BZPEERReading, trust and collaboration for research
Menu

Discover

GraphFollow connections around a paper, topic or saved view.

Workspaces

HomePick up where your research flow left off.InboxHandle requests, replies and notifications from one place.CollectionsCurate reading lists, evidence sets and shareable dossiers.ResearchSee your private provenance graph, trail and imports.CollaborationMove from discovery into focused discussion rooms.PublishDraft, preview and publish full-text research articles.

Network

ExpertsFind specialists worth following or asking for help.CommunitiesJoin research circles organized around shared work.PartnersSee external organizations active around the same topics.

Opportunities

ListingsBrowse roles, calls and collaborations with clearer fit signals.

Account

Log inReturn to your reading and collaboration workspace.Create accountStart saving work, following people and joining teams.
Log inCreate account

Researcher profile

Zixiang Wei

Zixiang Wei contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
cond-mat.softArtificial IntelligenceComputer VisionRobotics

Trust snapshot

Quick read

Trust 15 - UnverifiedVerification L1Unclaimed author
3works
0followers
4topics
4close collaborators

Actions

Decide how to stay connected

Follow researcher0

Identity and collaboration

How to connect with this researcher

Claiming links this public author record to a researcher profile and unlocks direct collaboration workflows.

Log in to claim

Direct collaboration

Open a focused conversation when the fit is right

Claim this author entity first to unlock direct invitations.

Research graph

See the researcher in context

Open full explorer

Inspect adjacent work, topics, institutions and collaborators without jumping out to a separate graph page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Published work

3 published item(s)

preprint2026arXiv

EdgeLPR: On the Deep Neural Network trade-off between Precision and Performance in LiDAR Place Recognition

Place recognition is essential for long-term autonomous navigation, enabling loop closure and consistent mapping. Although deep learning has improved performance, deploying such models on resource-constrained platforms remains challenging. This work explores efficient LiDAR-based place recognition for EdgeAI by leveraging Bird's Eye View representations to enable lightweight image-based networks. We benchmark representative architectures without aggregation heads using a unified descriptor scheme based on global pooling and linear projection, and evaluate performance under FP32, FP16, and INT8 quantization. Experiments reveal trade-offs between accuracy, robustness, and efficiency: FP16 matches FP32 with lower cost, while INT8 introduces architecture-dependent degradation. Overall, the presented results are a strong basis for future research on 'use-case'-aware quantisation of Neural Networks for Edge deployment.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Integrated nanoextraction and colorimetric reactions in surface nanodroplets for combinative analysis

A combinative approach for chemical analysis makes it possible to distinguish a mixture of a large number of compounds from other mixtures in a single step. This work demonstrates a combinative analysis approach by using surface nanodroplets for integrating nanoextraction and colorimetric reactions for the identification of multi-component mixtures. The model analytes are acidic compounds dissolved in oil that are extracted into aqueous droplets on a solid substrate. The proton from acid dissociation reacts with the halochromic chemical compounds inside the droplets, leading to the color change of the droplets. The rate of the colorimetric reaction exhibits certain specificity for the acid type, distinguishing acid mixtures with the same pH value. The underlying principle is that the acid transport rate is associated with the partition coefficient and the dissociation constant of the acid, in addition to the concentration in oil. As a demonstration, we showed that droplet-based combinative analysis can be applied for anti-counterfeiting of various alcoholic spirits by comparing decolor time of organic acid mixtures in the spirits. The readout can be done by using a common hand-hold mobile phone.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Oiling-out Crystallization of Beta-Alanine onSolid Surfaces Controlled by Solvent Exchange

Droplet formation in oiling-out crystallization has important implication for separation and purification of pharmaceutical active ingredients by using an antisolvent. In this work, we report the crystallization processes of oiling-out droplets on surfaces during solvent exchange. Our model ternary solution is beta-alanine dissolved in isopropanol and water mixture. As the antisolvent isopropanol displaced the alanine solution pre-filled in a microchamber, liquid-liquid phase separation occurred at the mixing front. The alanine-rich subphase formed surface microdroplets that subsequently crystallized with progression of solvent exchange. We find that the flow rates have significant influence on the droplet size, crystallization process, and growth rate, and final morphology of the crystals. At fast flow rates the droplets solidified rapidly and formed spherical-cap structures resembling the shape of droplets, in contrast to crystal microdomains or thin films formed at slow flow rates. On a highly hydrophilic surface, the crystals formed thin film without droplets formed on the surface. We further demonstrated that by the solvent exchange crystals can be formed by using a stock solution with a very low concentration of the precursor, and the as-prepared crystals can be used as seeds to trigger crystallization in bulk solution. Our results suggest that the solvent exchange has the potential to be an effective approach for controlling oiling-out crystallization, which can be applied in wide areas, such as separation and purification of many food, medical, and therapeutic ingredients.

0 citations0 reviewsNo code linkedOpen access