Roadmap For Design Research Articles

Simulation-Based Approach for Automatic Roadmap Design in Multi-AGV Systems

Simulation-Based Approach for Automatic Roadmap Design in Multi-AGV Systems

Design and analysis of a single-stage supersonic turbine with partial admission

Supersonic impulse turbines are commonly used to harvest waste heat from systems based on organic Rankine cycles, automotive applications, and gas-generator liquid rocket engines. This research aims to design and analyze a single-stage supersonic turbine with a rated power of approximately 440 KW. We present a comprehensive preliminary design roadmap followed by design parameters optimization. The preliminary sizing is carried out using one-dimensional flow analysis, while the blade geometrical design is performed using the two-dimensional method of characteristics. The turbine performance is then analyzed through numerical simulations on three-dimensional models. Comprehensive parametric analyses are conducted to examine the turbine performance sensitivity to changes in partial admission (PA), mean radius, and turbine blade height using three-dimensional sliding mesh techniques (SMT). The current analysis simulates the full turbine to capture PA effects, rather than focusing on a single periodic sector as is common in turbomachinery simulation practices. Different PA scenarios are investigated, emphasizing a single rotor passage over a complete rotor cycle in a partially admitted turbine, and examining its charging and discharging mechanisms. Flow tracking over such a blade shows that the turbine rotor exhibits compressor-like behavior over most of the unadmitted zone, contributing to efficiency drops and severe transients.

Intersectionality in Marketing: A Paradigm for Understanding Understudied Consumers

Intersectionality remains largely underutilized within marketing. To address this gap, this article synthesizes literature to provide tools for incorporating intersectionality into marketing research, including a framework for an intersectional marketing paradigm, a research design roadmap, a research agenda, and key takeaways for stakeholders. The definition of intersectionality focuses on three main components: (1) awareness and acknowledgment of overlapping (rather than isolated) social categories (e.g., gender, race, and class), (2) understanding of how differences in lived experiences at these intersections influence the marketplace, and (3) recognition of how power shapes these lived experiences. This article's novel research design roadmap features concrete theoretical and methodological approaches for marketing researchers from various backgrounds to utilize intersectionality in solving marketing problems: conducting exploratory subsample analyses, developing intersectional theory and hypotheses, conducting inclusive literature reviews, collecting and reporting detailed demographics, sampling understudied populations, and carefully situating conclusions. The research agenda provides research questions for emerging topics at societal, organizational, and consumer levels. Engaging with intersectionality will help ensure that marketing remains socially relevant, develops diverse and inclusive theories, and more accurately reflects the lived experiences of understudied populations and communities.

Enhancing overall performance of thermophotovoltaics via deep reinforcement learning-based optimization

Thermophotovoltaic (TPV) systems can be used to harvest thermal energy for thermoelectric conversion with much improved efficiency and power density compared with traditional photovoltaic systems. As the key component, selective emitters (SEs) can re-emit tailored thermal radiation for better matching with the absorption band of TPV cells. However, current designs of the SEs heavily rely on empirical design templates, particularly the metal-insulator-metal (MIM) structure, and lack of considering the overall performance of TPV systems and optimization efficiency. Here, we utilized a deep reinforcement learning (DRL) method to perform a comprehensive design of a 2D square-pattern metamaterial SE, with simultaneous optimization of material selections and structural parameters. In the DRL method, only the database of refractory materials with gradient refraction indexes needs to be prepared in advance, and the whole design roadmap will automatically output the SE with optimal Figure-of-Merit (FoM) efficiently. The optimal SE is composed of a novel material combination of TiO2, Si, and W substrate, with its thickness and structure precisely optimized. Its emissivity spectra match well with the external quantum efficiency curve of the GaSb cell. Consequently, the overall performance of TPV is significantly enhanced with an output power density of 5.78 W/cm2, an energy conversion efficiency of 38.26%, and a corresponding FoM of 2.21, surpassing most existing designs. The underlying physics of optimal SE is explained by the coupling effect of multiple resonance modes. This work advances the practical application potential of TPV systems and paves the way for addressing other multi-physics optimization problems and metamaterial designs.

In Situ Self‐Assembled Active and Stable Ir@MnOx/La0.7Sr0.3Cr0.9Ir0.1O3−δ Interfaces for CO2 Electrolysis

AbstractSolid oxide electrolysis cells are prospective approaches for CO2 utilization but face significant challenges due to the sluggish reaction kinetics and poor stability of the fuel electrodes. Herein, we strategically addressed the long‐standing trade‐off phenomenon between enhanced exsolution and improved structural stability via topotactic ion exchange. The surface dynamic reconstruction of the MnOx/La0.7Sr0.3Cr0.9Ir0.1O3−δ (LSCIr) catalyst was visualized at the atomic scale. Compared with the Ir@LSCIr interface, the in situ self‐assembled Ir@MnOx/LSCIr interface exhibited greater CO2 activation and easily removable carbonate intermediates, thus reached a 42 % improvement in CO2 electrolysis performance at 1.6 V. Furthermore, an improved CO2 electrolysis stability was achieved due to the uniformly wrapped MnOx shell of the Ir@MnOx/LSCIr cathode. Our approach enables a detailed understanding of the dynamic microstructure evolution at active interfaces and provides a roadmap for the rational design and evaluation of efficient metal/oxide catalysts for CO2 electrolysis.

In Situ Self-Assembled Active and Stable Ir@MnOx/La0.7Sr0.3Cr0.9Ir0.1O3-δ Interfaces for CO2 Electrolysis.

Solid oxide electrolysis cells are prospective approaches for CO2 utilization but face significant challenges due to the sluggish reaction kinetics and poor stability of the fuel electrodes. Herein, we strategically addressed the long-standing trade-off phenomenon between enhanced exsolution and improved structural stability via topotactic ion exchange. The surface dynamic reconstruction of the MnOx/La0.7Sr0.3Cr0.9Ir0.1O3-δ (LSCIr) catalyst was visualized at the atomic scale. Compared with the Ir@LSCIr interface, the in situ self-assembled Ir@MnOx/LSCIr interface exhibited greater CO2 activation and easily removable carbonate intermediates, thus reached a 42 % improvement in CO2 electrolysis performance at 1.6 V. Furthermore, an improved CO2 electrolysis stability was achieved due to the uniformly wrapped MnOx shell of the Ir@MnOx/LSCIr cathode. Our approach enables a detailed understanding of the dynamic microstructure evolution at active interfaces and provides a roadmap for the rational design and evaluation of efficient metal/oxide catalysts for CO2 electrolysis.

A novel titanium alloy for load-bearing biomedical implants: Evaluating the antibacterial and biocompatibility of Ti536 produced via electron beam powder bed fusion additive manufacturing process

Additive manufacturing (AM) of Ti-based biomedical implants is a pivotal research topic because of its ability to produce implants with complicated geometries. Despite desirable mechanical properties and biocompatibility of Ti alloys, one major drawback is their lack of inherent antibacterial properties, increasing the risk of postoperative infections. Hence, this research focuses on the Ti536 (Ti5Al3V6Cu) alloy, developed through Electron Beam Powder Bed Fusion (EB-PBF), exploring bio-corrosion, antibacterial features, and cell biocompatibility. The microstructural characterization revealed grain refinement and the formation of Ti2Cu precipitates with different morphologies and sizes in the Ti matrix. Electrochemical tests showed that Cu content minimally influenced the corrosion current density, while it slightly affected the stability, defect density, and chemical composition of the passive film. According to the findings, the Ti536 alloy demonstrated enhanced antibacterial properties without compromising its cell biocompatibility and corrosion behavior, thanks to Ti2Cu precipitates. This can be attributed to both the release of Cu ions and the Ti2Cu precipitates. The current study suggests that the EB-PBF fabricated Ti536 sample is well-suited for use in load-bearing applications within the medical industry. This research also offers an alloy design roadmap for novel biomedical Ti-based alloys with superior biological performance using AM methods.

Natural History of Untreated Idiopathic Sudden Sensorineural Hearing Loss.

Although corticosteroids and other treatments for idiopathic sudden sensorineural hearing loss (ISSNHL) have been described, understanding its prognosis without intervention provides valuable information for patient management. The objective of this study is to provide a comprehensive, quantitative statistical analysis of the natural history of untreated idiopathic sudden sensorineural hearing loss (ISSNHL). A systematic review and meta-analyses. Two independent searches of PubMed, Scopus, Web of Science, and Cochrane Library databases up to June 30, 2022, were performed. Adults with idiopathic sudden sensorineural hearing loss who received placebo or were untreated and had audiometric outcome measures in all study types were reviewed. These data indicative of the natural history of ISSNHL were analyzed, as were study characteristics related to risk of bias. Heterogeneity as assessed via I2 and random effects analyses were performed. Six studies meeting the inclusion criteria yielded 319 untreated patients whose natural history could be assessed. Heterogeneity among studies was moderate, with a variety of reported outcomes. A hearing improvement of at least 30 dB HL was observed in 36% (95% CI 0.28-0.44) of untreated patients, and of at least 10 dB HL was observed in 70% (95% CI 0.57-0.82) of untreated patients at 3 months. The mean hearing gain among untreated patients was 24.0 dB HL (95% CI 2.65-45.37) at 2-3 months. The observed natural history of ISSNHL suggests that patients can regain some hearing without active treatment. In the absence of future studies collecting prospective natural history data from untreated or placebo-treated ISSNHL patients, the data presented here provide the best available historical control data for reconsideration of results in past ISSNHL studies, as well as a roadmap for design and interpretation of future ISSNHL treatment clinical trials. Furthermore, knowing there is a statistically significant mean hearing gain of 24.0 dB HL in the untreated/placebo group provides an ethical basis for future placebo study of ISSNHL. The current status on ISSNHL management calls for a multi-institutional, randomized, double-blind placebo-controlled trial with validated outcome measures to provide science-based treatment guidance. Laryngoscope, 134:S1-S15, 2024.

Achieving health equity through conversational AI: A roadmap for design and implementation of inclusive chatbots in healthcare.

The rapid evolution of conversational and generative artificial intelligence (AI) has led to the increased deployment of AI tools in healthcare settings. While these conversational AI tools promise efficiency and expanded access to healthcare services, there are growing concerns ethically, practically and in terms of inclusivity. This study aimed to identify activities which reduce bias in conversational AI and make their designs and implementation more equitable. A qualitative research approach was employed to develop an analytical framework based on the content analysis of 17 guidelines about AI use in clinical settings. A stakeholder consultation was subsequently conducted with a total of 33 ethnically diverse community members, AI designers, industry experts and relevant health professionals to further develop a roadmap for equitable design and implementation of conversational AI in healthcare. Framework analysis was conducted on the interview data. A 10-stage roadmap was developed to outline activities relevant to equitable conversational AI design and implementation phases: 1) Conception and planning, 2) Diversity and collaboration, 3) Preliminary research, 4) Co-production, 5) Safety measures, 6) Preliminary testing, 7) Healthcare integration, 8) Service evaluation and auditing, 9) Maintenance, and 10) Termination. We have made specific recommendations to increase conversational AI's equity as part of healthcare services. These emphasise the importance of a collaborative approach and the involvement of patient groups in navigating the rapid evolution of conversational AI technologies. Further research must assess the impact of recommended activities on chatbots' fairness and their ability to reduce health inequalities.

Multifactor roadmap for designing low‐power‐consumed micro thermoelectric thermostats in a closed‐loop integrated 5G optical module

AbstractAs the core components of fifth‐generation (5G) communication technology, optical modules should be consistently miniaturized in size while improving their level of integration. This inevitably leads to a dramatic spike in power consumption and a consequent increase in heat flow density when operating in a confined space. To ensure a successful start‐up and operation of 5G optical modules, active cooling and precise temperature control via the Peltier effect in confined space is essential yet challenging. In this work, p‐type Bi0.5Sb1.5Te3 and n‐type Bi2Te2.7Se0.3 bulk thermoelectric (TE) materials are used, and a micro thermoelectric thermostat (micro‐TET) (device size, 2 × 9.3 × 1.1 mm3; leg size, 0.4 × 0.4 × 0.5 mm3; number of legs, 44) is successfully integrated into a 5G optical module with Quad Small Form Pluggable 28 interface. As a result, the internal temperature of this kind of optical module is always maintained at 45.7°C and the optical power is up to 7.4 dBm. Furthermore, a multifactor design roadmap is created based on a 3D numerical model using the ANSYS finite element method, taking into account the number of legs (N), leg width (W), leg length (L), filling atmosphere, electric contact resistance (Rec), thermal contact resistance (Rtc), ambient temperature (Ta), and the heat generated by the laser source (QL). It facilitates the integrated fabrication of micro‐TET, and shows the way to enhance packaging and performance under different operating conditions. According to the roadmap, the micro‐TET (2 × 9.3 × 1 mm3, W = 0.3 mm, L = 0.4 mm, N = 68 legs) is fabricated and consumes only 0.89 W in cooling mode (QL = 0.7 W, Ta = 80°C) and 0.36 W in heating mode (Ta = 0°C) to maintain the laser temperature of 50°C. This research will hopefully be applied to other microprocessors for precise temperature control and integrated manufacturing.

Preclinical Evaluation of Novel Positron Emission Tomography (PET) Probes for Imaging Leucine-Rich Repeat Kinase 2 (LRRK2).

Parkinson's disease (PD) is one of the most highly debilitating neurodegenerative disorders, which affects millions of people worldwide, and leucine-rich repeat kinase 2 (LRRK2) mutations have been involved in the pathogenesis of PD. Developing a potent LRRK2 positron emission tomography (PET) tracer would allow for in vivo visualization of LRRK2 distribution and expression in PD patients. In this work, we present the facile synthesis of two potent and selective LRRK2 radioligands [11C]3 ([11C]PF-06447475) and [18F]4 ([18F]PF-06455943). Both radioligands exhibited favorable brain uptake and specific bindings in rodent autoradiography and PET imaging studies. More importantly, [18F]4 demonstrated significantly higher brain uptake in the transgenic LRRK2-G2019S mutant and lipopolysaccharide (LPS)-injected mouse models. This work may serve as a roadmap for the future design of potent LRRK2 PET tracers.

The cellular landscape of the endochondral bone during the transition to extrauterine life.

The cellular complexity of the endochondral bone underlies its essential and pleiotropic roles during organismal life. While the adult bone has received significant attention, we still lack a deep understanding of the perinatal bone cellulome. Here, we have profiled the full composition of the murine endochondral bone at the single-cell level during the transition from fetal to newborn life and in comparison with the adult tissue, with particular emphasis on the mesenchymal compartment. The perinatal bone contains different fibroblastic clusters with blastema-like characteristics in organizing and supporting skeletogenesis, angiogenesis and hematopoiesis. Our data also suggest dynamic inter- and intra-compartment interactions, as well as a bone marrow milieu that seems prone to anti-inflammation, which we hypothesize is necessary to ensure the proper program of lymphopoiesis and the establishment of central and peripheral tolerance in early life. Our study provides an integrative roadmap for the future design of genetic and cellular functional assays to validate cellular interactions and lineage relationships within the perinatal bone.

MRNAid, an open-source platform for therapeutic mRNA design and optimization strategies.

Recent COVID-19 vaccines unleashed the potential of mRNA-based therapeutics. A common bottleneck across mRNA-based therapeutic approaches is the rapid design of mRNA sequences that are translationally efficient, long-lived and non-immunogenic. Currently, an accessible software tool to aid in the design of such high-quality mRNA is lacking. Here, we present mRNAid, an open-source platform for therapeutic mRNA optimization, design and visualization that offers a variety of optimization strategies for sequence and structural features, allowing one to customize desired properties into their mRNA sequence. We experimentally demonstrate that transcripts optimized by mRNAid have characteristics comparable with commercially available sequences. To encompass additional aspects of mRNA design, we experimentally show that incorporation of certain uridine analogs and untranslated regions can further enhance stability, boost protein output and mitigate undesired immunogenicity effects. Finally, this study provides a roadmap for rational design of therapeutic mRNA transcripts.

Designing Technology Diffusion Roadmaps of Thermoelectric Generators Toward a Carbon-Neutral Society

Thermoelectric generators (TEGs) have the potential to contribute significantly to the realization of a carbon-neutral society by recovering electrical energy from various types of waste heat. Potential applications include wireless sensors, automobiles, and wearable devices. Despite their promise, however, TEGs have not been widely diffused due to their currently high cost and low energy conversion efficiency. This article aims to design technology diffusion roadmaps in order to clarify the gap between market needs and technological development, and discusses ways to bridge this gap. Drawing on the backcasting-based roadmap design method developed previously by the authors, TEG roadmaps were prototyped using online interviews with two companies that are developing and marketing their own TEGs for specific applications. Based on the responses, a roadmap design process consisting of five steps—problem setting, preparation, information gathering, structuring and analyzing the results, and feedback—was developed. To demonstrate the proposed method, a case study in which various digital platforms and tools were utilized to efficiently exploit the knowledge and opinions of participating experts was conducted online. Results revealed a pathway by which TEGs could be effectively diffused to meet both social and market needs over the next 30 years. Internet of Things sensors and automobiles were identified as promising applications for the near term, while, for the longer term, the need to develop new solutions and surrounding technologies in order to expand future demand for TEGs was made evident.

Fabricating hybrid DSPC:DOPC:P(OEGMA-co-LMA) structures: Self-assembly as the milestone of their performance

Lipid/polymer nanoparticles are among the most promising hybrid nanoplatforms for pharmaceutical applications, and their many advantages are well established. Despite the efforts, the design parameters that influence their performance have not been deciphered in total yet. In this study, thermodynamic evaluation of lipid and lipid/copolymer bilayers was conducted via differential scanning calorimetry (DSC). Based on their biophysical behavior and by modulating different design parameters for each system, selected lipid/copolymer nanostructures were prepared by the thin film hydration method. The biomaterials of choice were 1,2-dioctadecanoyl-sn-glycero-3-phosphocholine (DSPC), 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), and a linear statistical (random) copolymer comprised of oligo (ethylene glycol) methyl ether methacrylate (OEGMA) and lauryl methacrylate (LMA). Their features were examined by light scattering techniques, fluorescence spectroscopy, and MTS assay. For the first time DSPC:DOPC:P(OEGMA-co-LMA) hybrid systems were successfully formulated and the most prominent factors influencing their thermodynamic, physicochemical, and toxicological properties were investigated. Our results indicate that self-assembly is pivotal for hybrid systems performance and is mediated via random topology of copolymer, lipid composition, hydrophilic to hydrophobic balance, and lipid to polymer ratio. Having in mind fast clinical translation, we hope this work to contribute to a design road map for efficient lipid/copolymer nanostructure development.

Multi-objective optimization of supercritical CO2 Brayton cycles for coal-fired power generation with two waste heat recovery schemes

The efficiency of supercritical CO2 (sCO2) Brayton cycle (SCBC) based coal-fired power generation can be enhanced by harnessing the waste heat from sCO2 cooling and flue gas, which currently remains largely untapped. In this paper, we propose two types of design roadmap for utilizing this waste heat. The first method involves using an organic Rankine cycle (ORC) to generate additional power, while the second method utilizes LiBr/H2O absorption refrigeration cycle (ARC) to further cool down compressor inlet sCO2, and thereby reduces its compression power consumption. An energy-economic-environmental multi-criteria models are formulated to access performance of the aforementioned designs and compare them with a standalone sCO2 Brayton recompression cycle system (Standalone). The non-dominated sorting genetic algorithm II is applied to carry out the multi-objective optimization of the three systems. The results show that the SCBC-ARC system achieves the maximum thermal efficiency (ηth) and minimum environmental impact load (EIL), while SCBC-ORC system achieves the minimum levelized cost of electricity (LCOE). We also find that minimizing LCOE conflicts with maximizing ηth and minimizing EIL, respectively. The relationship between maximizing ηth and minimizing EIL is consistent, suggesting that increasing efficiency will alleviate environmental impact of the systems. We also identify and discuss balanced designs for the systems, and our results show that the ηth of SCBC-ORC and SCBC-ARC is 1.40% and 1.70% higher than the Standalone, respectively, the LCOE is 0.56% lower and 3.66% higher than Standalone, respectively, and EIL is 1.16% and 1.59% lower than the Standalone, respectively.

Effectiveness of multi-junction cells in near-field thermophotovoltaic devices considering additional losses

Abstract Thermophotovoltaic (TPV) energy converters hold substantial potential in converting thermal radiation from high-temperature emitters into electrical energy through photovoltaic (PV) cells, offering applications ranging from solar energy harvesting to waste heat recovery. Near-field TPV (NF-TPV) devices, focused on enhancing power output density (POD), exhibit unique potential by harnessing photon tunneling. However, this potential can be mitigated by additional losses arising from high photocurrent densities and corresponding scalability issues. This study comprehensively investigates the effectiveness of multi-junction-based NF-TPV devices, accounting for additional losses. We propose two approximative expressions to quantify the impact of additional losses and characterize current density-voltage curves. Verification against rigorously optimized results establishes a criterion for effective performance. Our method provides precise POD estimations even for devices with 10 or more subcells, facilitating performance analysis across parameters like vacuum gap distance, cell width, emitter temperature, and the number of subcells compared to far-field counterparts. This research outlines a roadmap for the scalable design of NF-TPV devices, emphasizing the role of multi-junction PV cells. The analytical framework we developed will provide vital insights for future high-performance TPV devices.

Optimized Red-Absorbing Dyes for Imaging and Sensing.

Rhodamine dyes are excellent scaffolds for developing a broad range of fluorescent probes. A key property of rhodamines is their equilibrium between a colorless lactone and fluorescent zwitterion. Tuning the lactone-zwitterion equilibrium constant (KL-Z) can optimize dye properties for specific biological applications. Here, we use known and novel organic chemistry to prepare a comprehensive collection of rhodamine dyes to elucidate the structure-activity relationships that govern KL-Z. We discovered that the auxochrome substituent strongly affects the lactone-zwitterion equilibrium, providing a roadmap for the rational design of improved rhodamine dyes. Electron-donating auxochromes, such as julolidine, work in tandem with fluorinated pendant phenyl rings to yield bright, red-shifted fluorophores for live-cell single-particle tracking (SPT) and multicolor imaging. The N-aryl auxochrome combined with fluorination yields red-shifted Förster resonance energy transfer (FRET) quencher dyes useful for creating a new semisynthetic indicator to sense cAMP using fluorescence lifetime imaging microscopy (FLIM). Together, this work expands the synthetic methods available for rhodamine synthesis, generates new reagents for advanced fluorescence imaging experiments, and describes structure-activity relationships that will guide the design of future probes.

Oxygen vacancies and local amorphization introduced by high fluence neutron irradiation in β -Ga2O3 power diodes

Beta phase gallium oxide (β-Ga2O3) is emerging as a promising material for space applications due to its unique properties and potential high performance in extreme environments. In this work, we systematically study the impact of β-Ga2O3 Schottky barrier diodes (SBDs) under a high fluence neutron irradiation to explore the degradation mechanism of the devices. After irradiated by neutrons with an average energy of 1–2 MeV and a dose rate of 1.3 × 1012 cm−2 s−1, SBDs with a homoepitaxial layer suffered serious performance degradation. The main manifestation of this degradation was a substantial increase in on-resistance, which rose from 3.9 to 3.5 × 108 mΩ·cm2 under the aforementioned irradiation conditions. The appearance of amorphous/polycrystalline striped lattice damage in the epitaxial layer as well as the presence of deep-level defects caused by oxygen vacancies are factors related to this phenomenon. The simulation revealed that the capture reaction of neutrons and Ga elements is the primary cause of neutron irradiation. This reaction generates high-energy beta- particles (β-particles) resulting in the formation of defects. This paper reveals the degradation mechanism of β-Ga2O3 SBDs under neutron irradiation and provides a possible design roadmap for radiation-resistant β-Ga2O3 power devices. Moreover, a high-temperature oxygen annealing process was implemented, which proved to be in restoring the device performance.

Roadmaps for heating and cooling system transitions seen through uncertainty and sensitivity analysis

Future district heating systems should enable efficient and economic energy supply, which can be achieved by lowering the system temperatures and boosting it at demand-side. Current solutions include the ultra-low-temperature district heating (ULTDH) and fifth generation district heating and cooling (5GDHC) systems. The transition towards these systems is subject to multiple future uncertainties such as the energy price, investment cost, and demand changes, which were missing in previous works. To investigate the effects of these uncertainties on conclusions brought by established design roadmaps for future DHCs, a five-step framework, which combines the energy system optimization with stochastic simulations, uncertainty analysis and sensitivity assessment, is developed in this study. The framework is applied on a hypothetical 0.25 km2 square district with varying uncertain parameters. Based on stochastic cases, the index named cost-saving probability (CSP) is utilized to reflect the potential of being economic attractive when comparing the energy systems. For the transition towards the ULTDHC, 5GDHC, and individual systems, the most sensitive factors for the CSP are the area demand density, overlapping heating and cooling demand, and linear demand density, respectively. The investment in thermal energy storage (TES) becomes important only when the integration of a larger share of renewable energy is targeted. A roadmap summarizing the promoting and hindering factors for the system transition is provided, pointing out the future focus area for DHC design. The results from the sensitivity analysis also revealed the limited role of TES in integrating variable renewable energy in high-efficiency DHC systems.