IV). Conclusions and Future Directions. The study emphasizes the significance of taking into account both the disease stage at diagnosis and the length of time since diagnosis when creating interventions to help cancer survivors address their fear of cancer recurrence. Theoretical ramifications and interpretive limitations are presented.

Statistical resolution analysis of microwave computational imaging

AbstractThis letter presents a model based on the Cramér–Rao bound theory for calculating the theoretical lower limit of imaging resolution of microwave computational imaging aided by re‐configurable metasurface. The model takes into account two crucial parameters: the signal‐to‐noise ratio and the number of measurements in the imaging process. By simultaneously considering the signal‐to‐noise ratio and the number of measurements, as well as other parameters, the model allows for a comprehensive assessment of the imaging resolution of the imaging system. In addition, both position estimation and intensity estimation are considered, and a new composite statistical resolution concept is proposed, which is more suitable for microwave computational imaging.

Deep Learning for Solving Partial Differential Equations: A Review of Literature

Partial Differential Equations (PDEs) are fundamental in modeling various phenomena in physics, engineering, and finance. Traditional numerical methods for solving PDEs, such as finite element and finite difference methods, often face limitations when applied to high-dimensional and complex systems. In recent years, deep learning has emerged as a promising alternative for approximating solutions to PDEs, offering potential improvements in both efficiency and scalability. This paper provides a comprehensive review of the literature on deep learning-based methods for solving PDEs, focusing on key approaches such as Physics-Informed Neural Networks (PINNs), deep Galerkin methods, and neural operators. These methods leverage the expressiveness of neural networks to capture underlying physics while avoiding the curse of dimensionality associated with classical techniques. We explore the theoretical foundations, advantages, and limitations of these deep learning models, along with their applications in diverse fields like fluid dynamics, quantum mechanics, and financial modeling. Additionally, this review examines recent advancements in hybrid models that combine traditional numerical methods with deep learning approaches to enhance accuracy and stability. Through this review, we highlight key trends and open challenges in the field, paving the way for future research at the intersection of deep learning and computational mathematics.

A 3D-Printed Bionic Membrane with Autonomously Passive Unidirectional Liquid Transfer Capability for Water Condensation, Collection, and Purification.

Interfacial solar vapor generation is a promising technology for alleviating the current global water crisis, and the evaporation rate and efficiency have approached the theoretical limit. In a practical interfacial evaporation water purification system, the collection rate of purified water is typically lower than the evaporation rate. Passive collection devices based on gravity are susceptible to environmental influences and exhibit low collection efficiency, while active collection devices consuming external energy suffer from complex device systems and extra energy consumption. Given that both collection devices are nonselective and unable to distinguish contaminants mixed in the vapor, bionic membranes with autonomously passive and unidirectional water transfer capacity are developed through 3D printing for efficient water collection. More importantly, the bionic membranes are capable of high-speed water transportation without the need for external energy or gravity drive and liquid-selective transportation for separating oily pollutants from the collected products. The directional transport property facilitates the modular assembly of the bionic membrane, extending its application to practical large-scale solar-driven seawater desalination systems.

Research on Multi-Parameter Error Model of Backcalculated Modulus Using Abaqus Finite Element Batch Modeling Based on Python Language

The error in modulus backcalculation is a crucial component in validating the rationality and reliability of results for engineering applications. The objective of this study is to identify the theoretical limitations associated with backcalculated modulus errors under typical parameter uncertainties and to determine the primary factors contributing to these errors. Firstly, using the actual measurements or data from the Long-Term Pavement Performance (LTPP) project, the statistical distributions of errors for typical parameters in the modulus backcalculation model were determined. Subsequently, a factor level table for orthogonal experimental design was developed, leading to the construction of 81 orthogonal design experimental schemes and their corresponding theoretical pavement structure models based on the actual error distributions. The deflection responses of 81 theoretical pavement structure models were then computed using an ABAQUS finite element batch analysis method devised in Python. Furthermore, a multi-parameter error model for modulus was established using multiple linear regression and variance analysis. Finally, the theoretical limitations of modulus errors under actual errors were analyzed. The results show that the errors of thickness, load amplitude and load frequency follow a normal distribution, while the distribution of backcalculated modulus errors follows an approximate mixed Gaussian distribution. When the errors of multiple parameters are combined randomly, the modulus errors range from −100% to 595%, and the probability of the modulus errors being less than 15% is highest in the asphalt surface layer, followed by the subgrade, and then the base and subbase layers. Within the same error range, the modulus error is random. However, with different error ranges, the overall level of modulus error increases in proportion to the size of those ranges. Compared to factors such as thickness, load amplitude, and load frequency, the errors in deflections have a highly contribution rate on the modulus errors exceeding 99%.

Mathematical Modeling Unveils Optimization Strategies for Targeted Radionuclide Therapy of Blood Cancers.

Targeted radionuclide therapy is based on injections of cancer-specific molecules conjugated with radioactive nuclides. Despite the specificity of this treatment, it is not devoid of side-effects limiting its use and is especially harmful for rapidly proliferating organs well perfused by blood, like bone marrow. Optimization of radioconjugates administration accounting for toxicity constraints can increase treatment efficacy. Based on our experiments on disseminated multiple myeloma mouse model treated by 225Ac-DOTA-daratumumab, we developed a mathematical model which investigation highlighted the following principles for optimization of targeted radionuclide therapy. 1) Nuclide to antibody ratio importance. The density of radioconjugates on cancer cells determines the density of radiation energy deposited in them. Low labeling ratio as well as accumulation of unlabeled antibodies and antibodies attached to decay products in the bloodstream can mitigate cancer radiation damage due to excessive occupation of specific receptors by antibodies devoid of radioactive nuclides. 2) Cancer binding capacity-based dosing. The total number of specific receptors on cancer cells is a critical factor for treatment optimization, which estimation may allow increasing treatment efficacy close to its theoretical limit. Injection of doses significantly exceeding cancer binding capacity should be avoided since radioconjugates remaining in the bloodstream have negligible efficacy to toxicity ratio. 3) Particle range-guided multi-dosing. The use of short-range particle emitters and high-affinity antibodies can allow for robust treatment optimization via initial saturation of cancer binding capacity, enabling redistribution of further injected radioconjugates and deposited dose towards still viable cells that continue expressing specific receptors.

Vanadium oxide thin films growth by a chemical solution deposition method and its pH sensor toward bio-sensing devices

Abstract We report on the evaluation of the structure of VOx thin films under different fabrication conditions of the chemical solution deposition method and the pH response of an extended gate field effect transistor (EGFET)-type pH sensor. Polycrystalline V2O5 thin films of 30 and 60 nm thick and amorphous VOx thin films of about 30 nm thick were successfully prepared under different precursor solution conditions. Using polycrystalline V2O5 thin films and amorphous VOx thin films as an extended gate (EG) electrode, protypes of EGFET-type pH sensors were fabricated and investigated their pH response characteristics. The average pH responsibility of 64 mV/pH, which exceeded the theoretical Nernst limit, was observed over a wide pH range from 2.4 to 8.0 in the amorphous VOx extended gate sensor. It was also found that stable pH response measurements could be performed on amorphous VOx film samples.

Study on the deep deoxidation mechanism of titanium powder using Y/YOCl/YCl3 and Y/Y2O3 systems

Low-oxygen high-purity titanium (oxygen concentration ≤ 500 ppm) is a critical material for advanced semiconductor and biomedical applications. Current deoxidation methods limit oxygen concentration in titanium to approximately 1000–2000 ppm, failing to meet the demand for ultra-low oxygen levels in high-performance materials. This study investigated the preparation mechanism and conditions for low-oxygen high-purity titanium utilizing a molten salt thermochemical method, employing Y as the deoxidant with a theoretical deoxidation limit below 10 ppm. We experimentally explored the deoxidation mechanisms of titanium using Y/YOCl/YCl3 and Y/Y2O3 systems, successfully reducing the oxygen concentration in titanium to 200 ppm, and proving that the Y/YOCl/YCl3 system is more efficient than the Y/Y2O3 system. Additionally, the titanium samples were analyzed using SEM-EDS, XRD, XPS, and 3D surface profilometry before and after deoxidation. These analyses examined the impact of the deoxidation process using Y on the crystal structure, oxide film, and surface roughness of titanium specimens, which are useful for understanding the deoxidation mechanism. During the sintering process of titanium powder attached to Y, the deoxidation process will produce YOCl or Y2O3. The formation of these deoxidation products leads to local oxygen diffusion, and the crystals of YOCl or Y2O3 are gathered at grain boundaries, which will resolve during the subsequent acid etching process, thus reducing the oxidation concentration of the titanium. The above results provide further theoretical guidance and technical support for the production of ultra-high-purity titanium powder.

Linearly programmable two-dimensional halide perovskite memristor arrays for neuromorphic computing.

The exotic properties of three-dimensional halide perovskites, such as mixed ionic-electronic conductivity and feasible ion migration, have enabled them to challenge traditional memristive materials. However, the poor moisture stability and difficulty in controlling ion transport due to their polycrystalline nature have hindered their use as a neuromorphic hardware. Recently, two-dimensional (2D) halide perovskites have emerged as promising artificial synapses owing to their phase versatility, microstructural anisotropy in electrical and optoelectronic properties, and excellent moisture resistance. However, their asymmetrical and nonlinear conductance changes still limit the efficiency of training and accuracy of inference. Here we achieve highly linear and symmetrical conductance changes in Dion-Jacobson 2D perovskites. We further build a 7 × 7 crossbar array based on analogue perovskite synapses, achieving a high device yield, low variation with synaptic weight storing capability, multi-level analogue states with long retention, and moisture stability over 7 months. We explore the potential of such devices in large-scale image inference via simulations and show an accuracy within 0.08% of the theoretical limit. The excellent device performance is attributed to the elimination of gaps between inorganic layers, allowing the halide vacancies to migrate homogeneously regardless of grain boundaries. This was confirmed by first-principles calculations and experimental analysis.

The Time of the Stones: A Call for Palimpsest Dissection to Explore Lithic Record Formation Processes

The dissection of archaeological palimpsests has become a crucial process for achieving a diachronic understanding of the history of human groups. However, its widespread application to archaeological deposits has been hampered by both methodological and theoretical limitations, as well as by the inherent characteristics of the deposits. This paper explores whether overcoming these barriers, both methodological and theoretical, truly represents a significant shift in understanding past human behaviour, thereby motivating the pursuit of shorter timescales. To this end, we have analysed the lithic assemblages of Unit Xb from the Neanderthal site of El Salt (Alcoi, Iberian Peninsula) focusing on lithic attributes and raw material analyses, enabling the definition of raw material units and refitting sets. Considering these variables, we have applied archaeostratigraphic and spatial analyses in order to generate units of analysis whose content is compared to that of the entire unit. The defined archaeostratigraphic units display different spatial distributions and lithic composition. Some of them are attached to certain hearths and composed of refitted sets, while other units are related to areas without combustion evidence and integrated with bigger and heavier single products. Through this approach, here, we show that reducing the spatiotemporal scale of the record helps to unravel behavioural variability, reducing interpretative errors implicit in the assemblage-as-a-whole approach. This highlights the role of temporal resolution in reconstructing site formation processes and challenges research perspectives that assert the unnecessary or impossible nature of palimpsest dissection.

Electrolyte‐free solid‐state batteries demonstrated with bifunctional Li2VCl4

All‐solid‐state batteries have attracted much attention because of the expected high energy density and inherent safety stemming from their nonflammable property. While improving the energy density of the cathode poses a significant challenge, here we introduce a novel battery design strategy to enhance energy density by employing bifunctional cathode material, allowing the weight ratio of the active material to be increased without using an electrolyte for the cathode. By employing lithium‐containing vanadium halide Li2VCl4, serving as both active material and electrolyte, the all‐solid‐state battery cell with no electrolyte for the cathode with a capacity approaching the theoretical limit is demonstrated. In addition, we present a guideline for improving capacity retention from the perspective of interfacial stability. Notably, thermodynamic analysis revealed interfacial instability between Li2VCl4 and sulfide material. A double‐layer separator, incorporating halide materials for the cathode side, was implemented to enhance the interfacial stability and mitigate the capacity degradation. Furthermore, it was found that the rate capability depends on the lithium content in synthesized Li2‐xVCl4 and does not change with the state of charge significantly. This study will contribute to designing the bifunctional cathode material for an all‐solid‐state battery and describe its unique properties.

Efficient wide-bandgap perovskite photovoltaics with homogeneous halogen-phase distribution

Wide-bandgap (WBG) perovskite solar cells (PSCs) are employed as top cells of tandem cells to break through the theoretical limits of single-junction photovoltaic devices. However, WBG PSCs exhibit severe open-circuit voltage (Voc) loss with increasing bromine content. Herein, inhomogeneous halogen-phase distribution is pointed out to be the reason, which hinders efficient extraction of carriers. We thus propose to form homogeneous halogen-phase distribution to address the issue. With the help of density functional theory, we construct a double-layer structure (D-2P) based on 2-(9H-Carbazol-9-yl)ethyl]phosphonic acid molecules to provide nucleation sites for perovskite crystallization. Homogeneous perovskite phase is achieved through bottom-up templated crystallization of halogen component. The efficient carrier extraction reduces the Shockley-Read-Hall recombination, resulting in a high Voc of 1.32 V. As a result, D-2P-treated device (1.75 eV) achieves a record power conversion efficiency of 20.80% (certified 20.70%), which is the highest value reported for WBG (more than 1.74 eV) PSCs.

Optical networking that exploits massive wavelength/spectrum and spatial parallelisms

As DWDM transmission offers enhanced wavelength/spectrum parallelism, the capacity of optical networks has been substantially increased. Due to the theoretical capacity limit of C-band transmission over single-mode fibers, research into new frequency bands and parallel fibers has become very active. However, the hardware scale of current optical cross-connect nodes will explode with greater wavelength/spectrum and spatial parallelism. Three optical node/network architectures are presented in this paper that take advantage of one or both of these parallelism technologies. These architectures will provide a baseline for cost-effective and bandwidth-abundant future optical networks based on massive parallelism.

Tailoring Perovskite/C60 Interface by Reactive Passivators for Stable Tandem Solar Cells

AbstractIntegrating perovskite solar cells with crystalline silicon bottom cells in a monolithic two‐terminal tandem configuration enables power conversion efficiency (PCE) surpassing the theoretical limits of single‐junction cells. However, wide bandgap (WBG) perovskite films face challenges related to phase stability and open circuit voltage (VOC) deficit, particularly due to severe non‐radiative recombination at the perovskite/C60 interface. Here, the interfacial defects are passivated by incorporating a reactive passivator that reacts with lead halides to form low‐dimensional phases. The target product obtained by optimizing the reaction temperature not only suppresses recombination across the interface, but also facilitates the transfer of charge carriers. More importantly, this product can suppress phase segregation of WBG perovskite films under exposure to light illumination and moisture. This strategy enables a high VOC of 1.25 V for WBG perovskite device based on polymer hole transport layer and a certified stabilized PCE of 30.52% for a monolithic perovskite/silicon tandem solar cell. The unencapsulated tandem device retains 94% of its initial PCE over 200 h under continuous 1‐sun full spectrum illumination in air, demonstrating the improved phase stability.

Investigating the Degree to Which Unstructured Socializing With Peers and Delinquency Are Nonlinear.

Since the formulation of Cohen and Felson's (1979) routine activity theory (RAT), Osgood et al. (1996) established a reformulated theory to better explain patterns of situational offense and coined the RAT of general deviance or more commonly known as unstructured socializing with peers (USWP). The present study seeks to explore whether spending more time in USWP may increase antisocial behavior in a nonlinear manner, either accelerating or decelerating. Results showed that the relationship between USWP and property delinquency was found to be nonlinear in a decelerating manner. Similar results were found for the association between USWP and substance use. Finally, the relationship between USWP and violent delinquency was significant, although no evidence was found for nonlinearity. The present study concludes with theoretical implications, limitations, and directions for future research.

Tensile properties of SiC/SiC obtained from epoxy‐encapsulated minicomposites

AbstractThe current study investigates the tensile behavior of SiC/SiC minicomposites, focusing on the efficacy of epoxy encapsulation in extracting the intrinsic fiber bundle response. Three minicomposite types were examined: two with Hi‐Nicalon Type‐S fibers and one with Tyranno ZMI fibers. Tensile tests were performed on minicomposites and fiber tows, both bare and epoxy‐encapsulated, whereas interface properties were measured via fiber push‐in tests. The results demonstrate that epoxy encapsulation partially mitigates non‐uniform loading in minicomposites with discontinuous matrices. Theoretical limits on fiber bundle strength, estimated using micromechanical models based on weakest‐link statistics and shear lag theory, are similar to measured encapsulated tow strengths when failure occurs within the elastic regime of the epoxy. In some cases, microstructural defects such as fiber–fiber contacts and debonded coatings play important roles in limiting composite strengths relative to theoretical values. Although encapsulation does not always directly improve properties, it provides useful context for evaluating composite performance and exposing microstructural limitations unaccounted for in idealized models.

Enhancing Long Stability of Solid-State Batteries Through High-Energy Ball Milling-Induced Decomposition of Sulfide-Based Electrolyte to Sulfur.

Metal sulfides are increasingly favored as cathode materials in all-solid-state batteries (ASSBs) due to their high energy density, stability, affordability, and conductivity. Metal sulfides often exhibit capacities exceeding their theoretical limits, a phenomenon that remains not fully understood. In this study, it reveals that this phenomenon is primarily due to the sulfur decomposition from sulfide-based electrolyte. By employing the high-energy ball milling (HEBM) technique, the deposition of sulfide-based electrolyte onto sulfur is intentionally promoted, resulting in higher charge capacities compared to the discharge capacities and surpass theoretical limits of metal sulfides. Using chromium sulfide (Cr2S3) as the active material, the sulfur decomposed from sulfide-based electrolyte transforms into lithium sulfide (Li2S) after discharge, resulting in an increased capacity by ≈439.6 mAhg-1 and improved cycling stability. Consequently, it demonstrates a specific capacity surpassing 1200 mAh g-1 with a capacity retention of over 80% after 650 cycles, maintaining cycling stability for more than 1900 cycles and achieving a Coulombic efficiency exceeding 99.9%. This versatile HEBM approach enables the fabrication of ASSBs utilizing various transition metal sulfides, such as molybdenum disulfide (MoS2), niobium disulfide (NbS2), and iron disulfide (FeS2), all exhibiting over theoretical limited capacities and prolonged cycling capabilities.