Design Principles Research Articles

Co-designing an inclusive bus stop for a tourist transportation hub

ABSTRACT This study explores the integration of sustainable mobility and universal design principles in creating accessible public transportation infrastructure. The research focuses on the co-design of a bus stop at Faro International Airport, engaging diverse stakeholders, including older tourists and adults with disabilities, through surveys, group reflections, walk-throughs, and workshops. The methodology incorporated multiple methods, such as, inquiries, observations and interviews, and digital prototyping to gather comprehensive insights into the specific needs of the participants. By addressing societal vulnerabilities and promoting social sustainability, the co-design process fostered innovation, resulting in a bus stop design that is functional, inclusive, and adaptable. The study underscores the role of sustainable mobility in enhancing equitable urban transportation systems and demonstrates how inclusive design principles contribute to achieving the broader goals of environmental, social, and economic sustainability. The design incorporates accessibility features, such as tactile paving, raised platforms, intuitive seating, and smart technology, tailored to the diverse needs of users. Special emphasis was placed on minimising barriers for individuals with mobility, visual, or hearing impairments while addressing the practical requirements of older adults. The inclusive bus stop serves as a model for future initiatives, highlighting the importance of active community engagement in designing transportation infrastructure that supports diverse societal needs.

Tailoring of Selective Chemo-Responsiveness in Liquid Crystals via Organic Ionic Plastic Crystals.

Liquid crystals (LCs) are widely used as promising stimuli-responsive materials due to their unique combination of liquid and crystalline properties, providing the capability to sense even molecular-scale events and amplify them into macroscopic optical outputs. However, encoding a high level of selectivityto a specific intermolecular event remains a key challenge, leading to prior studies regarding chemically functionalized LC interfaces. Herein, we propose an integrative strategy to significantly advance the design of chemo-responsive LCs through a deep fundamental understanding on the orientational coupling of LCs with new functional molecules, organic ionic plastic crystals (OIs), presented at LC interfaces. In combination with computational simulations and experimental validations, we reveal the correlative interplay between LCs and each functional group in OI (di-cationic headgroup, aliphatic tails, and counter anions) to offer an excellent degree of freedom in tailoring the chemo-responsive features in LCs. Especially, we find the crystalline nature of OIs to providenew insights into the effects of counter anions, generating distinct quadrupolar interactions with adjacent molecules. Overall, our results provide generalizable design principles for the chemo-responsive materials that can explicitly distinguish the specific intermolecular event such as molecular bindings of OIs with acetic acid from those with propionic acid (one carbon difference).

Exceptional Battery-level Safety of High Energy Density Lithium-Ion Batteries through Non-Flammable and Low-Exothermic Localize High Concentration Electrolytes.

The poor safety performance of high energy density lithium ion batteries (LIBs) is drawing increasing public concern. To enhance the safety performance on the battery level, it is indispensable to design safe electrolytes that are both non-flammable and low exothermic under abusive conditions. By rational design, a safe localize high concentration electrolyte (LHCE) with non-flammability and extremely low exothermicity is formulated. Compared with conventional LiPF6-organocabonate electrolytes and previous LHCEs, the heat generated by the reaction between the safe LHCE and fully charged electrodes under abusive conditions is significantly reduced. Because of the non-flammability and low-exothermicity of the safe LHCE, high energy density LIB (1800 mAh, fully charged to 4.3V) with the safe LHCE successfully passes the nail penetration test. Because of the excellent interphasial properties of the safe LHCE, the cycle life and the rate capability of high energy density LIBs are significantly improved when the safe LHCE is adopted. This work sheds light on the design principles of electrolytes for achieving battery-level safety.

Designing the future of bond markets: Reducing transaction costs through tokenization

Corporate bonds are an attractive option for corporate financing. However, current bond markets face many challenges and inefficiencies, resulting in high transaction costs (TAC). In recent years, technological advancements like blockchain technology have enabled the possibility of reducing TAC in bond markets. Even though practice experiments with such solutions, academic literature lacks generic design knowledge under the TAC lens to design blockchain-based bonds. Thus, our research follows the design science research (DSR) paradigm to design and develop a bond prototype using the Ethereum blockchain protocol. Our results highlight the capability of blockchain-based bond markets to reduce TAC in the three dimensions of asset specificity, uncertainty, and transaction frequency. Further, our research provides design principles to contribute to both practice and the academic discourse on developing blockchain-based bond markets with reduced TAC.

Advancements in 2D Titanium Carbide (MXene) for Electromagnetic Wave Absorption: Mechanisms, Methods, Enhancements, and Applications.

With the advent of the 5G era, there has been a marked increase in research interest concerning electromagnetic wave-absorbing materials. A critical challenge remains in improving the wave-absorbing properties of these materials while satisfying diverse application demands. MXenes, identified as prominent "emerging" 2D materials for wave absorption, offer unique advantages that are expected to drive advancements and innovations in this field. This review emphasizes the synthesis benefits provided by the unique structural characteristics of MXenes and the performance enhancements achieved through their combination with other absorbing materials. Material requirements, synthesis approaches, and conceptual frameworks are integrated to underscore these advantages. The study provides a thorough analysis of MXene-absorbing composites, going beyond basic classification to address preparation and modification processes affecting the absorption properties of MXenes and their composites. Attention is directed to synthesis techniques, structural design principles, and their influence on composite performance. Additionally, the potential applications of MXenes in electromagnetic wave absorbing devices are summarized. The review concludes by addressing the challenges currently confronting MXene materials and outlining expected developmental trends, aiming to offer guidance for subsequent research in this domain.

Manual wheelchair training programs: a scoping review of educational approaches and intended learning outcomes

BackgroundTraining programs grounded in educational theory offer a systematic framework to facilitate learning and outcomes. This scoping review aims to map the educational approaches documented for manual wheelchair training and to record intended learning outcomes and any relationships between learning theories, instructional design and outcomes.MethodsEight databases; Cochrane’s Library, EMBASE, CINAHL, PubMed, Scopus, EmCare, Medline, ProQuest Nursing and Allied Health Database and grey literature were searched in September 2023, with citation chaining for relevant papers. Included papers related to manual wheelchair training programs/protocols describing intended wheelchair training outcomes for adults and/or caregivers. Data extracted included study characteristics, type of intervention, explicit learning theories, instructional design principles and intended learning outcomes. The International Classification of Functioning and Kirkpatrick’s evaluation framework were used to organise intended outcomes.ResultsOf the forty-four articles included in this review, only fourteen explicitly used a learning theory in the instructional design of training. Training outcomes most commonly related to changes in knowledge/skills of manual wheelchair users (Level 2b of Kirkpatrick’s evaluation (n = 43), with less emphasis on participatory outcomes. Training designs incorporating Social Cognitive Theory (n = 8) were more likely to explore long term training outcomes, compared with other training designs.ConclusionWheelchair training programs that are designed using learning theory are more likely to produce learning outcomes that are retained and meaningfully applied. Such longer terms outcomes could have systemic cost and efficiency implications, such as reduction in wheelchair falls and readmissions to hospital. Deliberate integration of learning theory into manual wheelchair training design is recommended to support broad outcomes and long-term learning. This design could synergise different learning theories.

Optimization of x-ray dark-field CT for human-scale lung imaging.

X-ray grating-based dark-field imaging can sense the small angle scattering caused by object's micro-structures. This technique is sensitive to the porous microstructure of lung alveoli and has the potential to detect lung diseases at an early stage. Up to now, a human-scale dark-field CT (DF-CT) prototype has been built for lung imaging. This study aimed to develop a thorough optimization method for human-scale dark-field lung CT and guide the system design. We introduced a task-based metric formulated as the contrast-to-noise ratio (CNR) between normal and lesioned alveoli for system parameter optimization and designed a digital human-thorax phantom to fit the task of lung disease detection. Furthermore, a computational framework was developed to model the signal propagation in DF-CT and established the link between system parameters and the CNR metric. We showed that for a DF-CT system, its CNR first increases and then decreases with the system auto-correlation length (ACL). The optimal ACL is mostly independent of system's visibility, and is only related to the phantom's properties, that is, its size and absorption. For our phantom, the optimal ACL is about 0.35 µm at the design energy of 60keV. As for system geometry, increasing source-detector and isocenter-detector distance can extend the system's maximal ACL, making it easier for the system to meet the optimal ACL and relaxing the grating pitches. We proposed a set of parameters for a projective fringe system that can satisfy the simulated optimal ACL. This study introduced a task-based metric and a process for DF-CT optimization. We demonstrated that for a given phantom, the detection performance of the system is optimized at a specific ACL. The optimization method and design principles are independent from the underlying dark-field imaging method and can be applied to DF-CT system design using different grating-based implementations such as Talbot-Lau interferometer (TLI) or projective fringe method.

Manufacturability and Performance Study of Triply Periodic Minimal Surface Air-to-Air Heat Exchanger

Abstract The study tests 3D printability, heat transfer characteristics and pressure drop of two types of triply periodic minimal surface heat exchanger in order to develop new flow principles for compact heat exchanger design. Various generic plate heat exchanger designs are also tested to compare to the printed alternatives. Geometry variations for heat exchangers and laboratory testing air recuperators are modelled in SolidWorks software and manufactured mostly by UV LCD and FDM additive manufacturing methods. Digital light processing printing method has been found to be most successful in printing the TPMS structures, while using photopolymer materials. Literature studies conclude that the most promising structures are Schoen’s gyroid and Schwarz-diamond surfaces, which have been modelled and tested in several variations. Using these results, full size gyroid and Schwarz-D structure heat exchangers have been modelled, manufactured and tested. The results are compared and analysed to study the effect of advanced surface designs in heat transfer efficiency. The obtained results can be used in compact air-to-air thermal recuperator development as well as other low pressure heat exchanger applications, as the printed TPME heat exchangers outperform the plate heat exchangers in similar dimensions.

Computational Modeling of Electrocatalysts for CO2 Reduction: Probing the Role of Primary, Secondary, and Outer Coordination Spheres.

ConspectusIn the search for efficient and selective electrocatalysts capable of converting greenhouse gases to value-added products, enzymes found in naturally existing bacteria provide the basis for most approaches toward electrocatalyst design. Ni,Fe-carbon monoxide dehydrogenase (Ni,Fe-CODH) is one such enzyme, with a nickel-iron-sulfur cluster named the C-cluster, where CO2 binds and is converted to CO at high rates near the thermodynamic potential. In this Account, we divide the enzyme's catalytic contributions into three categories based on location and function. We also discuss how computational techniques provide crucial insight into implementing these findings in homogeneous CO2 reduction electrocatalysis design principles. The CO2 binding sites (e.g., Ni and "unique" Fe ion) along with the ligands that support it (e.g., iron-sulfur cluster) form the primary coordination sphere. This is replicated in molecular electrocatalysts via the metal center and ligand framework where the substrate binds. This coordination sphere has a direct impact on the electronic configuration of the catalyst. By computationally modeling a series of Ni and Co complexes with bipyridyl-N-heterocyclic carbene ligand frameworks of varying degrees of planarity, we were able to closely examine how the primary coordination sphere controls the product distribution between CO and H2 for these catalysts. The secondary coordination sphere (SCS) of Ni,Fe-CODH contains residues proximal to the active site pocket that provide hydrogen-bonding stabilizations necessary for the reaction to proceed. Enhancing the SCS when synthesizing new catalysts involves substituting functional groups onto the ligand for direct interaction with the substrate. To analyze the endless possible substitutions, computational techniques are ideal for deciphering the intricacies of substituent effects, as we demonstrated with an array of imidazolium-functionalized Mn and Re bipyridyl tricarbonyl complexes. By examining how the electrostatic interactions between the ligand, substrate, and proton source lowered activation energy barriers, we determined how best to pinpoint the SCS additions. The outer coordination sphere comprises the remaining parts of Ni,Fe-CODH, such as the elaborate protein matrix, solvent interactions, and remote metalloclusters. The challenge in elucidating and replicating the role of the vast protein matrix has understandably led to a localized focus on the primary and secondary coordination spheres. However, certain portions of Ni,Fe-CODH's expansive protein scaffold are suggested to be catalytically relevant despite considerable distance from the active site. Closer studies of these relatively overlooked areas of nature's exceptionally proficient catalysts may be crucial to continually improve upon electrocatalysis protocols. Mechanistic analysis of cobalt phthalocyanines (CoPc) immobilized onto carbon nanotubes (CoPc/CNT) reveals how the active site microenvironment and outer coordination sphere effects unlock the CoPc molecule's previously inaccessible intrinsic catalytic ability to convert CO2 to MeOH. Our research suggests that incorporating the three coordination spheres in a holistic approach may be vital for advancing electrocatalysis toward viability in mitigating climate disruption. Computational methods allow us to closely examine transition states and determine how to minimize key activation energy barriers.

Compact silica dual-band wavelength demultiplexer based on asymmetric-defined multimode interference coupler

Limited refractive index difference of silica waveguide brings great size challenges in wavelength demultiplexing. A silica dual-band wavelength demultiplexer (DBWD) based on an asymmetric multimode interference coupler (MMI) is demonstrated. The selective separation and output of target dual bands can be implemented using the proposed design method based on asymmetric-defined MMI couplers. The beam propagation method is adopted to verify the proposed design principle. Standard CMOS fabrication is used in demultiplexer preparation. At λ=1350 nm, insertion loss (IL) and crosstalk (CT) at port Output1 are 1.94 dB and −24.92 dB, respectively. At λ=1550 nm, IL and CT at port Output2 are 2.44 dB and −29.00 dB, respectively. The 3-dB bandwidth (BW3 dB) for Output1 and Output2 are 82 nm (1297-1379 nm) and 87 nm (1492-1579 nm), respectively. The corresponding CT for Output1 and Output2 are < −7.16 dB and < −12.9 dB, respectively. Due to the introduction of asymmetric MMI coupler, the footprint is reduced to 0.1 mm2 (25 µm × 4000 µm). Because of the periodic characteristic, the wavelength demultiplexing can be extended from O/C bands to E/L bands by a reshaped asymmetric-MMI coupler. Even by combining more asymmetric-MMI couplers with different etched sections, all 18 channels of coarse wavelength division multiplexing (CWDM) transmission (1270-1610 nm) can be covered. The favorable manufacturing tolerance facilitates large-scale integration and mass production.

Binocular stereo vision-based relative positioning algorithm for drone swarm

To address the challenges of high computational complexity and poor real-time performance in binocular vision-based Unmanned Aerial Vehicle (UAV) formation flight, this paper introduces a UAV localization algorithm based on a lightweight object detection model. Firstly, we optimized the YOLOv5s model using lightweight design principles, resulting in Yolo-SGN. This model achieves a 65.5% reduction in parameter count, a 62.7% reduction in FLOPs, and a 1.8% increase in accuracy compared to the original detection model. Subsequently, Yolo-SGN is utilized to extract target regions from binocular images, and feature point matching is exclusively conducted within these regions to minimize unnecessary computations in non-target areas. Experimental results demonstrate that the combination of Yolo-SGN and the Oriented FAST and Rotated BRIEF (ORB) algorithm reduces feature point matching computations to only a quarter of those in the original ORB algorithm, significantly enhancing real-time performance. Finally, the extracted feature points from UAVs are input into a binocular vision localization model to compute their three-dimensional coordinates. The average of the three-dimensional coordinates of all feature points is used to determine the three-dimensional position of the target UAV. Experimental results confirm that the UAV binocular vision localization algorithm, based on a lightweight object detection model, exhibits exceptional performance in terms of precision and real-time capabilities.

Towards higher electro-optic response in AlScN

Novel materials with large electro-optic (EO) coefficients are essential for developing ultra-compact broadband modulators and enabling effective quantum transduction. Compared to lithium niobate, the most widely used nonlinear optical material, wurtzite AlScN, offers advantages in nano-photonic devices due to its compatibility with integrated circuits. We perform detailed first-principles calculations to investigate the electro-optic effect in Al1−xScxN alloys and superlattices. At elevated Sc concentrations in alloys, the EO coefficients increase; importantly, we find that cation ordering along the c axis leads to enhanced EO response. Strain engineering can be used to further manipulate the EO coefficients of AlScN films. With applied in-plane strains, the piezoelectric contributions to the EO coefficients increase dramatically, even exceeding 250 pm/V. We also explore the possibility of EO enhancement through superlattice engineering, finding that nonpolar a-plane (AlN)m/(ScN)n superlattices increase EO coefficients beyond 40 pm/V. Our findings provide design principles to enhance the electro-optic effect through alloy engineering and heterostructure architecture.

Dementia Friendly Buildings—Approach on Architectures

Dementia’s escalating incidence, coupled with its economic burden, highlights the need for architectural designs and forms that benefit people living with dementia. This research explores strategies and design principles that focus on establishing supportive spaces for the prolonged autonomy, well-being, and safety of dementia patients. Contemporary research emphasizes the implementation of effective navigational techniques, via visual cues, familiar landmarks, and simplified layouts. For greater navigational signage, the intentional use of contrasting colors, textures, and lighting are recommended to demarcate functional areas within a structure. Incorporating familiar objects in personalized areas enhances treatment outcomes, e.g., reminiscence therapy leverages familiar objects, environmental cues, scents, sounds, and tactile features to trigger and retain memory. Integrating safety precautions such as slip-resistant flooring, handrails, and accessible bathrooms helps mitigate falls for the cognitively impaired. From a therapeutic perspective, this study draws attention towards incorporating gardens and outdoor spaces, which offers sensory stimulation, encourages physical activity, and fosters social engagement. Additionally, the integration of scents, sounds, and tactile features enriches the sensory experience for individuals with dementia. Through comprehensive consideration of design elements, this research highlights how intentionally crafted, dementia-friendly environments can convert spaces into empowering therapeutic settings tailored to address the unique need of this vulnerable group. This architectural approach acts as a valuable complement to the medical and therapeutic interventions in the treatment and care of people living with dementia and their families.

Recent Advances in the Design and Application of Asymmetric Carbon-Based Materials.

Asymmetric carbon-based materials (ACBMs) have received significant attention in scientific research due to their unique structures and properties. Through the introduction of heterogeneous atoms and the construction of asymmetric ordered/disordered structures, ACBMs are optimized in terms of electrical conductivity, pore structure, and chemical composition and exhibit multiple properties such as hydrophilicity, hydrophobicity, optical characteristics, and magnetic behavior. Here, the recent research progress of ACBMs is reviewed, focusing on the potential of these materials for electrochemical, catalysis, and biomedical applications and their unique advantages over conventional symmetric carbon-based materials. Meanwhile, a variety of construction strategies of asymmetric structures, including template method, nanoemulsion assembly method, and self-assembly method, are described in detail. In addition, the contradictions between material synthesis and application are pointed out, such as the limitations of synthesis methods and morphology modulation means, as well as the trade-off between property improvement and production costs. Finally, the future development path of ACBMs is envisioned, emphasizing the importance of the close integration of theory and practice, and looking forward to promoting the research and development of a new generation of high-performance materials through the in-depth understanding of the design principles and action mechanisms of ACBMs.

Research progress in the design and application of whole-cell biosensors for antibiotics

Antibiotics are chemicals with bactericidal or bacteriostatic activity produced by microorganisms and artificially synthesized. Since the discovery of penicillin by Alexander Fleming in 1928, antibiotics have been widely used in clinical treatments as well as in the animal husbandry and aquaculture, leading to antibiotic residues in soil, water, food and other environments. At the same time, antibiotic resistance is increasingly serious, which necessitates the discovery of novel antibiotics. In recent years, with the development of synthetic biology, researchers have developed a variety of whole-cell biosensors that can respond to antibiotics. These whole-cell biosensors use microbial cells to convert antibiotic signals into readable signals, which can not only perform dynamic detection of antibiotics simply, quickly, sensitively and accurately but also effectively discover novel antibiotics. This review comprehensively summarizes the reported whole-cell biosensors for antibiotics, classifies them into two types (specific and general), and elaborates on the design principles and applications of the two types of antibiotic biosensors. This review will provide reference for the construction and application of other whole-cell biosensors for antibiotics.

Generation of Personalized Urban Public Space Color Design Scheme Assisted by Artificial Intelligence

This research focuses on the generation of urban public space color design schemes using Artificial Intelligence (AI). The designed AI-based system predicts colors for the environment, culture, and users and designs a color palette for smart cities. Neural networks and clustering algorithms are used to determine the best hues and shades, depending on the input parameters like climate, architectural style, and general looks in a specific region. It evokes sophisticated colors in varied urban contexts, URBAN FABRICS proposes a specific color answer to the aesthetic and performative beautification of the public realm. In addition to adopting elements of AI binding into the design principles, the system enables dynamic colors to adapt to the changing needs and external conditions. Testing the model in multiple cities demonstrated its ability to generate unique, context-sensitive designs, improving both aesthetic value and user satisfaction. This research highlights the role of AI in modern urban planning, presenting an innovative approach to color design that balances artistic creativity with data-driven insights. The findings offer practical implications for architects, urban planners, and designers seeking to enhance urban public spaces through personalized, AI-assisted color schemes.

Challenges and Opportunities of Gamified BCI and BMI on Disabled People Learning: A Systematic Review

This systematic review explores the potential of the gamified brain–machine interfaces (BMIs) and brain–computer interfaces (BCIs) to enhance the quality of life for individuals with disabilities. These technologies promise to solve complex problems by delivering customized interventions considering individual needs, ethical dilemmas, and practical constraints. This review follows the PRISMA statement. The search process extensively explored multiple registered databases for studies published between 2015 and 2024. Articles were selected based on strict eligibility criteria, focusing on empirical research evaluating gamified BCIs and BMIs in rehabilitation and learning. The final analysis included 56 studies. A thorough examination emphasizes the transformative potential of gamified BCIs and BMIs for people with disabilities, highlighting the need for interdisciplinary collaboration, user-centered design principles, and ethical consciousness for gamified neurotechnology. These technologies mark a significant change by providing enjoyable and effective treatments for disabled individuals. It also delves into how gamification, neurofeedback, and adaptive learning techniques can enhance motivation, engagement, and overall well-being. This evaluation underscores the efficiency of gamified BCIs and BMIs as potential instruments for improving the quality of life and empowering disabled people. However, despite their apparent potential for rehabilitation and learning, more research is needed to validate their effectiveness, accessibility, and long-term benefits.

SynDEc: A Synthetic Data Ecosystem

Given the critical role of data availability for growth and innovation in financial services, especially small and mid-sized banks lack the data volumes required to fully leverage AI advancements for enhancing fraud detection, operational efficiency, and risk management. With existing solutions facing challenges in scalability, inconsistent standards, and complex privacy regulations, we introduce a synthetic data sharing ecosystem (SynDEc) using generative AI. Employing design science research in collaboration with two banks, among them UnionBank of the Philippines, we developed and validated a synthetic data sharing ecosystem for financial institutions. The derived design principles highlight synthetic data setup, training configurations, and incentivization. Furthermore, our findings show that smaller banks benefit most from SynDEcs and our solution is viable even with limited participation. Thus, we advance data ecosystem design knowledge, show its viability for financial services, and offer practical guidance for privacy-resilient synthetic data sharing, laying groundwork for future applications of SynDEcs.

Reimagining Public Restrooms: Integrating Art and Design in New York Citys Urban Spaces

This research explores the integration of public art into New York Citys public restrooms, focusing on enhancing the user experience through design and functionality. Traditionally, restrooms have been seen as purely utilitarian spaces; however, design principles from Japanese restroom culture reveal the potential to transform these areas into immersive, artistic environments that prioritize comfort, privacy, and well-being. The study examines the use of advanced technologies, minimalist aesthetics, and sustainable materials in public restroom design, drawing comparisons to Japans innovative restroom culture. Through a combination of case studies, design analysis, and user feedback, the research explores how art can be incorporated into public restroom spaces through murals, interactive installations, ambient lighting, and soundscapes. The ndings suggest these elements can transform restrooms from mundane facilities into inviting, functional, and culturally reective spaces. This s design principles from Japanese restroom culture reveal the potential to transform these areas into immersive, artistic environments that prioritize comfort, privacy, and well-being. Shift in design can enhance the public's overall experience, foster community engagement, and improve public perceptions of restroom environments, promoting a shift in how these spaces are viewed within the urban landscape.

ExoSim 2: the new exoplanet observation simulator applied to the Ariel space mission

ExoSim 2 is the next generation of the Exoplanet Observation Simulator (ExoSim) tailored for spectro-photometric observations of transiting exoplanets from space, ground, and sub-orbital platforms. This software is a complete rewrite implemented in Python 3, embracing object-oriented design principles, which allow users to replace each component with their functions when required. ExoSim 2 is publicly available on GitHub, serving as a valuable resource for the scientific community. ExoSim 2 employs a modular architecture using Task classes, encapsulating simulation algorithms and functions. This flexible design facilitates the extensibility and adaptability of ExoSim 2 to diverse instrument configurations to address the evolving needs of the scientific community. Data management within ExoSim 2 is handled by the Signal class, which represents a structured data cube incorporating time, space, and spectral dimensions. The code execution in ExoSim 2 follows a three-step workflow: the creation of focal planes, the production of Sub-Exposure blocks, and the generation of non-destructive reads (NDRs). Each step can be executed independently, optimizing time and computational resources. ExoSim 2 has been extensively validated against other tools like ArielRad and has demonstrated consistency in estimating photon conversion efficiency, saturation time, and signal generation. The simulator has also been validated independently for instantaneous read-out and jitter simulation, and for astronomical signal representation. In conclusion, ExoSim 2 offers a robust and flexible tool for exoplanet observation simulation, capable of adapting to diverse instrument configurations and evolving scientific needs. Its design principles and validation results underscore its potential as a valuable resource in the field of exoplanet research.